Tech-Driven Business

Get ready to think differently about how technology driven solutions can lead to business success. Mustansir Saifuddin is the co-founder of Innovative Solution Partners. With a career that spans multiple industries and a variety of roles including a software quality assurance engineer to leading global teams and projects, he knows what it takes to fuse technology with what a business wants. Listen as he interviews tech experts, business experts, and visionaries on their successes, challenges, and lessons learned. We’ll cover everything from SAP and ERP focused solutions, to leveraging data analytics, to how to achieve your business goals with technology.

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Tuesday Nov 15, 2022

In this episode of Tech-Driven Business, Mustansir Saifuddin continues the conversation with Matt Florian of Comerit on how enterprises can leverage hybrid cloud data warehouse solutions. Matt shares the value of hybrid solutions, how to approach creating a hybrid solution, and lessons he's learned along the way. His key takeaway: focus on flexibility and resiliency in your data architecture so you can create data products that can answer multiple questions.  Matt has more than 25 years of leadership in data and enterprise architecture in numerous industries. He has successfully delivered enterprise data transformation projects for government, telecommunication, retail, manufacturing, and financial services sectors. Matt began consulting focusing on data warehousing in telecommunication for national providers. Over the course of his career has consulted for Oracle, IBM, and Unisys across many industries. His leadership, experience, and clarity of technical topics earned him the trust of client executive leadership. Matt’s talent to develop and lead teams is the key to his successful delivery of projects for clients. Connect with Us:LinkedIn: Matt Florian Mustansir Saifuddin Innovative Solution Partners  Twitter: @MmsaifuddinYouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   Episode Transcript [00:00:03.010] - Mustansir Saifuddin Welcome to Tech-Driven Business. Brought to you by Innovative Solution Partners. In this second episode of a multipart series, I welcome back Matt Florian of Comerit. Listen in as Matt and I discuss the value of hybrid cloud data warehouse solutions, including how to approach creating one, and lessons learned along the way. It's more than about just getting it in place.   [00:00:35.510] - Mustansir Saifuddin Hello, Matt. Welcome to Tech-Driven Business. How are you, man?   [00:00:39.130] - Matt Florian I'm doing very well Mustansir. How are you, sir?   [00:00:42.860] - Mustansir Saifuddin Another beautiful day. Hey, thank you for our first conversation when we started off this whole cloud data warehouse topic, and I'd like to continue our discussion on this topic. And I think one area that I feel a lot of conversations are happening is the hybrid environment. So I thought we should talk about that in today's session and wanted to get your take on that.   [00:01:15.190] - Matt Florian Oh, absolutely. It's a very common conversation that goes on with clients nowadays and trying to figure out what is it that they really want to go do and how much risk they want to carry on it. You'll hear hybrid pop up there every time. So I think one of the biggest problems they have is what the heck does hybrid need?   [00:01:34.090] - Mustansir Saifuddin Yeah, I hear you, and I think this will be really helpful, especially with your experience. And when you look at across the board, doesn't matter what industry you're in, it seems like customers are not ready to make that jump. Right. They are looking at ways to either extend their environments into a way that they can sustain in the short term and then plan for the long term.   [00:02:01.710] - Matt Florian Right.   [00:02:01.930] - Mustansir Saifuddin So this conversation would be very beneficial.   [00:02:05.820] - Matt Florian I completely agree.   [00:02:08.890] - Mustansir Saifuddin All right, so let's start with this. Let's start with a very basic thing. I think I would like to have my listeners get an understanding of when we talk about hybrid. What do you really mean and why hybrid? I think those two questions I like to start with.   [00:02:24.580] - Matt Florian Sure. You think of hybrid. Hybrid's about taking two options that are very similar to each other. They have overlapping functionality and saying.   [00:02:40.720] - Matt Florian I want the safety and security of what I've been doing, but I want to start dabbling into another way to do it. And we see that a lot with SAP customers who have a lot of security inside of being inside of BW, and then maybe they want to dabble over into cloud computing with Snowflake. And how do you do that? There's different ways that looks at you. Same thing we said, like the security of SAC, but maybe I want to use Power Bi or Sigma or something like that and balance it out, but don't extend their risk and just jump and go do it. So SAP customers don't tend to be risk heavy. They like to avert it as much as possible.   [00:03:32.590] - Mustansir Saifuddin Absolutely. And that makes sense, right? Especially when you have big landscapes and you want to manage your environment, what's the best way to do it? Right? So I guess I heard two things right, and I'm talking about benefits. It seems like you want to avoid risk as much as possible. At the same time try out new technology. Are there any other benefits that you see from your viewpoint when you take a hybrid approach?   [00:04:01.310] - Matt Florian So the hybrid is a benefit to using hybrid is that you get to focus on a particular use case that is of value and benefit to you. And I often see customers go down that hybrid because they want to go and have more flexibility to blend SAP data with other third party data and do it just easier. And so they'll go down this hybrid approach because, well, let's face it, BW does a lot of analytics well and don't break what's really working well for you. On the other hand, wanting to know your organic growth against other metrics that come from Salesforce or other CRMs or from Google Analytics, that's a whole other dimension. And that's hybrid really can help bridge that and be able to answer some questions that SAP doesn't answer easily.   [00:05:04.990] - Mustansir Saifuddin Absolutely, I think so. You use the SAP reference over here, right? So I guess I'll come from that angle now. So I'm an SAP customer. Why would I want to think about a hybrid solution? And I believe you kind of dabbled into the answer, but give some examples that you can think of where an SAP customer would like to go the route of hybrid.   [00:05:31.390] - Matt Florian So a couple of immediate use cases where hybrid can come into play and really help out is let's go with archiving and being able to look at archived data along with live data. Archiving into a cloud database is one option for archiving either a system that you've migrated off and you did a brownfield implementation. So you have historical data sitting in one place and all your new data building up in another. S/4HANA sitting over here, and you want to bring that together. Well, hybrid is a good option for bringing and looking at historical data along with your current transactions. So that's one area that you may want to go and dabble in. Another good use case is that you really want to implement machine learning and AI, and you want to watch streams of data and you want to train data models for machine learning. Well, that's a hybrid approach gives just a wide open ecosystem of tools that you can use for machine learning and AI, and it would really be beneficial. Again, just easier, for sure.   [00:06:57.240] - Mustansir Saifuddin No, I like your examples. I think kind of puts things in perspective, right? I mean, especially like I said, if things are working, you don't want to break it. At the same time, how can I bring in new ideas, new technology, or new approaches to make my environment easier to maintain and maybe more future proof as far as where I want to go in the long run, right?   [00:07:20.060] - Matt Florian Right. Absolutely.   [00:07:23.360] - Mustansir Saifuddin That's great. So I think let's talk about when we are on that journey, especially folks who are maybe just starting or like to go this direction when we look at from a good practices point of view. Do you have any suggestions or ideas as far as timelines for keeping the hybrid environment?   [00:07:48.860] - Matt Florian For keeping or building? What does it take to do? Is that what you're thinking?   [00:07:55.610] - Mustansir Saifuddin So I'm thinking two ways, right. One, is a lot of times the question come up, right? If I want to go the hybrid route, what is the best way to do it? Do I have a strategy? Timline strategy like I'm going to sunset the system in a certain time frame versus going maybe a one shot approach. I'm going to shut down this existing environment and then move completely into cloud. But I feel like hybrid is becoming a lot more common practice these days. So what would be a good timeline as far as a use case that we can apply in this situation?   [00:08:40.290] - Matt Florian Sure. So we'll go back to that migrating to S/4HANA as an example. If you're going to migrate to S/4HANA and you are going to go with a brownfield or even greenfield strategy on migrating over to that from a homegrown point of sale system to different ERP coming in, whatever it is. That's a great time to go and make that decision of, I'm going to do this hybrid and start the work even before your migration for your S/4HANA and start bringing that information in and building a common, unified model. That would be the place to start. A lot of companies begin that work way too late, and they're trying to play catch up and they want to have unified data at day one, but they don't because they didn't put in that work early enough to say, how am I going to unify my data? And there are strategies to do it, but you need to think it from the very beginning so that you have a solid strategy to make it happen. The other approach is if you're, let's say, you're going to incrementally go and build out your hybrid. In that case, you start with a very high impact use case, something that a lot of people would go and jump on and want to use, and oftentimes it's going to be directly related to sales.   [00:10:16.690] - Matt Florian That's something that's driving top line growth and wanting to tie that to other third party. Start with a very foundational use case that you can build from and then build the processes out around that. That just builds. It just naturally grows from there.   [00:10:38.810] - Mustansir Saifuddin For sure. You kind of touched upon two topics over here, and I like to jump a little bit deeper into this one idea that you just shared. Like, when I'm going the hybrid route, what should be the focus from an implementation perspective, when you go in the hybrid approach, what are some of the things that you should keep in mind?   [00:11:08.210] - Matt Florian Well, you should keep in mind first what's your point of reference is going to be in that hybrid. By point of reference, the hybrid system needs to have something to anchor itself to. For instance, if you're going in and you're going to build out again, I'm going to go back to the SAP. If you're building S/4HANA out, your point of reference is that S/4HANA model and then blending processes into that S/4HANA model. So S/4HANA becomes that anchor, and then you're building out a hybrid model that is SAP plus Salesforce, SAP plus HubSpot plus Google Analytics plus Legacy. But that's your foundation. If you can keep yourself focused on a foundation topic, then you'll be successful. If you go in without that focus, then the lack of clarity creates easily, will create chaos in your hybrid, and then you'll have a high risk of your perception of failure because it didn't answer the set of questions.   [00:12:29.510] - Mustansir Saifuddin Yeah, I think that's an interesting insight, what you just shared. Because I think it seems like in order for you to keep your hybrid environment, I'm looking at how to be successful in this approach.   [00:12:47.140] - Mustansir Saifuddin It seems like if you anchor yourself with a certain system as a starting point, it allows you or it gives you the flexibility to build it out versus going it all out and try to do too many things at the same time will set you up for failure. That's how I'm reading into that.   [00:13:05.650] - Matt Florian It will. If you build out based upon your process areas of the business, and you build out the models from that and connect them, then you have a hybrid environment that is able to answer a whole breadth of questions because they're tied. There's a logical story being told by the data. If you don't have that focus, then the data can't tell a story. And you want that data to tell a story. And all of it has story, and some of that story is from archives, from prior implementations. But it has a story to tell. And in order to do that, you have to give it context and focus. And that's why you need to start this way. You need to keep that something to ground it.   [00:13:58.860] - Mustansir Saifuddin I think, for sure. And I think one of the things, one of the takeaways that I see from this conversation is the fact that a lot of customers may have, depending on the industry, you may have a different set of challenges where you want to use this approach. There are certain things that are working in your current environment. You want to keep that as is. But there are other things that you want to bring in multiple data sets. And you take this approach of going to Snowflake using this multiple data set approach. But having an anchor system in the middle try to leverage that as a starting point. Right?   [00:14:37.210] - Matt Florian Yeah. Because really your anchor is if you think about it another way, your anchor is your process. What is your process today? And that is your anchor. The process is supported by a system of some sort, whatever it may be, but the process is the anchor. And using that as the point lets you go and have your insights and understanding about what it is that you're attempting to achieve.   [00:15:08.140] - Mustansir Saifuddin That kind of takes me to this question which I always ask as one key takeaway. Right. And today's conversation is in a way fairly broad, but I like to keep it controlled and in a way that makes sense for someone who is looking this route. So what would be the one thing that you would share with them as far as if they are thinking of hybrid or they're already on a journey to hybrid? What are some of the key takeaways that you want them to leave the session?   [00:15:41.140] - Matt Florian If you're thinking about go to hybrid and working that way, it's not going to be just focused on what that process is, but architecturally from a data perspective is that think of that hybrid in the approach of creating data products that can answer many questions. Don't try to just answer one. Build an architecture that lets you use that hybrid data as Lego blocks to build and answer other questions. Because if you try to just focus on answering a question, then you're losing other valuable insights that you can gather by blending more data. That's what your hybrid is going to do. You're going to blend data together and you have to architect with intent so that you can answer more questions and have flexibility.   [00:16:39.860] - Mustansir Saifuddin Yeah, I like your way of thinking, especially when you are looking at the future state. A lot of times folks want to take a narrow approach of getting things done, but that may not be the right answer, right.   [00:16:54.790] - Matt Florian It's not just about getting it done. It's about architecting for the future and for your resiliency. And there are many models, many approaches, methodologies that let you architect for resiliency. And when you go down this path, that should be a guiding principle of what that hybrid is built off of, is modeled and architected for that resiliency so that you can answer many questions and be more agile in your answering your questions to the business and respond to changing economic and market conditions.   [00:17:35.660] - Mustansir Saifuddin Great, thank you. This is really helpful.   [00:17:43.910] - Mustansir Saifuddin Thanks for listening to Tech-Driven Business brought to you by Innovative Solution Partners. Matt shared some valuable information on hybrid cloud data warehouse solutions. His main takeaway: focus on a data architecture perspective so your data can tell a story and answer multiple questions. It's not about just getting it done. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation by visiting isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.  

Friday Oct 07, 2022

In this next episode of Tech-Driven Business, Matt Florian of Comerit, joins Mustansir Saifuddin to talk about the urgency and motivation for companies to move to a cloud-based data warehouse. This is the beginning of a series of episodes that will dive into how newer tools, like Snowflake, are changing the landscape for companies to blend in different types of data, including their existing SAP systems.  Matt's takeaway: don't wait to start. There will always be something new coming on the horizon so start with a small project and buildup. Matt has more than 25 years of leadership in data and enterprise architecture in numerous industries. He has successfully delivered enterprise data transformation projects for government, telecommunication, retail, manufacturing, and financial services sectors. Matt began consulting focusing on data warehousing in telecommunication for national providers. Over the course of his career has consulted for Oracle, IBM, and Unisys across many industries. His leadership, experience, and clarity of technical topics earned him the trust of client executive leadership. Matt’s talent to develop and lead teams is the key to his successful delivery of projects for clients. Connect with Us:LinkedIn: Matt Florian, Mustansir Saifuddin, Innovative Solution Partners, Twitter: @PragmaticEA, @Mmsaifuddin,YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   Episode Transcript: [00:00:03.690] - Mustansir Saifuddin Welcome to Tech-Driven Business. Brought to you by Innovative Solution Partners. In this first episode of a multipart series, I welcome Matt Florian of Comerit. Listen in as Matt shares his thoughts on why companies are moving to a cloud data warehouse with such a sense of urgency. With data volumes growing, it's important for companies to take advantage of the power of new technology tools that Matt talks about, including snowflake.   [00:00:35.510] - Mustansir Saifuddin Hello, Matt. How are you?   [00:00:37.600] - Matt Florian I'm doing fine Mustansir how are you?   [00:00:40.090] - Mustansir Saifuddin Doing well. Welcome to Tech-Driven Business. It's a pleasure to have you on my show.   [00:00:46.160] - Matt Florian I'm very grateful to be a member of it and be part of this with you, man.   [00:00:51.710] - Mustansir Saifuddin Awesome. So today we will kick off basically the idea is to kick off a series of podcasts which will revolve around cloud based data warehouses. And we would like to dive into this topic of why companies are transitioning to cloud based data warehouses. Right. And at the same time, what are some of the benefits that they are getting with this move? How does that sound to you?   [00:01:18.420] - Matt Florian That sounds great. Let's get talking.   [00:01:21.110] - Mustansir Saifuddin Awesome. Okay. I know this topic is very near and dear to you, and I'm very glad that we have you on our show, and this will be a great conversation. So let's start with our why, right? So why it is so important right now, moving to a cloud based data warehouse? And the urgency. I think there's two components of this. Right. Why is it important for companies and the same time? What is the urgency behind it?   [00:01:47.800] - Matt Florian Sure. Well, I think that a lot of companies have taken a fair amount of time in the last several years of getting their processes in place and fixing processes with implementations of like SAP and other large ERP. At the same time, you have other parts of the business that are trying to get process in place with a Salesforce or other CRM and other tools out there like that. And each of these platforms, they've been operating fairly independently. And you can do a lot outside of SAP, but getting the full value, I think businesses are looking to get leverage, full value of those implementations, that investment by blending that data with other data, with other stuff. And that's why there's a big urgency and a big move, because it's just being able to do that and do it easily.   [00:02:48.940] - Mustansir Saifuddin That makes sense. Yeah. I think one key word that I got out of this conversation is you mentioned SAP being a central focal point for a lot of companies, but at the same time, they do have these other systems where they want to bring in this information together and blend it together.   [00:03:08.220] - Matt Florian And even we see this a lot with SAP implementation right. That SAP is able to manage a good part of the process, but it doesn't always manage all of the process. There's still other third party applications outside of the SAP ecosystem that are part of the business process and part of the outcomes of the business. And so if you're measuring your outcomes, you have to look at all that data together for sure.   [00:03:37.760] - Mustansir Saifuddin That brings up another point. What are some of the benefits of moving to the cloud? We talk about cloud in a lot of different contexts. Like when you talk about data warehouse and going to a data warehouse based cloud, what are some of the benefits that you see?   [00:03:52.090] - Matt Florian Well, a lot of the new modern data warehouse and cloud applications up there for data management focus, the purchasing and how you procure that is a whole different paradigm today than it was even five years ago. Five years ago, we talked about moving to the cloud and putting stuff into Azure data warehouse or Amazon Redshift. And when you did that, that was good. But you're buying capacity way up front. And some of the more modern warehouses I try not to use the warehouse term overboard here, but the modern data platforms out there really moved over to a utility model where you're charged just for what you're actually using. And combining that with serverless technology, where you're spinning up compute as needed on demand and scaling it, all things that we can't do in even some of the traditional AWS infrastructure and definitely could not do on-premise. So we have such flexibility to solve big problems with data with these cloud applications done smart.   [00:05:15.260] - Mustansir Saifuddin Yeah, I think the key word I hear from a lot of customers, and you mentioned it a couple of times here, is scalability. Right. And then the ability to control that which is not available or which was not available earlier in the traditional data platforms, if you want to use that terminology. Right. So it's a big win, especially when the data volumes are growing at a very rapid pace. And you do want to have that flexibility. And I think you do get both of them with this new move or the benefits that customers are seeing in real time now.   [00:05:56.860] - Matt Florian And if you think about we pick on SAC for a minute. We think about the infrastructure that we have to design and build out for SAP. For a lot of those implementations, you have to preplan everything that you're going to do. And once you go outside of that planned infrastructure, then it requires replanning. And so businesses will often limit themselves to what data they're going to do in there, not because of the limitations of data, but limitations of the infrastructure. So if I can change that dynamic and say, let's do this over in, say, a Snowflake data platform and do this inside a snowflake or inside a Snowflake, I can scale that infrastructure, the compute resources up and out dynamically. And that's something that you really cannot do inside of an SAP here and even in Azure data warehouse couldn't do that kind of scaling. So anybody that's able to make that easy like Snowflake did, that is a proof point right there to why we should move into the cloud.   [00:07:16.390] - Mustansir Saifuddin Yeah, definitely. That makes sense. I think that being said, let's talk about some of the choices available. I think that is one of the key questions a lot of customers are looking for now after COVID has been over. There seems to be a lot of things are happening in the cloud, especially with the amount of choices customers have. I mean, would you like to share some experiences about what are some of the data platform choices that are available and how to the stack up from your perspective?   [00:07:52.460] - Matt Florian Well, we've had opportunities to do cloud computing, cloud build, data warehouse in the cloud for several years now. And AWS and even Azure were very early into the gate of what you could do and they followed a model that was that procurement model inside of the cloud that says, hey, buy this much free capacity and you want to purchase that capacity. And that worked well. And I tell you, when we first did some Azure data warehouses, those warehouses screamed, we moved stuff off of Legacy to onprem into Azure and it was performing tremendously, but it also didn't scale. And how we moved data in was more complicated and it kept a lot of the Legacy mentality about infrastructure in place that you had to pre plan for. And so we didn't really see all the benefits that we should have seen out of it. The same can be said with AWS and Redshift, same kind of mentality, same idea. And it wasn't really until they said that Snowflake model came out that disrupted the marketplace. And I think you hear so much about Snowflake as being one of the predominant tools and platforms talked about today.   [00:09:30.510] - Matt Florian That's because it's utility, right? If I can service 50 queries with one set of compute, then I'm only charged for that one set of compute for the seconds in which I use it and then it turns off. And if I need to go and open up another room, it's like having you a big conference center. If I can service everybody in one room, great, I'm paid for one room. But if I need to spill out into three rooms, I can just spill out the three rooms, turn the lights on and run it until I don't need those other two rooms again, and then come back down into the one without any interactions, without any really taking action. And that's such a big difference in the compute and how we think about data. But it also required at the same time that we end up needing to change how we think about how we're putting data in and building that data. It's a complete mind shift entirely.   [00:10:34.240] - Mustansir Saifuddin That makes sense. I think that's the key piece, right? How you are able to get the flexibility and then control what you want and what you don't want at any given time, which is a lot of customers are asking for, especially when they don't know what the end state is going to look like. Right. I mean, this is what I need now, but it may change in a few months depending on what kind of information they want to bring into the platform and use it. Right. So that makes a lot of sense. Well, let's move away from this topic. Let's talk about on a personal note. You've been doing this technology for quite some time. What are some of the biggest accomplishment that you see you have accomplished over your personal or your professional career biggest.   [00:11:26.820] - Matt Florian Accomplishments besides maintaining a career as long as I have, that itself can be an accomplishment. But there you go. It's funny, early on in my career, I was on a project when I worked as a consultant for IBM and we built an Oncology database for Emory University. And this database, the contract issues can be run into, but the client really wanted a Cadillac for a database and platform that they had, but they had the money for a Yugo instead. And we built just a very streamlined platform and data engineering to build out this Oncology database and take all this clinical data that in the end off of a low cost ETL tool that at the end of the year end up winning awards for the actual design and implementation because it wouldn't identify all these clusters. All these clusters where cancer was occurring and fed and resulted in policy changes and all this great stuff that happened with it. It was done off of a low cost solution to a big problem. And when you can achieve something like that, simplicity to solve something big, man Elvis doesn't get much better than that.   [00:13:11.140] - Mustansir Saifuddin That's a great story. I think at the end of the day, I think it's just a lot of folks talk about data and building these huge data warehouse solutions, right? What is that? It's solving, right? And if you are solving a business case where the organization can see the value right off the bat, and I think that's what really stands out and that's what I got out of this story. So really awesome. Thank you. Thank you for sharing that. I think this is really good. So that kind of gets me into my next question. It's a nice segue, which is the real meat of this conversation, right. How can organizations make the right choice? I mean, there's a lot of choices, like you mentioned earlier, how can organizations make the right choice of picking the cloud data warehouse that works for them? What would you tell them?   [00:14:04.990] - Matt Florian So what I would tell them is to stop and take a look at what their end goal is for analytics and what it is that they're what type of measures and outcomes they're really trying to get at and build from there. Don't try to jump to the finish line without building a good quality data pipeline. We can rebuild things so much faster than what we used to. Now that being resistant to changing this because you're afraid of the cost and effort that it will take to rebuild your pipelines, that you have the tools that exist today. We can rapidly build and improve on pipelines. So it's taking a look at all the tools that you have and getting down to again, the simplest set of solutions to solve your biggest problems is achievable and it can be done.   [00:15:12.490] - Mustansir Saifuddin It seems like, to me, it seems like almost like know your end state and then kind of work backwards. And as long as you can see your end state as an organization, I think it's much easier to make the right choice in terms of these clusters of choices out there for customers.   [00:15:29.470] - Matt Florian Yep. And we help customers with that all the time.   [00:15:33.260] - Mustansir Saifuddin Definitely. I think that's the key word, right. Especially when there are choices, there are always confusion. And the confusion takes over the choices sometimes and it feels like you're going in a direction but you're not sure if the direction is correct or not unless you have that insights like you mentioned. Start with the end state and then look back and see what you need to achieve and how you can achieve that. Right, so that's a great advice.   [00:16:01.910] - Matt Florian It's confusion and just being stuck in old ways of thinking.   [00:16:27.210] - Mustansir Saifuddin That's the mindset. Right. And we talk about change management, especially when it comes to going to the cloud based data platforms. There is a huge change management involved in this whole process.   [00:16:27.210] - Matt Florian Yeah, we could have a whole episode just on the change management of going to the cloud   [00:16:28.840] - Mustansir Saifuddin and that's the goal. So I think what you want to do with this episode right now is to kind of set the stage of what's coming next. Especially we talk about the choices, we talked about what should be the right way to go, move forward, especially when you are trying to start on this journey or maybe you're in the middle of the journey and you're not seeing the results. Right. All of those different topics that we will cover them as we move along in this series. What is one of the key takeaways that you want to leave with the listeners today?   [00:17:03.710] - Matt Florian The key takeaway for those that are looking at cloud analytics and go into the cloud is to not wait to take that journey. Start it, you can start it with a small project and then build up, but start the journey and start getting there and going through that transformation. It's not a painful transformation, but it is a transformation and start making it happen. Don't wait, don't wait for the next thing to come out. There's always something else coming out, but there's some outstanding tools to go and make that move today, and there's no reason to wait anymore.   [00:17:49.160] - Mustansir Saifuddin What a great advice. Thank you for sharing that. I think that's what I'm hearing, and I keep seeing that time is of essence, right? Especially when folks are looking at moving that leap of fate into this new platform. It seems like the approach has changed in the past. You're planning it out for so long and then you get on the journey. Now it seems like the journey is almost here for you. You just need to get on it and move on forward.   [00:18:21.860] - Matt Florian Absolutely.   [00:18:24.190] - Mustansir Saifuddin Well, it's a great conversation with you, Matt, and I'm really glad that we were able to cover this topic today.   [00:18:36.640] - Mustansir Saifuddin Thanks for listening to tech-driven business brought to you by Innovative Solution Partners. Matt gave a great overview on the power of a cloud based data warehouse and why organizations should consider the move. His main takeaway? Don't wait. Start with a small project and build up. There will always be something new to come down the pipeline. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation by visiting us at isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.

Monday Sep 19, 2022

In this next episode of Tech-Driven Business, Mustansir Saifuddin continues the conversation with Hau Ngo of  Summerlin Analytics to discuss what enterprises should consider when choosing a tool like SAP Analytics Cloud (SAC). They cover everything from system landscape, data sources, visuals, security, and cost considerations. His key takeaway: look at how an analytics tool fits into your business, timeline, and total cost of ownership. Hau is an SAP Analytics Architect and an early adopter of SAP Analytics Cloud. In 2017, he helped a technology company in California consolidate global sales reporting across 7 different ERP systems. This effort culminated in one executive dashboard that displayed real-time information, eliminating weeks of manual coordination and data wrangling. Subsequently, Hau has presented his work at conferences such as SAPPHIRE 2019 in Orlando Florida, and has gone onward to help additional customers streamline their reporting processes and visualize the key company metrics. His experience with SAP Analytics Cloud extends to customers with various systems such as SAP Data Warehouse Cloud, BW/4HANA, and S/4HANA.  Connect with Us: LinkedIn: Hau Ngo, Mustansir Saifuddin, Innovative Solution Partners  Twitter: @MmsaifuddinYouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   Episode Transcript [00:00:05.170] - Mustansir Saifuddin Welcome to Tech-Driven Business. Brought to you by Innovative Solution Partners. In this episode, I welcome back Hau Ngo of Summerlin Analytics. Listen in as he shares key points to consider when choosing an analytics tool like SAP Analytics Cloud or SAC.   [00:00:27.750] - Mustansir Saifuddin Hello, how are you, man?   [00:00:29.530] - Hau Ngo I'm doing well, Mustansir how are you doing?   [00:00:32.610] - Mustansir Saifuddin Doing well. Welcome to Tech-Driven Business again.   [00:00:36.030] - Hau Ngo I'm good to be here. Thanks for having me.   [00:00:38.470] - Mustansir Saifuddin Awesome. Hey, so I know we've been kind of talking about different topics so far, and today I would like to kind of zoom in into this very important point where a lot of customers, when we talk about considering SAC as their cloud analytics tool of choice. What are some of the considerations they should take into account? That's how I'm thinking we can dig a little bit deeper, at least from a cloud analytics point of view.   [00:01:11.490] - Hau Ngo Yeah. So it really depends on what their system landscape looks like, if they have the legacy ECC or S/4, or maybe they have a BW or HANA Data Warehouse. So all those decisions sort of come into play. And I don't think a lot of customers are aware that SAC Analytics Cloud as a tool has different functionality depending on what you have on the back- end. So we can talk about that in this episode.   [00:01:43.230] - Mustansir Saifuddin Absolutely. And I think that kind of is a good segue to what I was alluding to earlier. When we talk system landscapes, it means a lot of different things depending on who you're asking. In this example, I'll use the system landscape, especially from a data source point of view. Especially when we're talking about creating models in SAC and those visuals, how does that come into play when you're dealing with, let's say, for example, an ECC source system or an S/4 for that matter, or compared to a non-SAP source, what are some of the things that you should take into account when creating your SAC models?   [00:02:30.070] - Hau Ngo Oh, sure. So one thing SAP does really well is they market their tool in terms of features and benefits and everything you can do from a Dashboarding perspective. I think the inherent problem, though, is SAP has such a large product matrix that it's hard to say, does this feature work here versus another one? So if you're using the legacy ECC as a source, there's really nothing you can do in terms of getting around it. You have to have some sort of data warehouse because SAP Analytics Cloud works best with a proper data warehouse. But if you happen to have an S/4 system, you can connect your dashboarding tool directly to S/4. And I was going to say on my first project in late 2017-2018, the integration between the front-end Analytics Cloud and all the back-end system weren't fully fleshed out or developed at that time. But if you were to fast forward to today, you're almost looking at feature parity for all the different systems. Before, it used to be that we have to import the data into the tenant, into the cloud tenant first, to have everything in terms of all the functionality, all the utility of the tool.   [00:03:46.820] - Hau Ngo But now a lot of that feature set is rolled out to BW, to the HANA data warehouse, of course, data warehouse, cloud, and now even S/4. So there are differences now, but they're getting much less and smaller between the different systems.   [00:04:04.770] - Mustansir Saifuddin That's good to know, because especially you see, a lot of customers have a mixed bag of systems and depending on whatever source system they are using, it seems like the tool itself is capable of consuming that data, right. In a way that is, from a user standpoint, it doesn't really matter what is the source, it's just the visuals. And the tool itself can mask that from them, right?   [00:04:34.680] - Hau Ngo Yes, absolutely. And then I think in certain cases, I think my current client now we're exploring even a use case, a dual use case where some reports come from their BW system that we're initiating, and then a different set of reports come from S/4. But the UI, the interface is still SAC, so to the user is transparent, but depending on the use case, it could come from a data warehouse or their transactional system.   [00:05:03.690] - Mustansir Saifuddin Right. And I think that kind of brings up this point. Right? The lines are getting blurry when it comes to the data itself. Right. It is real time information versus data stored in a warehouse and being consumed based on whatever frequency is getting updated, right?   [00:05:22.310] - Hau Ngo Yep, absolutely.   [00:05:24.810] - Mustansir Saifuddin So, talking about tips, right? Can you share some ideas or tips that when it comes to using different visuals in SAC, are there any best practices or any ideas that you like to share?   [00:05:43.410] - Hau Ngo Oh, sure. So the cloud itself, the tool itself, Analytics Cloud, has a number of different chart visualizations and they're categorized primarily by function. For example, you have a group of bar charts for comparisons. If you want to see trends, there are a set of line graphs, and then there's pie graphs and tree maps for distribution. So you have a good number of chart types to choose from, depending on what you wish to communicate with. That being said, the three that I've seen the most on my last ten projects has been bar, number one, numeric, the large numbers, the aggregation as number two, and tables as number three. And what I found early on, when I try to experiment with all the different chart types, it tends to confuse people if they're not statisticians. Right. You can't just throw a scatter plot and assume people know what that means. So what I find is most people tend to stick to those three bar numeric and table as the three most common chart types. If you stick with that and start from there, you should be in good shape.   [00:06:57.150] - Mustansir Saifuddin That's a good tip. I mean, keep it simple. It seems like the more simple you keep, the better usability you get out of that, right?   [00:07:05.940] - Hau Ngo Absolutely. And a lot of these folks, they do generate their existing dashboard from Excel. And if you were to look and use the existing dashboard from the managerial report deck, they almost typically use those three chart types.   [00:07:23.270] - Mustansir Saifuddin I think one of the things that I'm looking at from a prerequisite point of view, talking about, what are some of the prerequisites required for a client. When they're using SAC as a self service tool? Because it's almost like a parallel, right. Things that are done currently in Excel, especially when you're doing some kind of manager or reporting that you want to customize in Excel and you want to take those skills into SAC. So what are some of the things that they should have in place from a prerequisite standpoint if they want to use this as a self service tool?   [00:08:04.000] - Hau Ngo Oh, sure. So I think that may be a two part answer. From a personnel or staffing perspective, I would suggest that our audience consider finding someone, whether they be internal or external, who is excited about dashboards and what this tool can do for the company. And I'm not talking about the technical features of the tool, but the way the tool itself can benefit someone's day to day chores or workload. And now imagine if you were a business analyst and you can tell your team that they don't have to open their laptop and log into SAP to see the numbers. And that would be cool, because if they got an email each morning with a full color PDF with all information they needed, that simplifies and cuts out that friction. Right. And for the field staff, if they could open up a phone or a small tablet and get the customer sales history before going to a sales meeting, that would be easier than what they're using now. And from a technical perspective, companies with an S/4 landscape should consider SAC as a reporting tool of choice. I'm working on a proof of concept where I'm embedding the SAC dashboards into the S/4 environment for a customer, and maybe we can talk about that on a future episode.   [00:09:28.670] - Hau Ngo But if you have a BW or Hana data warehouse and you're deciding between SAC or another cloud based tool, then I would strongly suggest you consider SAC. And that's because you get tighter integration with live data connections and you don't really have to worry about the security.   [00:09:48.550] - Mustansir Saifuddin Yeah, for sure. And I think that kind of is a good segue into my next question, which is all about leveraging what you already have in place, right. So when you are dealing with an S/4 or data warehouse cloud source system, what are some of the quick wins when you want to leverage the security models the roles definition that you have in your source system, do you have some examples that you can share with us?   [00:10:17.800] - Hau Ngo Oh, sure. So I would say the quickest wins you can do when you're going in and highlighting the features of a new tool is to eliminate the unnecessary things that you would have to do, which is building data model, model data validation, and setting up security. If you could connect your dashboard to existing data warehouse or S/4 system, you're halfway there. And the beauty of SAC in terms of integration is there is no security. You inherit the security profiles of your source system, whether it's BW Hana or S/4. And the front end tool with single sign on respects all of the privileges you set up versus another tool where you have to kind of maintain or even duplicate that setting. With SAC, you don't have to worry about it, single sign on takes care of all of that.   [00:11:13.790] - Mustansir Saifuddin I think that can go a long way, right? I mean, I'm thinking from the ease of use as well as the ease of deployment. It seems like if I can leverage my source systems for my security and my roles that are already in place, it can make much easier for folks to kind of leverage that information. That mapping that is already in place.   [00:11:40.450] - Hau Ngo Yeah, I would say it's an easier sell. And also long term, there's only one point of failure. There's no dual maintenance that someone has to maintain in different systems. So I think it's an easier path as well. In terms of the actual tool itself, you can have some limitation in terms of whether user is a content viewer where they can consume the information or if they're a power user. Right. But in terms of the actual line by line, row by row authorization, let that be taken care of centrally in either your data warehouse or your S/4 system.   [00:12:18.830] - Mustansir Saifuddin Okay, that makes sense. Now, what are the opportunities? It seems like that's a good feature to have. Right. And that comes out of the box from SAC if you want to do any additional security in SAC because I know there are some planning functionalities as well as just pure reporting and dashboarding capabilities. Are there features available in SAC that allow you to further customize your securities or the role?   [00:12:49.410] - Hau Ngo Yeah, sure. So for some customers, they have data sets that they upload, whether they're doing manual compiling of information or planning or something like that. You can still set up security inside analytics cloud from a team perspective. So you can define team roles where certain team members can see the financial information but other team members cannot. So there are some security functionality, but it's more around who can see what sensitive information that's maybe not in your systems, but in these confidential flat files.   [00:13:29.990] - Mustansir Saifuddin That's good to know because I think your point earlier, right, when you talked about source systems, and especially when you're dealing with multiple source systems, it seems like it may be a better idea to have SAC drive some of the security of the role definitions. Right, because you have a mixed bag of information coming in to your models.   [00:13:48.530] - Hau Ngo Yes, absolutely.   [00:13:50.930] - Mustansir Saifuddin Good to know that. It's interesting when you look at this overall, we talk about everybody's looking at cloud analytics as the way to go and it's just so much simpler and the technology has advanced so much across the board. Right. It seems like the most logical choice for customers to move forward in the direction. Would you say so?   [00:14:17.290] - Hau Ngo I would say so. I think what you're going to see moving forward is maybe not SAP specific, but more cloud based technology. Just because from a deployment perspective, the vendor only has to maintain one instance or one master copy of the tool. It's just so much easier to use than what I think we've had a struggle with in the past, where even though a lot of customers are doing similar things, we have to have our own installation on custom repository. Here I've noticed at least on the early days, SAP was rolling out features every two weeks and it was really hard to keep up. But now the products seem to have matured a lot more. So I think at this point we're going to focus more on usability versus features.   [00:15:07.910] - Mustansir Saifuddin For sure. I know we covered a lot of different things in the session. Would you like to share any one key takeaway that our listeners can take it with them?   [00:15:19.750] - Hau Ngo Oh, sure. So we talk about SAC quite often and some of the different considerations for implementing this tool. But overall there are other tools and if you consider implementation and tool selection in a broader perspective, I've been lucky to be in a few early conversations during the tool selection phase and most customers seem to struggle with either SAC or another cloud based tool such as Power BI or Tableau and deciding which one to use. And most of the time the conversation seems to be centered around features versus cost between these tools. And what I've seen in terms of outcome from a couple of these meetings with different companies is that the SAP centric customer tends to stay under the SAP umbrella due to the tighter integration and security benefits that we spoke about. And other customers with non SAP systems in the mix choose the other tools because they have similar features at a lower cost. But that cost saving is usually offset by higher development times. So that's just the cost of doing business when you're integrating different systems. But that's just something to think about.   [00:16:42.830] - Mustansir Saifuddin Yeah, and that's a good tip, right. And a good takeaway, especially when you have all these choices available to you. One thing that folks tend to leave behind is the fact that sometimes costs can be a factor in most cases, it is a factor. But what is the cost? Are you looking at the cost at this point in time, or are you looking at a future cost perspective? Especially when you're doing integration? Right. And this is all about maintaining your systems in the long run, right. So you have to keep that in mind.   [00:17:18.090] - Hau Ngo Yes, absolutely. I think a lot of customers, they're very intelligent, but sometimes they get too focused on a certain thing and they get tunnel vision. But like you said, if you were to step back and look at the total cost of ownership of not only the tool, but maintenance, and will this be accepted? And which tool can actually be embraced by the business community? So those factors are taken into account. I would leave, I guess, the audience with one thing. People now are more impatient than they were in the past, because at the speed of things and their expectations have changed. Right. So app development, dashboard development, it's much faster. And if your tool can meet that demand from your customer base, then you're golden. The fact that you can whip up a dashboard in an hour or two is great, but if you're taking three months to get a lower cost tool up and running, that might be a deal breaker for your community, for sure.   [00:18:20.070] - Mustansir Saifuddin And that's a great takeaway. I mean, it's something to keep in mind, especially when you're doing any cloud based analytics, right? What is the time to delivery that matters? Thank you so much, how. This has been a great session. Thanks for some of the insights into what things we should consider, especially when you're going with SAP analytics cloud as a tool of choice. So really appreciate your time and we'll look forward to meeting with you in the future.   [00:18:47.940] - Hau Ngo Yes, absolutely. Have a good one, Mustansir.   [00:18:50.930] - Mustansir Saifuddin You too.   [00:18:55.770] - Mustansir Saifuddin Thanks for listening to Tech-Driven Business, brought to you by Innovative Solution Partners. Hau has shared some key pointers for you to think about when choosing SAC. His main takeaway? Look at the bigger picture when choosing a tool. Be careful when being driven by cost. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation by visiting Isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.

Wednesday Sep 07, 2022

In this next episode of Tech-Driven Business, Mustansir Saifuddin continues the conversation with Hau Ngo of Summerlin Analytics to discuss how to approach data modeling and visualization when using SAP Analytics Cloud (SAC). Hau first joined us for a 6-part series in 2021 to talk about SAC and what it means to enterprises as they move to the cloud. Hau and Mustansir share real-life tips on how to approach this depending on your team and company. Listen in for quick takeaways that you can put in to place today. As the tech industry moves to simpler tools, data modeling plays an even more important role. Hau is an SAP Analytics Architect and an early adopter of SAP Analytics Cloud. In 2017, he helped a technology company in California consolidate global sales reporting across 7 different ERP systems. This effort culminated in one executive dashboard that displayed real-time information, eliminating weeks of manual coordination and data wrangling. Subsequently, Hau has presented his work at conferences such as SAPPHIRE 2019 in Orlando Florida, and has gone onward to help additional customers streamline their reporting processes and visualize the key company metrics. His experience with SAP Analytics Cloud extends to customers with various systems such as SAP Data Warehouse Cloud, BW/4HANA, and S/4HANA.  Connect with Us: LinkedIn: Hau Ngo Mustansir Saifuddin Innovative Solution Partners  Twitter: @Mmsaifuddin YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   Episode Transcript [00:00:06.010] - Mustansir Saifuddin Welcome to Tech-Driven Business. Brought to you by Innovative Solution Partners. In this episode, I welcome back Hau Ngo of Summerlin Analytics listen in as he talks about the importance of balancing data modeling with visualization to get the most out of your investment in SAP analytics Cloud or SAC. [00:00:34.110] - Mustansir Saifuddin Hello Hau, how are you? [00:00:37.110] - Hau Ngo I'm doing well, Mustansir, how are you? [00:00:39.570] - Mustansir Saifuddin Hey, doing great, man. Welcome to Tech-Driven Business. Again, today we will talk about the balancing act they call it, especially when you talk about SAC. And you have so many different variables in terms of the data modeling part, the data visualization, and what is the right balance. That's what I want to talk about today. [00:01:06.070] - Hau Ngo Oh, sure, yeah. I think it gets a little bit tricky, I think now with this newer tool because you can do so much with it. Before we used to just do everything in either ABAP or BW and you just have like a table dump either in Excel or an LB grid. But now with SAC, you can still do a little bit of data modeling. You can define calculations so the lines are blurred, like where do you do which things? Right? And I think in terms of what I would suggest for a good data model in this new paradigm, I would try to have all your work done on the back end, meaning you would have all your calculations done in either S/4 or BW or Data Warehouse Cloud, and treat SAC as a read-only layer. So SAC as a reporting layer, just read what you've written and leave that. Now of course there's some give and take, some things are easier in SAC, but I think for the most part, make sure everything is done on the source system and you should be off to a good start. [00:02:13.930] - Mustansir Saifuddin Interesting. So what seems like a good data model in your example that you just shared? It's almost like do more of the heavy lifting on the back end, which can be either S/4 or Data Warehouse Cloud or any other system for that matter, as long as you can connect to SAC and then use SAC as almost like your reporting layer. But create your stories, but avoid more detailed calculations and modeling in SAC.   [00:02:47.170] - Hau Ngo Yeah, exactly. Because if you start reading into the technical documentation, SAC explains the technology in this way. Each widget, each table that you see in your dashboard is a separate report or query call to the back end. So if you're doing a lot of heavy lifting on the front end, inside Analytics Cloud, it has to do that X times per widget. So we have nine or twelve there's nine or twelve separate calls. It's going to fetch a lot of data and then you're going to do a lot of calculations in your browser and that may slow it down.   [00:03:27.770] - Mustansir Saifuddin Yeah, that's for sure. I mean, the number of widgets does impact your so, I mean, when we talk about widgets, especially, I've seen some dashboards or stories that can go from a single pager to multiple pages. Is there a good definition of exactly how many visuals you can have or you should have just to make your dashboards more robust? [00:03:56.110] - Hau Ngo Oh, sure, yeah. If you're looking for like a really responsive, quick rendering type dashboard, something that the user can open and see the data right away. The approach I've been taking is if you can break up your stories into multiple pages, I think SAP still recommends having only six at most charts per page, which is kind of sparse, to be honest. I typically run between nine and twelve per page, but if you can render all of your stuff on different pages, you only have to load those widgets per navigation. So typically I build for directors and executives, and they almost always want to see an overview page, which is like one chart type from one page, another chart type for another page, and they want to see specific things on the overview, and as they go from page to page, they go into a more specific look or drill down into their data. But if you can break it up, it renders much faster. If you can stick with the simpler chart types, like bar charts, numeric, pie, anything that's not a table, you should be in good shape.   [00:05:13.230] - Mustansir Saifuddin That makes sense. Yeah, especially those cards are very useful. As you mentioned, when you're working with the C-levels, the information can be readily available. It's easy to grasp what's being presented on the initial overview page.   [00:05:27.230] - Hau Ngo Exactly.   [00:05:28.290] - Mustansir Saifuddin So that kind of leads me to my next question. This is good because we always get this inquiry, especially when you're dealing with a source, especially when you have multiple source systems feeding into your SAC model. Right. What constitutes like, a model, especially when you're dealing with data warehouse and S/4, what would you prefer?Usually you see from your experience, do you see a blend of those data sources or do you see a single data source and then working with that on the SAC side?   [00:06:16.520] - Hau Ngo Yeah, I would say typically when we first start off on a project, I see a blend and then it moves into a centralized data warehouse. And I say that because with SAC, you can get things up and running pretty quickly. So we can leverage this trick called in browser blending where you can say, I have data coming from multiple things. I want to them all mashed together on a dashboard. And if I were to select something like company code, that selection applies to all of the chart types regardless of the source of data. So to get those types of dashboards up and running quickly, to make sure that the information you're presenting is clear, understandable is what the user is looking for. That is a great starting point, but almost always you run into the data integration issue and that's almost always better done in a data warehouse because the tools are made for that.   [00:07:13.310] - Mustansir Saifuddin Yeah, that makes sense. Well, especially I'm just thinking of a scenario where you have a need to quickly bring something up, especially when you're dealing with executives and they want information on their fingertips, and you try to kind of get information directly from the source system versus a model based on a data warehouse, things can get a little tricky.   [00:07:42.260] - Hau Ngo Yes. And with this tool, also, you get around that trick or that tricky scenario by showing these executives what you can do with the tool before committing three to six months into a lengthy implementation. They want to see what's possible upfront, and if they want to invest that fund towards that effort.   [00:08:04.380] - Mustansir Saifuddin It's a great advice, actually. I like that. So what I'm hearing is you can do a quick show and tell and then see what the capabilities are and how the tool can interact with a transactional system versus a data warehouse. And then once things are the way it's supposed to be from a business standpoint, you can create a model behind the scenes. Right. To make it more the reusability seems to go up, correct? Is that my understanding?   [00:08:37.110] - Hau Ngo Yeah, exactly. I consider this more like a high fidelity mock up where you're using production data. They're familiar with the figures, and you can get them most of the way there with business content. So regardless of which system that you have, the tools are there for you to kind of take apart and blend together in your browser with this tool.   [00:09:00.410] - Mustansir Saifuddin For sure. Yeah. So let me ask you this. Based on your experience, I know you talked about you've done multiple SAC implementations in your experience. Anything that stuck out for you, like, any example that you would like to share with our listeners?   [00:09:14.760] - Hau Ngo Yeah. So this is going to be, I would say, a tricky one to answer because I work with large teams where the project budget is $400 million, and then I work with small teams where it's just me plus the client, because newer companies are being formed now through divestiture where there's a larger firm, they spin off a smaller subdivision or subsidiary. And those folks, they know what they want. They're used to having information in a certain way, but they no longer have the staff or the team to deliver that. So I would say if you don't have a data warehouse, don't worry, you can use this tool. You can use other cloud based dashboard tool with your source data, whether it's ECC or S/4. But as you get more mature and as you consider purchasing a data warehouse, maybe you don't even need a large team for that either, because now SAP has another tool called Data Warehouse Cloud, which is a cloud based data warehousing tool that doesn't require the large upfront cost and the team to implement.   [00:10:25.400] - Mustansir Saifuddin That interesting. Yeah. I think the way the industry is going depending on the size of the implementation and the requirements. Right. You can take multiple approaches and there's no right or wrong answer. It depends on what your requirements are at that point in time, right?   [00:10:54.870] - Hau Ngo Yes, exactly. And it seems like now the tools are advancing that in a way that we can do more with less and we can get things done quicker than before. So it's pretty exciting.   [00:11:08.430] - Mustansir Saifuddin Yeah, for sure, I think. And that's the key piece, right? I mean, you can spin up a dashboard in a matter of days and hours versus weeks and months. That used to be the case in the past.   [00:11:19.540] - Hau Ngo Yeah, exactly.   [00:11:23.050] - Mustansir Saifuddin That's an interesting segue into this idea of like, folks talk about getting things quickly and that means that a lot of times a lot of projects want to bypass our data warehouse. Right. What are your thoughts on that? What would be your advice to them or the right way to do it?   [00:11:47.290] - Hau Ngo Oh, sure. So if they're, I would say relatively small and nimble in terms of company size, you can create beautiful dashboards with S/4 data. You don't need a data warehouse if you happen to run S/4, so that there's a lot of business content there that you can leverage and extend. But if you are looking at a data warehouse, like I mentioned, data warehouse cloud is an option. But a lot of these cloud based tools, they seem to work better and they seem to work across different data sources as well. I would say just go ahead and give it a try. The takeaway here isn't so much the tool, it's trying to get the user buy in from your business. So I would focus more on that before really focusing on how do we do it, making sure if this is something that the users want to get done.   [00:12:44.470] - Mustansir Saifuddin Yeah, for sure. I think that is probably one of the key takeaways. I always ask this question because my listeners like to hear, especially when you're talking about these kind of insights. What is the one takeaway when you talk about the balancing act between data modeling and data visualization when it comes to SAC?   [00:13:07.510] - Hau Ngo Oh, sure. I think in the past we used to have, I would call them clunkier tools like business objects or Lumira, where you need a dedicated resource or team of resources to maintain the server to do the development. What I've seen now is the transition to simpler tools, both the front end and the back end, the SAC visualization tool and the data warehousing tool that's coming out because they're so much easier to use. I would focus less on the reporting visualization need in SAC because you can get a dashboard out and running in an hour if everything is really clearly defined, so the effort is much less. Right. But the classic problem exists if you happen to be doing a lot of data transformation or merging data from different places, the data modeling efforts still remains, even though you can get it done quicker. The effort between visualization reporting versus back end modeling, the ratio is now leaning more on the back end. So before, if it's three to six months on the back end, maybe a month on the front end. Now it's more like a day at most on the front end, depending on how many revisions you want to go to.   [00:14:38.760] - Hau Ngo But the data validation is still there on the back end. So I would focus more on hiring developers for the back end who knows what they're doing and are familiar with the process. More so on the back end than the front end.   [00:14:52.450] - Mustansir Saifuddin Yeah. So I think it kind of leads up to that question about how do you architect your data? Right. In your source system? And what is that? The possibility of pulling the information in a way that it makes sense from whatever the business KPI that you're working on, correct?   [00:15:09.250] - Hau Ngo Yes, absolutely. And you'll find, as you know, the time sync is validation and there's really nothing that you can do to get around that, depending on how many sources of data you're combining, transforming, and the complexity that is still there.   [00:15:25.570] - Mustansir Saifuddin Yeah, for sure. And that's probably not going to go away until you have all these different definitions of the key indicators and how you measure it. And every company, every organization has their own way of doing it. So as long as that is well defined and well published, the front end work seems like it's become a lot more easier and better in terms of the visualization with Sac.   [00:15:56.170] - Hau Ngo Yeah, absolutely.   [00:15:58.450] - Mustansir Saifuddin Great. Hey, it's been great talking to you. How really good insights in today's session. Look forward to our next coming up soon. Thank you so much.   [00:16:09.200] - Hau Ngo Yeah, thank you, Mr. Have a good one.   [00:16:11.760] - Mustansir Saifuddin You too.   [00:16:15.530] - Mustansir Saifuddin Thanks for listening to Tech-Driven Business brought to you by Innovative Solution Partners. Hau shared some key pointers as you think about where to focus your efforts in SAC. His main takeaway, as we transition to simpler tools focus on data modeling. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation consultation by visiting Isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.  

Monday Jul 25, 2022

In this next episode of Tech-Driven Business, Mustansir Saifuddin brings back Hau Ngo of Summerlin Analytics to share an update on SAP Analytics Cloud (SAC). Hau first joined us for a 6-part series in 2021 to talk about SAC and what it means to enterprises as they move to the cloud. He revisits us to talk about what it takes for an architect to be successful in implementing SAC. Listen is for quick takeaways that you can put in to place today. With the wealth of learning tools available, SAC is no longer out of reach for clients or consultants.  Hau is an SAP Analytics Architect and an early adopter of SAP Analytics Cloud. In 2017, he helped a technology company in California consolidate global sales reporting across 7 different ERP systems. This effort culminated in one executive dashboard that displayed real-time information, eliminating weeks of manual coordination and data wrangling. Subsequently, Hau has presented his work at conferences such as SAPPHIRE 2019 in Orlando Florida, and has gone onward to help additional customers streamline their reporting processes and visualize the key company metrics. His experience with SAP Analytics Cloud extends to customers with various systems such as SAP Data Warehouse Cloud, BW/4HANA, and S/4HANA.  Connect with Us: LinkedIn: Hau Ngo Mustansir Saifuddin Innovative Solution Partners  Twitter: @Mmsaifuddin YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   Episode Transcript Mustansir Saifuddin (00:03) Welcome to Tech-Driven Business. Brought to you by Innovative Solution Partners. In this episode, I welcome back Hau Ngo of Summerlin Analytics listen in as he talks about his real-life experience of SAP Analytics Cloud, specifically, how SAP is making it easier for clients, lessons he has learned since he last joined me in 2021, and more importantly, what you need to do to be successful with an SAC implementation.   Mustansir Saifuddin (00:51) Yeah, it's been a while. It has been a year and a half when we last spoke about SAC and the role of SAC in the business intelligence SAP world.   Hau Ngo (01:04) Yeah, I think so. And I think at that time, SAC was still relatively new and unknown. So it's good to catch up after some time in the field and see what other people are experiencing with the tool.   Mustansir Saifuddin (01:16) Yeah, for sure. I think it's come a long way since we last spoke, and for today's session, I would like to talk about some of the key ingredients, especially when you're making your reporting and analytics implementation right. And what makes them successful, especially when you're dealing with SAC.   Hau Ngo (01:35) Yeah, sounds good. And I would say now that things are starting to pick back up, projects are starting to come back online, a lot of people are starting to look at reporting as the key driver in the businesses again. And it's good to see that SAC is up there with the other cloud tools.   Mustansir Saifuddin (01:51) For sure. Yeah, I think we've seen a lot of good changes coming through the tool and how it has kind of developed over the past couple of years. So okay. With that, let me get into the first topic I would like to get your insights into. So when we talk about SAC, what is the role of the analytics architect, especially when it comes to implementing SAC?   Hau Ngo (02:20) Sure, I think that's a great initial question, and I think a lot of clients overlook communication as a quality that should be high up the list. Of course, technical competency and familiarity of the tool is a given. The resource should know where 80% of the time, where to find the option to change a setting or to enable a feature. And I think I've done about ten SAC projects so far, and I still ask my clients for direction when they come and ask for something I'm not clear about. But getting back to the communication part, I think this skill ranks nearly as high as the technical know-how, because building a dashboard is very collaborative and it's an effort that involves directors of finance or supply chain who then need to present the information to someone in the executive office. So folks at these level are exceptionally pressed for time and having a resource who communicates well, whether it's during the working sessions or through email makes this process go smoother, quicker, and more enjoyable.   Mustansir Saifuddin (03:30) Interesting. So it seems like one of the key skills required for having a successful implementation, especially when you're playing the architect role, is communication.   Hau Ngo (03:40) Yes, absolutely. Only because this tool is end-user friendly. And there's a lot of things now, I guess, two or three years later, written about this tool and the functionality, and SAP has done a wonderful job of marketing that. Where it gets into a little bit of trouble, I think, for a lot of end users and clients is they're not sure what the tool can do because it can do a lot. But what they have in their specific environment, whether it's Analytics Cloud to S/4 directly, or if they're connecting to the new Data Warehouse Cloud, or if they're connecting to HANA Data Warehouse, or BW Warehouse, or BW/4HANA. So depending on how it's used and what it's connected to, it can do certain things in some instances, but not another. And having an architect who maybe have a little bit of experience in all four different areas could definitely help walk them through that process.   Mustansir Saifuddin (04:40) That's interesting. Yeah, I think that makes sense, especially when you're dealing with the level of users who are more business focused and having that communication skill, as well as a way to understand what their requirements are. Right, I think that makes sense.   Hau Ngo (05:00) Yeah, absolutely.   Mustansir Saifuddin (05:01) So I think this kind of leads me into my next question. We always talk about this, right? Why does the business knowledge and collaboration with business users is so important, especially when you go about implementing SAC? Hau Ngo (05:15) Yeah. If you recall a couple of years ago, and this is maybe speaking to our age, but most of the reporting tools were excel-based, and now dashboards have been recognized as the more efficient way of presenting large amounts of data in a quicker way. And the challenge with this new approach is that each business department looks at different metrics and how they interpret the data differently. Right. So, for example, someone in finance looks at the profit and loss or maybe the sales margin numbers and may want key data points in a tabular review and in a specific order or grouping. Someone else in order fulfillment or customer service may like the larger numeric tiles that show daily sales numbers or bar tiles that show open orders for specific items that may not ship in time. So to add to that, each dashboard will be tailored to the preference of that particular executive. Maybe she's older and you have to use larger fonts and maybe consider something that's print ready. Or you may have a director who's younger and wants to see numbers on the go. So you may have to consider a mobile, responsive layout.   Hau Ngo (06:29) So all of this is to say that design dashboards and the data models that go with it is often highly customized and require a lot of interaction. More so than your typical back-end developer maybe used to.   Mustansir Saifuddin (06:42) I think that is important to know, especially when you talk about a demographics. Right. Who is my end client, especially the age. The way of presenting the information based on their key roles seems like one of the key reasons that you need to understand the business. And what I'm hearing from you. Collaboration is the key piece, right?   Hau Ngo (07:10) Yes, absolutely. Because you don't want to go back and forth with a higher-level executive. Too many times they are pressed for time. So however, you can shave off those cycles of back and forth, whether you're familiar with the process area or maybe you can anticipate the request. That definitely goes a long way.   Mustansir Saifuddin (07:31) For sure. So I think that let me ask you a personal question. What do you consider one of your biggest accomplishments when it comes to doing these implementations? Any personal favorites?   Hau Ngo (07:49) Yeah, I would have to say that learning new skills and learning them quickly has been exciting and rewarding. I would say during the first 15 years working with SAP, the technology has been relatively slow. Back then you had BW and ABAP for data warehousing and reporting. But just in the last five years, that has been a blur with Hana calculation views, S4 CDS views, analytical cloud and the application design, of course. And now with Data Warehouse Cloud and each one of these required learning and retooling and it's a very exciting time.   Mustansir Saifuddin (08:30) Absolutely. I think that kind of sums it up. Right. I mean, things have changed quite a bit in the past few years, especially when it comes to SAC and certain tools that are very business focus and the whole layout and the communication that it brings to the end users, I think is much different than what it was in the past.   Hau Ngo (08:55) Yeah, you can almost say we went from waterfall to agile very quickly.   Mustansir Saifuddin (09:02) That's a good comparison. Things were done a certain way for a very long time, especially when it comes to analytics. Now we are able to take that to the next level, right?   Hau Ngo (09:13) Yes, absolutely.   Mustansir Saifuddin (09:14) Especially with SAC some of the key ingredients that it contains. As a tool, from predictive to planning to the stories, everything is just giving you the information very quickly in a very precise way.   Hau Ngo (09:34) Yeah, and SAP has done a good job with that. They actually package a lot of the information where it's almost out of the box and implementation is very minimal to get your data into a presentable format quickly.   Mustansir Saifuddin (09:47) Absolutely. We always talk about these implementations and that question comes up. Right. Analytics implementations are challenging at times and especially when you're dealing with different levels of business users. What are some of the key indicators for a successful implementation? How would you quantify that?   Hau Ngo (10:12) If you ask a lot of people, I'm sure you'll get different answers. But I think the clarity of the project goals and limitations of the tools are important. Sometimes I see projects fail because the client expects more than what the people or the tool can deliver. In a limited time, the scope keeps expanding. But where I've often seen successes are when projects that have a team that constantly work together to define and agree to what's possible. Those projects tend to be more successful more often than not.   Mustansir Saifuddin (10:48) So I think it kind of sums it up with that statement you had just made. Right. As long as you have a very succinct definition of the requirements and then a resource or an expert who understands architecture can do things, these things in a very precise manner right. In a very timely delivery also.   Hau Ngo (11:13) To be honest, most of my projects, the one I enjoy the most, I actually learn from the client. So it's an oxymoron. You're hiring someone who's an expert in this field but that person is also learning both the functional business side and the technical side, sometimes, from the client. So it has to be collaborative for some of these things to work out well.   Mustansir Saifuddin (11:35) Yeah, I think that's a key statement you just made. Especially a lot of these kind of projects tend to go different ways depending on how requirements are defined and what kind of challenges you have when you come on board in these projects. Technical challenges, business challenges, et cetera. And when I look at it as a whole, it seems like the learning is on both sides, especially when you are interacting with the level of users in these kinds of cases is definitely different than working with an analyst, right?   Hau Ngo (12:21) Yes, absolutely.   Mustansir Saifuddin (12:24) Okay, great. So I know we kind of come to our time for at least this particular session. I would like to ask you this based on what we have covered so far, what is one of the key takeaways that you would want to leave the listeners with today?   Hau Ngo (12:42) I would say most of the new cloud-based tools that we see today, like analytics cloud, they're relatively easy to use, but still I see a lot of hesitation when it comes to adapting or even trying out these new technologies. So my advice is to just give it a try, even if it's just an evaluation, and learn what it can do and just as important, what it cannot do. There's a lot of tutorials, online video and written, so the barrier to entry isn't as high now as it's been in the past. You'll have to put in the work, of course, but you'll be surprised how quickly you can become an expert with these new tools. And after that, it's about sharing what you've learned and helping your team succeed.   Mustansir Saifuddin (13:28) That's a great advice. That's a great advice. I like it. Especially when you mentioned that there are so many tools available for anyone who is interested and has the desire to take that to the next level. So the information is available as long as you're willing to go out and explore.   Hau Ngo (13:48) Yes.   Mustansir Saifuddin (13:49) Great. Well, thank you so much, Hau. So it's been a pleasure talking with you and look forward to our next session.   Hau Ngo (13:56) Yeah, likewise, Mustansir, to dive into some deep conversation technical conversations next time. So talk to you then.   Mustansir Saifuddin (14:05) Thank you so much.   Hau Ngo (14:07) Yes, thank you.   Mustansir Saifuddin (14:11) Thanks for listening to Tech-Driven Business, brought to you by Innovative Solution Partners, Hau gave a great overview of SAP Analytics Cloud in today's environment. His main takeaway: take advantage of the many resources available to learn. The barrier to entry for SAC is low, so take advantage of it to learn all that you can. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation by visiting Isolationpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.

Monday Jun 06, 2022

In this next episode of Tech-Driven Business, Mustansir Saifuddin talks with Dawn Solomon of Haworth. With Dawn's decades of industry and tech experience, she shares what she has learned while implementing and using SAP Business Planning and Consolidation (BPC). Dawn not only shares what has worked well, but also what to watch out for when implementing BPC; especially if you look to combine it with Microsoft Power BI. Her key takeaway: as a life-long learner, Dawn has been able to stay abreast of changing technology and support Haworth through it's refinement and use of SAP. Dawn Solomon is a Sr. SAP Business Process Analyst supporting HR and Finance in the Center of Excellence (COE) at Haworth Inc.  During Dawn’s career she’s done everything from Accounts Payable to being a Subject Matter Expert to joining the COE. Involved with multiple upgrades of the finance systems at Haworth, she has also supported Haworth globally including North America, Asia Pacific, and European sectors. This global support was for not only finance applications but some parts of Human Resources as Haworth moves to Success Factors. Dawn is an active volunteer with America SAP User Group (ASUG) where she shares her insights and expertise with others.Continue the conversation on: LinkedIn: Dawn Solomon Mustansir Saifuddin Innovative Solution Partners  Twitter: @Mmsaifuddin @DawnSolomon5 YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.   

Monday May 09, 2022

Mustansir Saifuddin continues the conversation with David C. Williams of AT&T whose background includes leading large-scale IT projects which result in large returns for the organization. In this episode, David dives into no-code and how companies are leveraging no-code to make a significant impact. Low-code and no-code have the power to transform business processes in an exponential way with a lower financial investment. It also opens the door for those that may not have the traditional tech background.  David also shares his latest venture, the "Business Model" book that he has authored to highlight how we can combine our past experience with our business passion to create our own business model. In other words, how his mom made "$1 out of $0.15. David's takeaway : be bold and courageous to take your idea boldly to where it should go. No-code and low-code is a great way to get it moving forward. During David's career with AT&T, he has created deep-link HTML marketing initiatives that garner 90 million monthly impressions, led Competitive Intelligence which helped shape AT&T's Mobile First strategy, has been responsible for supporting several Fortune500 companies encompassing $120M in revenue, and authored two patents for Reprogrammable RFID and bridging satellite and LTE technology. In his current role, David is responsible for hyper-automation & emerging technology to transform Customer/Employee Experience and Cost Structure for his organization. He leads the largest Robotics Process Automation program worldwide. His innovations are driving change across the company as his team has developed 600+ Bots automating 70M contacts, realizing $400M in operating income at over 3,000% ROI. Additionally, he also invented & sponsored a decision engine driving $200M credit reduction annually. David is the 2021 Legacy Award recipient at Black Engineer of the Year STEM Global Conference, 2x Dream in Black winner, AT&T Champion of Diversity Award winner, a proud mentor of multiple Employee Groups, & Diversity Ambassador. David’s humble beginnings in the poorest corner of Dallas, TX, continual giving back through Solar Robot Workshops to the community, and rise through a corporate giant is encapsulated in his soon to be released book entitled, Business Model.  Continue the conversation on: LinkedIn: David C. Williams Mustansir Saifuddin Innovative Solution Partners    Twitter: @dcwglobal @Mmsaifuddin   YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.

Monday Apr 11, 2022

Mustansir Saifuddin continues the conversation with David C. Williams of AT&T who leads one of the largest Robotic Process Automation initiatives for AT&T. Now covering 70 million transactions daily with a 3000% ROI, David understands what it takes for a RPA initiative to be successful. He'll discuss the importance of giving a bot time to mature and the power of sustainability. David's belief in "culture trumps strategy" has allowed for him to build a team that always keeps improving their bots. He discusses how Corporate America can be a lot, but we are humans first. He follows his mom's mantra of making "$1 out of $0.15" to drive ingenuity and that "1" by "1" makes "11".  More importantly, David shares how the end game of creating hybrid solutions allows for collaboration tools and RPA to leverage the best from each solution.  During David's career with AT&T, he has created deep-link HTML marketing initiatives that garner 90 million monthly impressions, led Competitive Intelligence which helped shape AT&T's Mobile First strategy, has been responsible for supporting several Fortune500 companies encompassing $120M in revenue, and authored two patents for Reprogrammable RFID and bridging satellite and LTE technology. In his current role, David is responsible for hyper-automation & emerging technology to transform Customer/Employee Experience and Cost Structure for his organization. He leads the largest Robotics Process Automation program worldwide. His innovations are driving change across the company as his team has developed 600+ Bots automating 70M contacts, realizing $400M in operating income at over 3,000% ROI. Additionally, he also invented & sponsored a decision engine driving $200M credit reduction annually. David is the 2021 Legacy Award recipient at Black Engineer of the Year STEM Global Conference, 2x Dream in Black winner, AT&T Champion of Diversity Award winner, a proud mentor of multiple Employee Groups, & Diversity Ambassador. David’s humble beginnings in the poorest corner of Dallas, TX, continual giving back through Solar Robot Workshops to the community, and rise through a corporate giant is encapsulated in his soon to bereleased book entitled, Business Model.  Continue the conversation on: LinkedIn: David C. Williams Mustansir Saifuddin Innovative Solution Partners  Twitter: @dcwglobal @Mmsaifuddin   YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation. 

Tuesday Mar 22, 2022

In this next series of episodes, I have the pleasure of speaking with David C. Williams, Assistant Vice President-Automation at AT&T. David understands how to use the power of IT to manage change quickly and effectively in times of uncertainty. He and his team were responsible for putting the technology in place to move AT&T's 40,000 reps from being in the office to being remote with the pandemic forced lockdown. Listen in to how David worked cross functionally to make this massive change in 5 weeks rather than 6 months.  During David's career with AT&T, he has created deep-link HTML marketing initiatives that garner 90 million monthly impressions, led Competitive Intelligence which helped shape AT&T's Mobile First strategy, has been responsible for supporting several Fortune500 companies encompassing $120M in revenue, and authored two patents for Reprogrammable RFID and bridging satellite and LTE technology. In his current role, David is responsible for hyper-automation & emerging technology to transform Customer/Employee Experience and Cost Structure for his organization. He leads the largest Robotics Process Automation program worldwide. His innovations are driving change across the company as his team has developed 600+ Bots automating 70M contacts, realizing $400M in operating income at over 3,000% ROI. Additionally, he also invented & sponsored a decision engine driving $200M credit reduction annually. David is the 2021 Legacy Award recipient at Black Engineer of the Year STEM Global Conference, 2x Dream in Black winner, AT&T Champion of Diversity Award winner, a proud mentor of multiple Employee Groups, & Diversity Ambassador. David’s humble beginnings in the poorest corner of Dallas, TX, continual giving back through Solar Robot Workshops to the community, and rise through a corporate giant is encapsulated in his soon to bereleased book entitled, Business Model.  Continue the conversation on: LinkedIn: David C. Williams Mustansir Saifuddin Innovative Solution Partners  Twitter: @Mmsaifuddin YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation. 

Tuesday Feb 15, 2022

In this next episode, I have the pleasure of speaking with Mark Stifter who's career focus has been on compliance. As tech professionals we often are at the receiving end of compliance requirements. But what does that really mean? Mark explains the four pillars of compliance, why it's important, and the successes and failures he's seen with companies as they implement their compliance strategies. Mark, president of Herndonwood Associates, is a global governance, risk and compliance entrepreneur with a cybersecurity background. He has extensive experience successfully managing teams and supporting organizations with the creation and implementation of IT compliance strategies and programs required due to growth, acquisition, divestiture, disruption and new or reinterpreted regulations. His background includes developing solutions that are sustainable, measurable and leverage automation using both proprietary and custom tools.  Continue the conversation on: LinkedIn: Mark Stifter, Mustansir Saifuddin, Innovative Solution Partners,  Twitter: @Mmsaifuddin YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation. 

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Mustansir Saifuddin excels in bridging the gap between business and IT so that clients can create and implement solutions that produce results for years to come. That's why, in 1999 I co-founded Innovative Solution Partners, an IT consulting firm specializing in providing our clients with data insights for informed decision making. As a passionate and visionary leader, I know how to lead teams cross-functionally as well as around the world to drive results.

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