Hello, I'm Merritte Stidston a Technical Solution Specialist in DPG sales. Today's presentation was put together by myself and Mr. David Rhodes. Today's conversation or discussion is around building business value in modern data platforms. Our agenda is going to be transformation is inevitable. Trying to not move to the Cloud is not possible. There are too many advantages and benefits that you can gain from moving to the Cloud. The biggest, most important one is you want to be able to do it on your customer's terms and makes sure that at the end of the day that this move to the Cloud is successful, whether it's going to be your on-premises or private cloud or hybrid cloud, public cloud or multi-cloud strategy spending multiple cloud service providers. The next one is that you want to understand what the business implications and benefits that apply to your move to the Cloud and understand that these benefits when applied appropriately will benefit in all Cloud deployment methodologies. The next one is something that David and I call the seven Ps. Now, these aren't industry standard Ps, but the letter P is the first one in each one that you will be able to have this conversation with your customers, be able to find out what the motivations are and what the biggest drivers are for them to move to a Cloud strategy. It's very essential that you understand what these are. Now, don't memorize them. The biggest, most important thing is that it's going to enable your conversation with the customer and be able to pinpoint whether the key things that matter to them in the business decision of moving to the Cloud. Next is one size does not fit all. It's really important to understand that what one customer might want, another customer may not. One may be totally a private Cloud deployment. The other one may be a full move over time to a full public cloud deployment methodology. You want to understand between those two extremes, what is there for your customers so that you'll be able to recommend the appropriate things that they need to do to be successful. The next one is start small. It's very important that if you're not a company or you're working with a company that hasn't been doing a lot of things in cloud, you want to take him find something that has high value that can be accomplished in a very small timeframe. A small time frame would be 3-6 months, that way will give your customers time to learn very important Cloud skills and processes that they can apply to the next project and the next project. Remember, start small and build out from there. Let's cover some of these topics in more depth. There's first of all confusion about what a modern data platform is, and where it should be. Everyone says in a cloud, the truth is which cloud? A couple piece of advice that I have is that for modern native platforms, that you want to take in leverage, native, architectures, and processes. These are necessary for both the platform design and operations. It's really critical that you do these things because those are essential. That's how customers actually leveraged the real value of what's in a cloud, and why it's just as good applying them to an on-premises cloud to get your most value there, whether it's going to be in a public cloud with the CSP. Very important. You want to take and leverage modern cloud architectures that are native in these processes are really important. Second of all, you want to take and understand that cloud doesn't only mean a CSP, it can mean both your on-premises hybrid or public cloud. So remember that when you're in a conversation with the Cloud, don't instantly think you're going to move to a CSP, or they're going to only stay on premises and have a private cloud. You really want to understand what's going on. Chances are that customer is talking about a hybrid cloud scenario, and that will give them the right business value and security methodologies or profiles that they're looking for. It's really important to understand what that is. Then the other one I mentioned before, Start small. It's really important. You want to get your best value from your data problem. Those business insights. Pick something, looking at for example, how do you make sure you have the right product mix for a customer? Or that your price optimization is right based on your customers previous buying habits so that you can adjust that. That's something you can do very quickly. It provides high value, but it's something that can be done in a 3-6 month timeframe. You want to work with these cloud projects in at least get them to understand how you can do it. Again, that would apply to some of these new or intermediate users of clouds that are just moving to it. If they're an experienced cloud user, then you want to skip this. Next of all, when you're looking at this, it's absolutely essential that you understand what the company's business strategies are. This isn't just simply business strategy computer Cloud. It's really what they're trying to do. What are the pillars inside that strategy that are coming from the top of the enterprise, the CEO and the board, all the way down and being driven into the center part. Because if you don't understand what the business drivers are and how that applies to their corporate strategy, trying to apply a data strategy to that, is going to be a disaster. You're going to be delivering the wrong insights that don't actually help meet those business strategy objectives that you have. There's this really good article that I've included and that's what this diagram comes from. It's from McKinsey. It really does help you to understand. Here's how you move through this process to be able to deliver those insights. This is something we all intuitively feel comfortable with because it's something we deal with every day. How do we handle the data ingest? How do we handle the data refinement? How are we turning these data into insight? So on and so forth. These are what we feel comfortable with. But if you didn't understand what the business drivers are, you'll be collecting the wrong data and helping them process it in a way that doesn't deliver the insights that they need. I highly recommend to everybody that you take a little time, click on the link in this presentation , and go read that. It's a bit of a long read, but you can be done with it in about an hour. Very informative, and it's one of the best articles I've read in a long time. Now, the 7P. What the heck did David and I mean by this? Well, we want to talk, what are the internal policies? What are the politics that are going on in the enterprise? What procedural issues that are happening there? What processes exist today? Are there people issues, is there a fight between two different business units and their heads, or is it that they want to take and reduce the number of people that they have? They believe Cloud is going to allow them to work with fewer people inside the enterprise, so it's monetary. Then the last one, is it the pricing? Is it something between CapEx and OpEx? Again, our point here is not for you to go down and recite all these things. You want to have an idea, listen for them. As you're talking to the customer, you want to have a very clear understanding of what the drivers are. You really only need two, maybe three of these, to really understand the nuts and bolts of what's going on in this. That's going to help you, again be able to define what do they need to do to be able to move to the Cloud and have the right balance of infrastructure underneath that gives the customer the solution that they're looking for. That's very important. Next one, as I talked about, where are some of the important characteristics of a modern data platform? Here are a few of them and we're going to go into some of them. Now, depending on what you look up, if you look this up on the Internet, you'll find that there might be five, someone says there's 10 or 12 or what number. It doesn't really matter. What is key is that you have an understanding of what a number of them are. Most important, at the center of all this, is understanding that your security level is a minimum metric. Security is one of those things that has to be looked at right up front and ensure that it's front-and-center in everything that you're going to be doing with that customer, and make sure that you understand the customer's needs around security in that enterprise. What does that mean? Well, let's drill down into some of them. Well, first of all, the modern data platform exists in multiple forms. As I've mentioned before, it can be a private Cloud, hybrid Cloud, public Cloud. It's understanding which one of these and what the implications are of each one of them. So you want to go through that and make sure that you have the appropriate architecture in place for that customer. Another one is, what skills are going to be needed for the team that's going to be managing this? I've talked to many customers that have had the misconception that once they move to the Cloud, they don't need all those IT people anymore. They're going to be able to eliminate them with the hardware that can't be further from the truth. You still need your network architecture, storage architecture, platform architecture architects, and on top of that, they have to be trained and being able to leverage the services that are available in any public Cloud provider environment. It's essential that when you look at the stat and talk to the customers and make sure that they understand that they have to take a look at what the people that they've got are being trained to the level that they need. Some of them will make it, some of them won't, and in this case, then they need to look at back filling those positions and putting the right technical people in place to leverage that. Another one is making sure they've got testing automation. Testing automation covers multiple areas. It could be application testing. It can be an infrastructure change. You want to be able to constantly run automation against your running environments and see if something's happening. That way in the event of a failure, you'll know that your platform will fail either to another availability zone or would fail to a region, or it could fail to any number of systems that are on-premises. So making sure that they have this testing automation in place is important. Underlying that is automation overall. Being able to manage Cloud native environments, whether it's your private Cloud, public Cloud or any mix of those, you want to automate as many of the services as possible inside of that, environments can scale automatically. They can scale down or scale up, you can add storage and you're constantly monitoring that environment. Now it leverage the past of what your team has to offer and also will focus on what provides the most business value to that enterprise. Lastly, you want to look at an event streaming platform. What does this mean that you've got source systems, we call them producers, so that would be your SAP system and Oracle database can be NetFlow data, could be Firewall data. You want to take an ingest that data, move it through the system and make it easily consumable by those business units that can derive business value from it. These are very important things that you need to do inside of that platform, making sure that you have this event streaming platform, again, is a modern data architecture and that's the use case we're going to be talking about today. What happens is in real life, customers will take and install data warehouse. They install agents on your source systems and send data to the data warehouse where it can then be processed, put into tables, organized, categorized so that you can derive business value from it. Over time what happens is you get what's on the right-hand side. At scale, it's a mess. It's what we call a spaghetti architecture. You got everything connected to everything else and you've got data moving back and forth, and not all of those systems use the same agents, so then you've got multiple agents that are extracting data off of the source system, slowing it down as it processes and pulls that data to send it over to another system, doing the same thing. These spaghetti architectures are very common in their prices. How does that start? Actually starts organically, very simple. What happens is you start off with a data warehouse, you connect it, you've installed your agents all across the environment, and then someone comes along and says, you know what? We want to be able to look at data in a different way. We want to process that in a Cassandra data store, so what do they do? They go through and install a whole bunch of agents on that, and then eventually you get that spaghetti architecture. What you want to do is moved to the after and say, we don't want to do that anymore. We want to be able to connect a system one time to an event streaming application. The other side of that, we have our consumers, and those consumers can grab that data very easily. This is a wire what strategy, so once I connect those source systems and start pulling that data to my streaming platform, I now can make it available to any number of groups inside of them. One of the key things I would say is don't take and look at the data swamp strategy. Take it when you move that data and put it in defined domains so that that data belongs to that domain and it makes it easier for you to maintain and manage it or your customers to maintain and manage that data over long periods of time. That is a key strategy, so how do we do this in real life? Our example, as I said, streaming platform. What you see on the screen right now is that ingest, store, process, and deliver methodology. Here we're looking at an enterprise that's moving from the left to the right, being able to process data from the source systems all the way over to the far right where that data is being consumed as a report or a dashboard or maybe feeding another system downstream. When we look at this data is going to fall across that. What if I want a business intelligence platform? Funny, you should ask. Here's an example of looking at just information moving for a business intelligence platform. All of your sources will be sending data to some subset of your data management or data storage claim, then over to your data processing plane, and then ultimately to the far right. Knowing how this data is going to move is going to help you to understand what conversations to have with your customers about moving, storing, and processing data, either in a private Cloud, [inaudible] public Cloud or multi-cloud strategy. It's important to understand this, but when you can break it down into each one of its constituent parts, you can then match it to the appropriate Cloud strategy that you're looking for that delivers the business value that your customer requirements. These are the important things to need to look at, and with that, that's the end of our presentation. I hope you liked it. It's been a pleasure for us and please feel free to contact myself or David Rhodes. Again, we're both in DPG sales and we'd be happy to help you in any version that you need. Thank you very much and have a good afternoon.
