In this episode of the Futurum Tech Webcast, principal analyst Shelly Kramer is joined by Allan Pym, Chief Operating Officer at APOS, for a conversation on the challenges making the most of business data presents for organizations, and how APOS Live Data Gateway is helping solve those challenges — and in real time.
We all know that data is crucial for today’s organizations. From sales and marketing to manufacturing and maintenance, smart organizations need data to make decisions in real time. However, with so much data being gathered in so many different places, it can often feel impossible, overwhelming, or both to wrangle it intelligently. So, what can organizations do to make the most of their data? Are there other technology solutions that can help? Why does real-time matter when it comes to accessing and utilizing data? That’s exactly what Allan and I covered today, and if you’re wrestling with data challenges, it’s a conversation you’ll very much enjoy. We covered the following:
We know that data is important, that’s not a secret. In fact, some 94 percent of organizations report needing access to multiple data sources to support their decision-making — but not every organization knows what to do with their data.
Allan shared some of the challenges he and the team at APOS are seeing as organizations wrestle with data connectivity. That’s not at all difficult to understand, as research shows that on average companies are drawing from more than 400 different data sources. To compound that massive amount of data coming from myriad sources, one-third of companies report experiencing trouble simply connecting those sources together, let alone pulling accurate or meaningful insights from them.
We discussed live connectivity: what it is and why it’s so important for organizations today.
Allan walked us through the APOS Live Data Gateway, its purpose and the key benefits organizations can experience using its three layers of functionality (Data Connection, Data Preparation, and Data Consumption) and three types of data views that can be utilized within the Data Preparation Layer.
We explored APOS Live Data Gateway’s Data Connection layer, where the solution makes the connection to data, and we talked about some of the data sources that APOS Live Data Gateway provides connectivity with.
We explored both the Data Preparation layer and the Data Consumption layer, including how APOS Live Data Gateway works with SAP Solutions and how live connectivity versus import connectivity works with SAP Analytics Cloud.
Allan shared that APOS Live Gateway works with analytics solutions beyond just SAP Analytics Cloud, including live connectivity from Power BI to SAP Analytics Cloud, as well as the expanded consumption options that include Odata, ODBC, and JDBC, in the unified semantic layer.
Lastly, Allan shared some stories from customers who are currently using APOS Live Data Gateway which, as always, was one of my favorite parts of the conversation.
If you’re thinking about getting arms around your data and know that live, real-time data is what you need, this is a conversation you should make time for.
You can watch the video here:
Or stream the audio here:
You can find more information about APOS Live Data Gateway on SAP Store, and I’m sure that if you’d like to connect with Allan on LinkedIn, he’d be happy to not only connect, but answer any questions that you have about the solution.
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Transcript:
Shelly Kramer: Hello and welcome to the Futurum Tech Webcast. I’m Shelly Kramer, Principal Analyst here at Futurum Research. And today I’m joined by Allan Pym, the Chief Operating Officer of APOS for a conversation about how to make the most of your data and in real-time. And this, I know for certain, is a challenge that many organizations are facing today. So we all know that data is crucial, from sales and marketing to manufacturing and maintenance and smart organizations, everyone needs data in order to make decisions in real-time. However, so of the challenges is that we have so much data that’s being gathered oftentimes in so many different places, harnessing it, and being able to use it is a huge challenge for organizations. So there are technology solutions that can help, and that’s what Allan and I are going to be talking about today. So Allan, welcome to the show. This is one of my favorite topics, and I’m so glad to have you.
Allan Pym: Thanks, Shelly. I’m pleased to be here. And yeah, looking forward to it.
Shelly Kramer: Two data geeks talking about data. It doesn’t get any better than that.
Allan Pym: Let’s go with that.
Shelly Kramer: All right. So before we dive into our conversation, I’m always interested in just learning a little bit more about my guests. So if you’ll indulge me, just tell us a little bit, if you would, about your career path and how you got from where you started to where you are today. I’d love a little bit of that backstory.
Allan Pym: Yeah, thanks. And interesting, I came from a non-technical background in my education and early career or in finance and those areas, but essentially my path led me to get involved with a technology organization. We were doing some development work and working on some projects that were building enhancement solutions and custom solutions for a few different organizations, and sometimes projects go awry. We needed some assistance to help bring those projects back on track. And I reached out to an organization I’d heard of called APOS, and they saved the day on a number of fronts.
And fast forwarding the story, I joined the company 25 years ago, and we shifted gears in a few different ways and progressing through our work that’s focused on business intelligence and analytics. So as the organization has grown, my role has changed and adopted. So yeah, here I am. I head up the team in terms of our sales and marketing and business administration and all things in that realm.
Shelly Kramer: And continuing to save the day for customers, I would guess?
Allan Pym: We are doing some pretty neat things.
Shelly Kramer: That’s really awesome. So as I said when I kicked off this show, we all know that data’s important. That’s no secret. Every organization has data. Not every organization knows quite what to do with the data. We see lots of challenges today that organizations are dealing with when it comes to data connectivity. Share with us a little bit, if you would, some of the challenges that you are seeing in the market.
Allan Pym: So the data volume is no question, that’s a given. Where we tend to fit in with organizations is by helping them with the connectivity aspect of that. And it’s one thing to have great data, but if you can’t make use or extract it and leverage it with the right technical mechanisms to do that, then it’s a great resource, but you can’t use it. So what we have focused on is specifically how to have connections into the data and leverage data in that way.
Shelly Kramer: So when you think about this a little bit when you think about data connectivity, one of the things that we look at is… I came across a research report on business intelligence that I thought was interesting. And on average, companies are drawing from more than 400 different data sources. And 94% of organizations report needing access to multiple data sources to support decision-making. And in the same report, a full one-third of companies reported that they had trouble connecting these sources together. Thus the importance of a data connectivity solution.
Allan Pym: Exactly. And building up assets in so many different places, that’s the key.
Shelly Kramer: Yeah, absolutely. So tell us a little bit, I’d like to talk more about connectivity. So will you explain what live connectivity is and why it’s so important for organizations today?
Allan Pym: Yeah. So essentially with a live connection versus another type of connection, often I think of it as an import connection, different analytics tools. And that’s where our focus has been as an organization is coming from VI and Intel and analytics and basically the ability to connect to data where it sits. So as data volumes have grown so much, the daunting task of moving data more than is required becomes a pretty big point of efficiency and timely information. So wherever movement of data and replication of data can be avoided, this is a pretty key point of streamlining the process.
So with a live data connection, this allows you to leverage data from its current location without having to move it from one repository to another repository, meaning that you have to apply a new security model at that next layer, you’ve got issues around data being current depending on the timeliness of the updates. Whereas with a live connection, you can make that analytics connection directly to the data source where it sits and leverage all of those existing investments into security and storage and all the rest directly from that.
Shelly Kramer: I have to admit, the minute you started talking about moving data from one source to the other, the first thing that popped into my head was security. And that is such a big deal for companies today. And not having to move that data from one place to the other is, I think tremendous. So super interesting there. So let’s talk now about the APOS Live Data Gateway. So what’s the primary purpose of that and what are the key benefits? I mean, you touched on it a little bit just now, but are there other benefits that we can talk about that organizations can experience using this Live Data Gateway?
Allan Pym: Yeah, the name’s a bit of a giveaway, isn’t it? So yeah, our focus really is on the solution Live Data Gateway is to enable that live connectivity. So rather than have you replicate data, go directly to the source, directly to the database, and use a live connection. So Live Data Gateway is doing that, and really the key benefits that security, that’s a critical one, the currency of data, making sure that it’s not outdated is a key one.
So within the solution, there are a few different layers of functionality, and I’d love to describe a bit more about that and how that fits. But each one really holds its own purpose and intent. So essentially the three layers are one is the data connection layer, the second is the data preparation layer, and the third is a data consumption layer. So those three layers encapsulate everything that the solution does, and each one has its own piece in delivering the value that the Live Data Gateway has as a whole.
Shelly Kramer: So when I was looking at the solution, I saw some specifics like the semantic layer view, which I thought was tremendously important because it allows non-technical users, someone like me to be able to select tables and fields. And then it joins in APOS Live Data Gateway web user interface. So I felt like that was an important feature to mention. And then I also noted the Freehand SQL views. So that allows technical users to create views based on queries in the gateway. And then the OLAP view, which creates a subset of existing measures and dimensions from a cube data source in the gateway. All of those things, the part of it that applies to non-technical users is attractive but the functionality that applies to technical users, it’s equally attractive, I think.
Allan Pym: Yeah. It certainly is the case. So thinking again of those three layers. The data connection layer, that’s really where the Live Data Gateway server makes a connection to the data source. There’s not anything particularly exciting about that, but you need a door to walk through to get to the data. So that protocol, that connection layer is exactly that. When we get to the preparation layer, we often refer to that as our semantic layer, which it is. And you mentioned the different kinds of views, and this is where views are created for the purpose of communicating data to the analytics tool in a way that makes sense.
And also so that the end report designer doesn’t need to know the complexities of the underlying data source, which is huge. So the different kinds of views that you mentioned, one is the semantic layer, which is a wizard-based user interface, web-based interface so that people can go in who don’t have to have technical SQL skills, they just need to be able to know generally what data they’re looking for. And that interface allows them to make those selections, create this view, and then they can use that themselves, they can share that with others. And it really simplifies the whole process.
The Freehand SQL view, that’s for more technical users who want to get in and get their hands dirty on SQL and be a little more targeted in the view that they’re creating, which works really well for those users. And then the old app view that you mentioned as well, this is really for putting a control layer on top of a big data cube so that you control how much data gets exposed. So it really becomes this business layer that simplifies the access for users. And self-service analytics is a very common term. We see that we play an effective role in that, but this notion of self-service modeling is something that we’ve been talking more about because the simplified approach to creating these views and then being able to share those views really brings down the requirements and the skill level that’s required to be able to create that modeling. So we’re quite proud of that.
Shelly Kramer: Yeah, absolutely and understandably so. Let’s talk about it, I know that APOS is an SAP Analytics partner. So tell me how Live Data Gateway works with SAP solutions?
Allan Pym: Frankly, that takes us to that consumption layer because what is the consumer of the data that we’re sourcing and then preparing and providing out for use? So we’re a long-time SAP partner. Our history with SAP goes back 25 years where we’ve been building enhancement solutions for the BI and analytics platform. Business objects have been a huge part of our world for that timeframe. Over the last seven or eight years though, SAP has been very active in promoting and bringing to market its SAP Analytics Cloud Solution, which is quite impressive and its traction market share is growing significantly.
So where we fit is that this was really the main crux of why we built Live Data Gateway to start was to provide live connectivity from SAP Analytics Cloud to non-SAP data sources. So SAP Analytics Cloud is a cloud-based application, a cloud-based platform for analytics, but it has these two different types of connection modes. One is an import connection where you move the data from its source location and put it into the analytics cloud data environment. And that’s effective and useful. But more and more organizations I have been looking for, “Well, that’s great, but how do I, my analytics with a cloud-based analytics platform without having to move my data from its location?” So that’s really the essence of a live connection and what Live Data Gateway is doing and fulfilling all of those benefits of Live Connection, but with SAP Analytics Cloud.
So that really is the main focus of how we work with these SAP Analytics Cloud or with the SAP environment and providing that. So yeah, we can source many, many different kinds of data. So we’re connecting from a wide range of legacy relational sources to old lab sources, to deep sources, to targeted applications. And a really big one over the last few years, no question has been the large cloud sources that really have taken off so much market share.
So the Google BigQuery is the Amazon rest shift, Azure, Snowflake, these environments are ones that we’re getting a lot of activity with these days to be able to use the analytics cloud environment from SAP and have a live connection to those data sources without having to move that data. And again, a data volume, that’s where it comes in because people just don’t want to move that after they have that investment. Yeah.
Shelly Kramer: Absolutely. So you touched on this briefly just a few minutes ago, and I know that you’re an analytics and SAP Analytics partner, but the Live Gateway solution works with analytics solutions beyond the SAP Analytics Cloud. So I think that’s important as well. Can you touch on that a little bit?
Allan Pym: Yeah. We have been doing more work that way, and something that’s been a key catalyst in this is the important collaboration that we’ve been doing with SAP. SAP has a cloud-based data warehouse solution called Data Warehouse Cloud. And that is a solution that again, is growing a lot in its traction and its use within the SAP community. So one of the challenges that have come up is enabling a live connection to Data Warehouse Cloud, but not from SAP Analytics Cloud, the analytics platform, because SAP does a great job of that, but other analytics solutions. How can they connect in live mode into Data Warehouse Cloud? And Power BI has been really at the top of that list of solutions for that.
So we’ve expanded our solution to be able to handle those scenarios specifically for Data Warehouse Cloud. That’s been the main focus we’ve had. So a live connection from Power BI to Data Warehouse Cloud. So that’s opened that up. And in doing that, we’ve been expanding the consumption protocols that are required to do that. So ODBC, OData, those kinds of mechanisms have allowed a much more generic approach to who can connect and consume data from the Live Data Gateway, including not just analytics tools, but there’s even potential for other data sources to be a consumer from Live Data Gateway as well. So it’s been a neat expansion.
Shelly Kramer: I think that what appeals to me is meeting customers where they are. You don’t have to do just this. There are choices and variety in the offering and all of that sort of thing. And I think that’s really important today. I think that when customers are trying to make a decision about the solutions they’re adding to their tech stacks, I think that’s a valuable one. When you can meet them where they are and when your solution serves them regardless of where they are. I think that’s incredibly valuable.
Allan Pym: Yeah, agreed. And it’s a big world and lots of technologies within these organizations. One really specific point of note on that is we talked about the semantic layer data preparation layer and the views that get created there. So what becomes unique about this is you can create those views, and then they can be consumed by multiple different consumers. So you have this sense of, again, the old term of a single source of truth but we’re talking specifically there about the semantic layer and how those semantic views can be shared across consumers.
Shelly Kramer: So sounds pretty awesome. Now, what I want to know is more about your customers. Who are your customers? What organizations are using Live Data Gateway? Let’s dive into that a little bit.
Allan Pym: So one of the interesting things about a solution like this, a connectivity solution, is that there’s nothing particularly industry oriented to this. There’s nothing particularly specific business use case about it. It’s very horizontal in nature, and I think it’s just the broader applicability of the solution that that’s one of the great things about it. So as we think about the size of organizations that we work with, we’ve worked with anything from large multinational corporations down to mid-size regional companies. We work with some of the major international pharmaceutical companies. We work with some banking organizations, from a very large European bank all the way to a regional bank in Ethiopia. We work in mining in Australia and France, and some customers there. Oil and gas, we have some customers there. US energy distribution company, healthcare, retail, manufacturing. Even one of the top-tier systems integrators uses our solution for one of their internal projects as well, which is quite interesting. We do have-
Shelly Kramer: Well, here’s the thing, everybody has data. Everybody needs to be able to effectively use that data. Data connectivity is an important part of the whole equation. I didn’t know the answer when I asked that question, but it makes perfect sense that there’s just not a specific industry or business size or whatever because everybody has data and data challenges, and figuring out a way to solve the connectivity issue is a universal challenge, I think.
Allan Pym: Yeah, for sure. It’s probably worth putting context to one more specific scenario. So one of our customers is called WR Grace, they’re in chemical manufacturing and materials manufacturing, a US-based organization, but they work globally. Their specific scenario is one where they had data in Google BigQuery that was central to their month-end financial close processes. They had some very manual data movement processes that were just generally creating inefficiencies. So by enabling a live connection from SAC to their Google BigQuery environment, what it did for them is a couple of things. One, it removed two days a month of manual effort, so that’s important. But even more than that, the real-time nature of being able to access that data meant that they’re being able to close their financial cycles each and every month significantly. So you don’t measure that quite the same way as you do manual days of effort removed, but that’s a critical benefit that’s come from them.
Shelly Kramer: It is. And a huge headache every month. Well, that’s awesome. Any other customer stories you want to share?
Allan Pym: There are lots of them, but those are the kinds of things that we see. But the nature of the data sources is broad in its range. And the requests that we come into contact with each and every week, the new opportunities that come our way, it’s really unique to see all the different places that people are leveraging their data, the different combinations of data. It’s fun to see all the different things that are happening out there with these great companies.
Shelly Kramer: Yeah, absolutely. Well, data’s the lifeblood of every organization, and that is so true. So being able to manage it, connectivity, all those things are just really a foundational part of business success in so many different ways. And I think that we’ve touched on a lot of those things. Well, Allan Pym from APOS, thank you so much for spending time with me today. I knew it was going to be a fascinating conversation you did not disappoint.
For our listening audience, I will include some links in our show notes to where you can find more information, and where you can find Allan if you have any questions. I know he’s more than happy to chat with you. And with that, we’re going to wrap our show. And thank you again, Allan, for spending time with me today. It’s been an awesome conversation.
Allan Pym: Yeah, that’s great. Thank you, Shelly. We appreciate it.
Shelly Kramer: Absolutely. All right. And with that, we’ll see you next time.
Author Information
Shelly Kramer is a Principal Analyst and Founding Partner at Futurum Research. A serial entrepreneur with a technology centric focus, she has worked alongside some of the world’s largest brands to embrace disruption and spur innovation, understand and address the realities of the connected customer, and help navigate the process of digital transformation. She brings 20 years' experience as a brand strategist to her work at Futurum, and has deep experience helping global companies with marketing challenges, GTM strategies, messaging development, and driving strategy and digital transformation for B2B brands across multiple verticals. Shelly's coverage areas include Collaboration/CX/SaaS, platforms, ESG, and Cybersecurity, as well as topics and trends related to the Future of Work, the transformation of the workplace and how people and technology are driving that transformation. A transplanted New Yorker, she has learned to love life in the Midwest, and has firsthand experience that some of the most innovative minds and most successful companies in the world also happen to live in “flyover country.”
