Miguel Martinez is a Senior Product Marketing Manager for Microsoft Power BI. He oversees the digital strategy for the cloud business intelligence solution. His background includes formal training and practical experience in Marketing and Engineering.
Solver International: Microsoft’s Power BI is both an application, Power BI Desktop, and an online SaaS (Software as a Service). It also connects to a host of other common applications such as Word and Excel. How did Power BI and its internal group develop?
Miguel Martinez: I usually default to what Satya Nadella, our current CEO, keeps stating in interviews which is the motto of the company, “To empower everyone to achieve their maximum potential.” The way people work is changing. When Microsoft realized that companies throughout the world are producing more data, and that we needed tools to tap into the potential for making decisions based on that data, that is what drove us internally. Like the early years with SQL, as you build on top of that very basic data operation, how do you get insights and then make better decisions to make people more productive? I think that was the core of the beginning of the BI group that you see today.
And I would add, even though we have hundreds of offerings across the board for the consumer and for the enterprise, our groups need to come out with the best tool, where everything works together as a platform, integrates with each other, and actually accomplishes the maximum potential. Not only do you have hardcore data tools, like analysis services, reporting services, all very IT-centric in the beginning, as you move forward and more people need access to that data, you see groups working together to get the power of that data and the data analysis to everybody in an organization. It doesn’t matter what skillset they have or how technical they are.
SI: Power BI is not a thing, it’s a collection of things, right?
Martinez: I would say yes and no. Let me give you the reason why. Yes, it’s a collection. You have several components within that portfolio, but they all serve the same purpose, which is giving people access to data, so they can get insights and do a better job on a day-to-day basis. But if you double click on that—and this is the no part—while it’s a collection of things, you have an authoring tool, Power BI Desktop, that an analyst or whoever is tapping into that data can use to connect to the data, mash it up, clean it up, and make it ready for analysis; creative visualization is the channel that everybody in the organization can use to understand that data and make it as interactive and as friendly as possible. And then you have the Power BI service, which is the “cloud component,” where you share—and because it is cloud-based you have more processing power and more access for people to tap into that analysis.
The third piece is the consumption piece. Basically, everybody has a phone, so it’s not enough that you have a desktop application and a browser application. You need to make that analysis available anywhere people are consuming it. If you’re in a warehouse and all you have is a tablet to see the real-time level of inventory, we allow you to do it on that tablet. We don’t force you to go to a laptop or a desktop machine to consume that data. Those are the different moving parts that you see in Power BI.
Going back to the first part, it’s a collection of tools and I think that makes the case for not being just one thing, it is the back end. The back end includes all the technology, all the patents, all the knowledge that we have on how to analyze data and scale it to a level where it doesn’t matter if you’re a 100,000-person enterprise or a 10-person startup. The back end serves the purpose of providing a lot of power, a lot of analysis, that comes right out of the box with familiar tools. Because they have been around for so long, we try to bring all the things that people know about those tools into the consumption layer of Power BI.
SI: Back in the early days of micro-computing, back in the 1980s, the big problem was always integration–integrating hardware and software, making it easy to get information. Is that one of the things that BI is now doing, integrating all the collections of data that are scattered around the world?
Martinez: Definitely, yes. That is one of the pillars, not only of the Power BI offering, but every Microsoft offering today. If you look across all our suite of products, including Office, what you’re going to see is not only very tight integration between those different applications, but also very tight integration, or at least a communication funnel, between applications that do something else.
I think there are several examples of that within the Power BI world. Let me talk about the top three. Number one is connection to data. I would be a fool to assume that all the data for a company, or even for a particular analyst, lives in the same place and in the same format. So, a modern business intelligence tool, one that is not only relevant today but will be relevant in the future, is one that can connect to any source of data, any format of data. It could be structured or unstructured. It could live in an Excel or a CSV file. It could be in Salesforce or in Google Analytics. So that is key into a successful BI tool, and that’s what Power BI is trying to accomplish.
The second piece is focused not only on the data but also the execution. If you get a great insight out of something, or s-omebody gets an idea or an “A-ha moment!” out of an analysis, there is a big problem today. To put it very, very bluntly, if I’m on my laptop and I see that insight but then have I go to a different system or to a different machine, and execute something based on that, there is a gap. What you’ve seen from Microsoft, not only on our enterprise software or productivity software but even in the consumer side of things, is that we will bring your day-to-day job into the application itself. It doesn’t matter if it’s operational, if it’s financial, if it’s physical, or if it’s digital, we try to bring that into the application so it’s easy for you and you don’t lose time and you are more productive executing on the things that you learned from that BI-specific tool.
Some examples: under the umbrella of Power BI—the engineering organization that we call the Business Application Platform—you have things like Microsoft Flow, which is basically “if then, do that” for enterprises. Not only does it let you know if sales went over a certain level, you can automate the way to react if sales go over that level, so it can email certain people because they need to execute something in response. If you have other applications, like a CRM (customer relationship management) software, you can also automate the actual task to get it done immediately instead of having to check all the checkboxes to get that done.
Integration? Yes, in the ‘80s it was being studied and it was very important. Now it’s a requirement. Nobody will use any piece of enterprise software if it doesn’t integrate with the other things that they’re using.
SI: We hear a lot of discussion of Big Data. Are BI and Big Data compatible?
Martinez: I would say they’re definitely compatible, and I can speak from experience on that one. In one of my previous positions, in a previous life—I’ve always been in data-related roles—I was at an airline and looking at all the operational data that we captured. You can use that data to figure out fuel consumption or adjust shifts for crews that needed to fly planes. The amounts of data back then—I’m talking 10 or 12 years ago—was already overwhelming and I would think it would qualify as Big Data. There is no way to take advantage of that amount of data, that velocity, that volume, that real-time component, if you don’t have a layer that allows people who are making business and operational decisions to make sense out of it.
To bring it back to things that you see, not only in Power BI but in a lot of BI tools, how do you translate an insane amount of data into a visualization, into something that makes sense? I see two trends there. One is the data visualization piece, the sexy part that you see in all the BI tools, and the intelligence behind it. It doesn’t matter how many people you put into data analysis, you’re still going to need the AI (artificial intelligence) component to filter that data and to show you just the things that are relevant, to save you time from moving that amount of data to actual analysis.
So, BI and Big Data are 100 percent compatible. You need to deal with any type and any amount of data that you have available. But if you don’t allow the user to execute on that amount of data, it’s worthless. So those two things are very related, and that’s what you need, to make both of them play well together and get the most value out of them.
SI: We usually talk about data and intelligence and information all being similar, but different. You mentioned velocity. I’d like to go back to that. Is current micro-level BI capable of dealing with high-velocity data, that is, data that changes frequently? Can it keep currency of the data so that people are working with what is current rather than what is old data?
Martinez: Definitely. This is where Microsoft is heading, how to quickly get the data into the hands of people that need it. Are people accessing the one version of the truth at the right time? All those components are key, not only to Power BI but, again, to all our cloud and enterprise/data analytics solutions. For example, Power BI is a pioneer on the data visualization piece, to visualize data in real time. At our Data Insights Summit, which is where we bring data analysts to talk about Excel and Power BI, the real-time component, like the visualization piece, is front and center. It’s a big differentiator that we have. It doesn’t matter that you can visualize every sensor that you have on a factory floor if there’s no logic and intelligence behind that.
Because of the way data is coming into the hands of people that use it, real-time is a key. It doesn’t matter if your data are on the same platform or if you’re using different systems, data needs to come as close to real-time as possible.
SI: You talk about Big Data, about big companies that have a lot of sensors, as you point out, or are collecting data from many different sources—the Internet of Things. What about smaller companies, perhaps a two or three person information-based company? Do they get any value from business intelligence?
Martinez: Definitely. It doesn’t matter what size of company it is; it could be a company of one. First is the technical component, a way of speeding up access to a solution, so you can be up and running quickly. Basically, signing up for an account or downloading Power BI Desktop lowers the barriers of entry, the barriers to learning. It integrates familiar tools, the things that you’re already using. You’re going to see a lot of the Excel UI (user interface) and logic within Power BI without being in Excel, because there’s no need to have two Excels within the same company. Those two are complementary and they work better together. So, number one is how accessible and how easy to use it is.
Number two, I would say is the cost component, which is part of how hard it is to get the tools you need. Power BI is a leader in the market in that way. The scalability of the product on a per-user pricing basis is very, very accessible, and I would say it’s one of the most competitive that’s out there today.
And then number three is the data itself. I have a very good friend who owns a shop. They need to be available on every single online search that happens in the ZIP code where they offer their services. The providers of those search engines, like Bing or Google, make that data available for you, for free. It’s part of their service. If you have a tool that allows you to make better sense out of that data, which could be a pie chart and maybe a bar chart, to see what the key word that is most popular, that can be of great benefit.
If you can easily tap into that data, in a familiar environment like Excel, and you can tap into it in real time, that will give a company as small as an individual the same power as an organization of 100,000 people tapping into sensors in every factory, the benefit of making the right decisions based on data. Microsoft has always been a great enterprise destination but that doesn’t mean that small companies, even students or individuals having a business, cannot take advantage of it.
SI: Is business intelligence a long-term investment for Microsoft?
Martinez: Absolutely, yes. It has been for the last three years. If you look at the pace of innovation in Power BI and in Microsoft Research, which is the leading edge of the innovation that we have, you’re going to see that business intelligence is just one very specific piece of data analytics and empowering productivity for people to achieve more. It’s in the DNA of every single product we put out.
SI: Let’s go back to the beginning. Tell me how you see business intelligence and, obviously, Microsoft’s involvement in it? What does it mean to an MBA student or those in other programs looking forward to working in analytics?
Martinez: Great question. I think the number one advantage is the familiarity. They don’t need to learn new things to take advantage of what was, eight years ago when I took my MBA, an IT-focused or IT-bubble type of workload. Now you can tap into any data that you want. You are easily able to match it up and relate it to others without having a lot of technical knowledge, and get visual representation that is easy to understand and will take you to a finding or to an insight in a shorter time. This is what I see with MBAs, they’re usually going to have to interact with a lot of executives, with a lot of people where the patience they have for an analysis or for an insight is going to be very short.
If you look at the pain points of any data analyst or business analyst, when they are presenting an analysis or a model to someone, it’s usually, “How do you present it so it doesn’t take a long time for that audience to understand? How do you tell a story of the things that you’re finding in that data?”
All the tools in modern BI, which we call the third wave of BI, are making it easier for the person creating those analyses and those reports, and also for the consumer of those reports. You are shortening the gap between whoever is analyzing the data—the business analyst, the MBA student, the data scientist—and the person receiving it. And new ideas, new insights can come out because it’s not only the analyst doing the analysis, it’s everybody together consuming that data and coming out with an analysis.
So, to summarize, number one, not a lot of investment in learning new tools; two, more power to present things in a better way; and, three, coming up with actual better insights and solutions because you are empowering people, as an audience for your business knowledge, to make better decisions, more informed decisions.
SI: Have you had any experience with applications from other companies that work with Power BI? Has that presented a benefit or a problem for you?
Martinez: We have a lot of experience with that situation. You cannot expect any customer, any user of a particular piece of software, to be exclusively on your platform. It happens, but it’s very, very rare. That means when you build a tool like Power BI, or any other tool within Microsoft, you need to consider several things: not everybody’s using only your tools, so it must be open source and, especially if it’s a data analytics tool, you need to bring all the data in regardless of where it is generated. We accomplish a lot of that through working with other companies.
On the data connectivity side, Power BI connects natively to names like Salesforce, Google Analytics, NetSuite, QuickBooks—it’s a list that goes to the hundreds. When doing analysis for our own team, I connect to those company’s programs and that experience is very, very friendly.
On the consumption side, even though Microsoft is a company that has a lot of resources, you are going to have a lot of custom visualizations that people want to build for specific problems they’re trying to solve. For example, using Narrative Sciences to create a model and get a natural language representation, actual words that tell you what the data is telling you. With things like that, even though we can do them, we tap into partners to offer even better solutions.
As I mentioned before, I used to work for an airline. There’s a custom visualization that one of our community members built—it’s available on our website—that is an interactive, part-by-part visualization of an airplane engine. It only applies to companies that are in that industry, so you can count them on your fingers. The fact that you can easily accomplish something that specific, because of the open source component of a tool, is something you’re going to see, not only in Power BI, but in most of the Microsoft offerings.
And then, the last piece is how you get the data out. While we may want you to go into Power BI and look at that analysis, for some customers, for some companies, that is not the channel where they want it delivered. You need to play well by embedding Power BI analysis and Microsoft analysis in other tools, and that is something that we do, too. We have offerings like Power BI Embedded, where instead of going to our SaaS experience, you can take visualizations from a Power BI report or model and consume them in another application.
A good example of that is SharePoint. It is one of the CMSs that are most widely used, especially in the business environment. What if a company doesn’t want to use Power BI and send everybody to Power BI? They just want to embed that analysis in a SharePoint site. We allow people to do that. It’s a benefit we have, internally and externally, so it’s very easy to use Power BI with other tools.
SI: If you were going to sell the idea of business intelligence to an MBA student, one who is trying to decide what area of business to go into, what would you say?
Martinez: This is going to sound like a blunt approach, but if I’m really trying to convince them, I would say, “Take a look at any job posting––it doesn’t matter the level, it doesn’t matter the industry, the company––and how see they talk about their data analysis needs.”
We have a case study internally where you look at the history of the world or humanity, and we’re seeing something very similar with data when you compare it to books. When books were very new, few people could read because books were too expensive. It was very difficult and expensive to produce a book; you had to copy it by hand. Then you had the printing press and books explode. After a few hundred years, you couldn’t get a job if you didn’t read.
We’re seeing the same with data. Even if you’re not in a hardcore data analysis industry or department, the fact that business intelligence is the way data analytics is reflected in business decisions—it’s a key piece of knowledge—it must be part of your skillset, there’s no way you can escape it. So, either through fear that you have to learn it or because you enjoy data analysis, this is the right time in history to be exposed to analytics because you’re going to be very successful.