SMB Business Intelligence: The magic of Tableau and DataSelf

Well, good morning. Thank you for joining us today. I'm Ted Gazzello and I want to show you over the next 25 minutes or so how data self analytics solves a problem that so many small and medium sized businesses face as they select business intelligence tools. DataSelf has been helping small and medium sized businesses get value from their data for about the last 15 years. We saw the price versus power dilemma way back 15 years ago and we still see it now. The type and variety of solutions available has grown, but you still have the same problem. And it goes like this. You realize that you need better data tools than you've got. Perhaps you've got, you've been getting by on crystal reports or you've been trying to use Excel or Microsoft reporting services and you've heard all this talk about big data and you know you've got all this data piling up in your system and you suspect that maybe you're not quite, you know, doing the most you can with it. And maybe you even see signs that your competitors have sharpened their edge with data analysis and you know that there's more you could do with it if you just had the right tools. So you go looking for tools. Naturally you look at the tools that are supposed to be designed for your space small and medium sized business. Well, unfortunately, those tools seem to have made the assumption that, that I'm not sure you agree with. They seem to assume that you'll ask new questions so rarely that it's okay to depend on it, to do things like reconfigure your data or modify your reports or keep up with new questions and new markets and new products.

And.

Whatever changes you experience in, you know, what everybody knows is a rapidly changing business environment for everyone. And you just can't, you just can't do business like that. Success these days depends on the ability to respond quickly and intelligently. Yet many of these made for SMB solutions limit you with a lack of speed and a lack of flexibility. So you say, well, let's see what the big guys use. And I'm sure you know they've got the good stuff. It's fast, it's flexible and it's expensive and it's expert centric and it requires experts to configure and maintain. Now these providers assume that you've got the budget and the expertise to run those systems, to have people come in and tweak your configuration and set up new questions, add data sources, whatever you need. And just like anywhere else, even the big guys suffer from this. You put in a request and you wait and you wait and you wait. And meanwhile, the opportunities that you saw coming your way fly right by you. Until now, you were stuck. Well, we've solved that dilemma. So how do we do it? It's actually pretty simple. We select the best of the available tools, we put them together and make them work together. That's it. And that's how it works. We make it work. Today I want to show you just one of them. I'll go over the others a little bit later at the end. But today I want to talk about Tableau. Tableau is the most successful tool on the market today. Most successful, I should say, business analytics tool in the market today. It's used by companies from the biggest to the smallest. In fact, the 2015 edition of Gartner Magic Quadrant for business intelligence and analytics platforms says Tableau's intuitive visually based data discovery capabilities have transformed business users expectations about what they can discover in data and to share what they discover without extensive skills or training with a BI platform. It also goes on to praise Tableau's focus on helping people see and understand their data. Now, Tableau held its first customer conference in 2008. That's just a few years ago. I was out on the Seattle waterfront at the Edgewater Inn. I was there and it drew Fewer than 200 attendees all crammed into that little space. And even then you could feel that there was something big going on. I listened to a lot of stories from users. Obviously these are early adopters, but they turned out to be pretty representative of people who came later. And the stories pretty much went like this. We were trying to figure out some mess of data. Then someone remembered a funny little product they downloaded somewhere they heard of it or something. And we got it. We tried it and within a few hours we came up with something we had to tell the boss about. That is exactly what Tableau has set out to let people do, to let people see and understand their data visually and instantly without a lot of expertise. Now just last month they held their eighth conference. They had 10,000 attendees and you could still feel the electricity. At almost every other B conference, people talk about how their technology should work and how they're trying to make it work. And at Tableau, they talk about what they're doing with their data and what they've discovered with it and how they're.

Going to do it.

And you can still feel that same buzz as I felt in 2008. And it seems like every tool maker in the world is trying to catch Match Tableau these days. They have been trying now for the last few years at least. And after all that investment, all that talent, there's still no one who's come close to what tableau can do, or close to their ease of use or the power for the individual all the way up to the large corporation. Now, I'm going to tell you right now, I'm not going to do a demo. I've seen hundreds of demos of all kinds in business intelligence products and others over the last eight years, nine years, ten years, and not one of them looks hard to handle. They all look easy. They all make you go, wow, how could I live without that? Well, let's just talk about the premise for tableau. Let's look at what the Tableau founders started with way back at Stanford University by thinking about how people think about data. Usually it's with spreadsheets, cross tabs, reports, and so on. And they're fine, they're good as far as they go. But the numbers are hard to compare at a glance. Now, you could look at these and the rare person can look at this and tell you what's going on. I've known, I think, two people who could tell you in a second what's going on in this chart. And I don't mean just kind of looking at the total and, and telling you, well, it adds up to this, but really telling you what the trends are and what the weak points are and so forth. What Tableau lets you do is to think visually. After all, we recognize visual cues a lot faster than we do numerical ones. For example, look at this. You know what that is, and you know right away what that is. You say, let's get the heck away from this. You do that without logical thought. If you didn't, if we didn't have that kind of instant reaction, we might not even be around today. And here we are, apparently, and we're still going, and some of us are even running every day in the Nevada, Nevada desert. Now, here's something you probably won't. You know, you won't die from a data byte from this, but you'll work a lot slower than you'd like to look at these numbers. I bet you can't tell me how many nines are in this mass of numbers. You could give me a number if you spent long enough, but it'd be pretty tedious. Now, here's the same chart, just color coded, and we're a lot closer to the answer. And you can probably give me a good guess right now. What that is, there are about 10. Sorry, about 10 nines in here. Now here's a similar example in rows and columns. Tell me how many cafe mochas in the espresso category sold. Or, you know, you probably have to study a little bit longer to tell which region had the highest sales or which product categories are most successful. You'd have to study the numbers and. Well, you get my point. And here's the same data just shown visually. Now, which you know which region has the highest sales? Well, the central region, which products are losing money, looks like the red ones are. You know, that kind of intuitively red usually means losing. And also at a glance, you can kind of see that we're having a problem in the, in the West. This gives you an overview of the operations and other further visualizations help you answer more specific questions. Let's say I want to see outliers. I want to see whether sales track with profit.

In the cycle of visual analysis, you, you start with a task or goal and you go searching for data to answer your questions with whatever. You have the spreadsheets, desktop or whatever, to get pictures of your data and look for visual structure. From what you see, you derive further questions and possibilities and you go around again. You generate questions, you generate answers, and it goes around in this circle and you go deeper and deeper in a cascade of insights. You could start with just one question, like, how is sales doing? Total sales? You can see that in the left hand chart. Then you say, well, how does that vary by region? You can see that in the next chart or further, how would that vary by product type? And you can see that in the third one over. So many business users, though, still think of charts as kind of a nice to have a pretty thing. And they think of these charts. After all, the data analysis is done well here. Charts actually help in the analysis. They become part of your thinking, they facilitate your thinking. Now, no one's saying get rid of your spreadsheet. They still have a role. You can still do that. In fact, in tableau, you can see your raw data in a spreadsheet form if you want to. All they're saying is that visual analysis can quickly show you how to investigate and what to ignore, where to drill in, where you might find trends, where you might find the meat. In this iterative interrogation of data, you get to critical insights a lot faster than you would with spreadsheets. You have direct interaction with the data. As I said earlier, it's the charts. You don't just go back and forth between numbers and charts. You're right there with the charts. You adjust the charts and the data comes right with you. And it's stunning. Tableau has beautiful charts and it's persuasive. And Bess, perhaps you're thinking, yeah, fine, but I need to know some of the same things every month, every day, maybe every month. Whatever you say. Let's say I just need to know how sales is doing, or I need weekly reading of how my salespeople are doing, or I need to know cost of sales versus total sales or accounts payable, accounts receivable, general ledger, inventory, you name it. You can do that with the 5,000 reports, dashboards and KPIs that data self comes with. It deploys Data Self analytics, deploys the comprehensive starting package of reports. Now, about half of our clients find that this out of the box package is all they need, and the other half find that it's a pretty darn good starting place. The Data Self catalog has actually been crowd sourced over the last 15 years from reports that our customers have made on their own for their own needs. So there's sure to be a template in that library that will fit your needs, maybe with a few tweaks, but maybe perfectly just out of the box.

Now.

Tableau loves its data. It needs a pretty good data drive train to keep it fed and happy. And that's what we provide with Microsoft SQL Server. It's another important piece of the data train. Data drive train. If you have time, the bandwidth, and the people with the right skills, you can set up the connections yourself. But our experience shows that you'll be spending a lot of time on that.

And.

Especially as your needs become more sophisticated. You'll need some sort of data warehouse before you can pull data into. And this could take you months, could take you years and lots of money. So dataself helps you from reinventing the wheel and it accelerates your roi. Dataself has built a comprehensive set of tableau connectors for popular ERP and CRM systems. And just like for Tableau, the Gartner Magic Quadrant puts Microsoft SQL Server in the leaders quadrant. Plus Tableau's own ETL supplies serves as the intake processor. Etl, in case you don't know, stands for extract, transform and load. You extract the data from your ERP or ERP or CRM systems, Microsoft, whatever system you have, and it significantly simplifies the deployment maintenance of Microsoft SQL Server. In a nutshell, it makes it easy and fast to maintain a really rock solid data drive train for Tableau. Altogether, it's a complete and polished solution. It's a powerful data drive train. We've got a huge library of ready to use templates. And as I pointed as I went over before, there's the tableau, data analysis, unmatched data reporting, data discovery, the visual cycle of analysis. It's all fed by that rock solid, best of breed data drive train. So with that we have time for a few questions and I have a few ahead of time. Had a few ahead of time. One from Frank says, can I use Tableau separate from Data Self? Yes, you can use it. Such as if you bought it separately, yes you can. You'd have to connect the data yourself, but if you're comfortable doing that, then yes, you can. Krish says, does Data work Data Self work on an iPad? Yes, it works on an iPad and Android tablets. And Paul says, can I see the rows and columns in Tableau if I want to? Yes, yes you can. That's pretty easy. That's one click. So that's the questions I have for right now. I know you're going to have more questions, so just email them to Jay Girardi. It's up there on the screen. J G I R A R d I@dataself.com and we'll be happy to help you with whatever questions you have. So thank you very much. Thank you for sitting through the audio interruption and I hope, I hope I explained Data's health for you. Thank you. Bye.