InetSoft BI Webinar: Importance of Data Mash-Up

This is a continuation of the transcipt of a Webinar hosted by InetSoft. The speaker is Mark Flaherty, CMO at InetSoft.

Mark Flaherty: Data mash-up is another concept that I think is really very important and I think that this is certainly a new trend: this ability to avoid what I call the “duct tape” of Business Intelligence. And unfortunately many of us are still using Excel for a lot of our Analytics. We have these PAT spreadsheets that do certain computations or mash-up information from one sheet to another and have all these wonderful macros in it. But the problem is that we are doing analytics in an area where we don’t have the power that we truly need and we have spend an awful lot of money on these wonderful analytic platforms but we are not integrating Excel with that or data from other sources for that matter.

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So data mash-up becomes very important and the focus becomes mashing up information: the ability to very seamlessly take an Excel spreadsheet or an Access database or other outside information and mash it up in your analytic app. And when you are doing that you are going to want to look for certain tools that allow you to kind of go beyond some of the things that Excel might have been able to do for you because I think that that’s where the value really begins and you want to be able to mash-up the data as it's needed. You want to be able to have a simple interface; data mash-up in your analytic environment shouldn’t be rocket science. You want to look for opportunities that are as simple as drag and drop, and dialogues and wizards that make it very simple.

And of course you want to look for some power; you want to be able to do calculations on the data once you brought it back in from your desktop into the analytic environment and you want to integrate that information in the reports and dashboards. And I think this is especially true when we are playing around with Big Data, because Big Data is something that discovery is behind and in order to do discovery you want to implement and bring in other data points that help you find the answers that you are looking for. And in the end, data mash-up can be a very important piece of technology for you when you are managing your Big Data and when you are managing your Analytics.

So I am going to move on to getting the value from the data. And I think one of the areas that is most important here is this opportunity to look at data in a real-time environment. As I mentioned before and upfront, the volume and velocity and the variation of data were all kind of pieces that make up Big Data. But I am going to talk about the velocity part here for just a minute. It's a perfect candidate for real-time business analytics. And in this case faster is better, quite often, and this is sort of where the Holy Grail of Business Intelligence and Analytics lies, is this ability to make faster decisions that are highly valuable in less amount of time.

There has been a lot of research done that the longer it takes to make a decision the less impact it might have on your enterprise around the business process that you are attempting to apply it to. And over time the value declines and the opportunities can be lost. Real-time analytics is ability to ingest Big Data and make decisions on it faster and smarter are certainly something that it would be a key benefit for getting awesome value from Big Data so use tools that support the reduction of data and analytic and decision latency. Don’t settle on tools that take too long or take too much IT interference to get the answers from.

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And that brings me to my last area for getting value from Big Data which is exploration: an “Aha!” moment. So I think that this is one of the best things that we get from BI is when one of the executive or business users has that “Aha!” moment because of the fact that we have empowered them with all the things that I have mentioned before. We have given them this new direction of mash-ups and the ability of wider data access. We have given them technology like In-Memory Data or the ability to tap into the granular data itself. We have put all of these things in the hands of these players and we have allowed them to go off with the BI tool and actually do exploration.

And there is no better place to do this type of exploration than around these brand new sources of Big Data and to be able to find information that we once were able to do. Once again you have to have a horsepower and the applications and the tools in place to be able to go through this data in a timely manner. But in the end exploration and “Aha!” moments I think is something that we were looking to give to all of our end-users.

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