This is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of "Data Discovery Tools and End User Mashup." The speaker is Abhishek Gupta, Product Manager at InetSoft.
The only other mega BI vendor I want to single out there is probably SAP with MIRO. So they are trying to build out a visualization and memory-based data discovery tool called Lumira. You will probably see it at SAPPHIRE which is next week, SAP’s major conference. You will probably see Lumira focused on very heavily. Probably the biggest only concern here many people already complain that there are so many tools in the Business Objects and SAP portfolio, and there’s been some shifting focus on which tools to use in which situations.
So we haven’t seen a lot of SAP Lumira adoption yet because I think the entire SAP and Business Objects installed base has been looking at Webi and Crystal and a lot of the BW tools around design studio and analysis, et cetera. So we haven’t really seen as much adoption yet of Lumira in the market.
But anyway, the moral of the story is data discovery alive and well and becoming really the dominant segment of the BI space right now and this is how people are integrating, reporting, and analyzing their data.
Now if we are going to do this, I think we want this notion of enabling end users to use these data discovery tools, where they can mash-up sanctioned data coming from the data warehouse with other personal files they might have, again whether that’s Excel or whether that’s that marketing campaign data from a software-as-a service provider.
This is where this notion of data mashup comes up where the end-user themselves as opposed to a formal IT team is able to mash-up and blend data together. And I would argue that this doesn’t necessarily have to be just an individual working by themselves, it could be an individual business user working side by side with an IT person who has the stronger data integration skills.
But the moral of the story is it’s a local or smaller team blending the data together and then providing an ability for them to promote that to be reviewed by some sort of sanctioning body that says okay yes, we think this analytical view that’s created is worthwhile and valid. Let’s promote it for wider dissemination across the enterprise.
So introducing this notion of a data mashup or as Tableau uses the term ‘data blend’, it's the same concept here, but it meets this requirement of okay where it’s kind of like the movie Spider-Man, the quote from Spider-Man, “With great power comes great responsibility.”
If we are going to enable people with this great power to blend data together, mashup data, let’s have the responsibility of putting the right process in place to maybe let people do that, great. But if we are going to use it for a wider dissemination, let’s have a sanctioned team of people that can be responsible for promoting that for that enterprise-wide dissemination.
And the real lynchpin of that idea is that all the stakeholders in your company buy into this notion of the certification of this BI content and then recognize how to distinguish between a prototype where yeah this is just something that a bunch of people blended together. They took that marketing campaign data and blended it with some sanctioned data from a data warehouse, and they created a prototype. And hey, we create lots of prototypes just to see if there is anything interesting in there or any type of insightful analytical view. We shouldn’t treat that prototype as something that’s a gospel or system of record by any means.
Now, maybe we promote some of these prototypes that we create, and the idea we created them, the marginal cost of creating a prototype is so cheap that we just build lots of these prototypes, and then maybe some of those will be promoted to limited production or enter some sort of pilot phase really, where a small group of users use this on a day-in-day-out basis.
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