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Growing Self Service BI

Jared Hillam

Jared Hillam

June 4, 2016

 

Several years ago I released a video titled “What is Business Intelligence.” While this was released long ago, it still applies to the market today. But there is a category mentioned in the video that I called Micro decisions which has really taken off over the years. The market often calls this self-service BI. The focus of these vendors that provide self-service BI is to enable business users to make impromptu decisions from data even though the data might not formally be available from sanctioned IT reporting systems.

This often meant that the users of these systems worked more like rogue data consumers rather than winning the good corporate citizen awards. However, because they were able to produce answers to the executives, they soon became seen as heroes which made the slow IT team look bad.

These self-service BI vendors approached the hairball of data integration with assumptive associations. So for example, if one source of data has a date/time column, it will automatically associate that column with the date/time of the other source of data. Was it possible that an incorrect association could be made? Yes, but the association doesn’t happen in a black box and the process can be guided. So the Vendors depth of this kind of automatic association is really what separates the men from the boys. And is also a key factor in being able to gradually bridge the rogue analyst into a corporate visionary.

Intricity has an approach for guiding these micro decision platform deployments for larger corporations that want to take advantage of the rapid prototyping capabilities while broadening the reach of the data integration into non-proprietary avenues like a corporate data warehouse.

The first reaction that somebody who strictly focuses on self-service BI is, why would you need to take the data out of the proprietary self-service system? Here are a few reasons:

  1. In a large corporation, there are often multiple Business Intelligence tools that are feeding the business information. While it might sound feasible to just replace their current BI technologies, (and notice that’s plural) that often is easier said than done with engrained corporate cultures and multiple departments
  2. Integrated data is often used to drive other processes that are not solely committed to analytics. Sometimes this is data coming from an operational data store or data lake which is ultimately justified by feeding into a Data Warehouse. Leveraging a Data Warehousing effort to acquire data for other operational efforts is a very common occurrence, and it frees up transactional systems from getting hit hard with requests. This activity simply cannot be done by routing all data requests directly through the BI tool. That would be far too expensive from a licensing perspective and far too proprietary to enable multiple endpoints.

By running a parallel engagement Intricity is able to deliver self-service BI while using the prototyping advantages of these platforms to model and iterate a persistent Data Warehouse that the rest of the corporation can take advantage of. This also ensures that the data warehouse is delivering the information that will benefit the users.

There’s a lot more discussion to be had here, and I recommend you reach out to Intricity and talk with one of our specialists. We can help bridge your rogue self-service BI and the rest of your organization's deployments into a data-sharing strategy that everybody benefits from.

Related Whitepaper (by Qlik): The Qlik Associative Difference

 

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