What is data discovery? Is it something real or is it just another in a long string of buzzwords invented by marketers to instill a new need for their product or differentiate it from the competition? No, this time it’s real. But it’s hard to give a precise definition.
Wikipedia states this definition: “Data discovery is a business intelligence architecture aimed at interactive reports and explorable data from multiple sources.”
Gartner is a little more expansive: ”Data discovery software and traditional BI platforms offer similar capabilities. But there are some important differences.” Gartner explains that with traditional business intelligence, the buyers are in the IT department, the user interface is in the form of reports, dashboards, or grids, and it is primarily used for monitoring and reporting. It says that for data discovery, the buyers are the business workers, the user interface is through data visualization, and it is primarily used for analysis.
The Oracle description is actually my favorite: An “ongoing dialog with the data” that “happens in the moment at the hands of the data analyst.”
The fact is that, until you get into the data, not only don’t you have all of the answers, you may not even have all of the questions. Unanticipated questions mean that you may not have the right data on the screen to address the question when it forms in your mind. Data discovery allows you to explore the data to answer those questions that pop up as you look at the data. Sometimes that means looking at the data in a new way—a rich visualization instead of a table, a heat map instead of a scatter plot. Sometimes it means including more data in your universe—does the sales data beg a question about customer loyalty? Do you need to grab some customer history data? Sometimes it means enriching your data with calculations and classifications.
Users who are both data-driven and “creators” of analyses (“Detectives” according to Aberdeen), use data discovery tools “to freely explore pertinent data and approach business problems from a new angle.” They frequently don’t know where the data will lead them, but the use the data to inform the decision at hand. So a data detective might look at a P&L and see something that looks out of place. From there, she may want to drill into the data to see transaction detail. But that might spark another question related to the sales region, so she might need to drag the sales data onto the screen along with the financial data and then do some visual trend analyses to pinpoint a problem or opportunity. A data discovery tool will allow the user to do all of this in real time without IT intervention.
BIO Business Intelligence for Microsoft Dynamics provides full functionality for interactive, self-service data discovery. From drag-and-drop analysis to adding available cubes on-screen to in-grid calculations, BIO lets those Data Detectives leverage their knowledge base and analytical skills to develop deep insights and solve business problems.
To see how BIO is used for data discovery, take a look at this short video.
Join us for a free webinar for an introduction to all of BIO’s business intelligence, reporting, and data discovery capabilities.
Click here to read Aberdeen’s report, Introducing the Analytical Mind Map: The BI Personality Test. Not just informative, this report is actually fun to read. At the end, there is a link to Analytical Detectives: Solving Data Mysteries, which has the detail on Aberdeen’s Detective persona I referred to above.
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By Sandi Richards Forman of BIO Analytics Corp., a Microsoft Dynamics Business Intelligence (BI) Solution Provider