Capitalizing on Big Data: Analytics with a Purpose
Despite the fact that we often see the terms used simultaneously, there actually are significant differences between business intelligence (BI) and data analytics.
If you’re a bit fuzzy on how they differ, Lillian Pierson recently posted a succinct video post explaining the key difference between business intelligence and data science (the rest of us would call that data analytics or Big Data analytics).
Pierson is the founder of Data Mania, a data science consultancy and education company, as well as author of “Data Science for Dummies” (2015). Previously, she worked as a project engineer consultant and a spatial data scientist. I highly recommend following her on Facebook, which is how I found this video.
Specifically, Pierson explains, BI draws on primarily internal data sources residing on traditional sources. Data science — her term for analytics — can involve both internal and external data in a variety of formats.
There’s another key difference, though, and that’s how BI and data science serve up the data. She points out that BI’s output is reports, data tables and dashboards, whereas data science tools offer up the info as data visualizations or interactive analytics.
In some ways, these strike me as constraints caused by the heritage of the technology rather than any required business distinction. There is a reason, after all, why Excel remains one of the most preferred BI tools.
But business users are going to need better visualization tools as they move beyond simple reporting to actually exploring data and making data-driven decisions. You should expect to hear more about that capability. In fact, just this week, Dell announced a partnership with data visualization specialist Datawatch that will add more visualization and dashboard capabilities to Dell’s cloud-based analytics platform, Statistica.
Datawatch’s visualization engine will become the permanent visualization engine for the predictive analytics platforms, Dell said. The new capabilities will allow business analysts to explore predictive analytics questions about industry trends, new sales opportunities and ‘what if’ scenarios.
Dell also revealed enhancements to Statistica’s Big Data analytics module, formerly known as Kitenga, and provided integration through its Toad and Boomi product lines.
The new functions are included in version 12.7, which is generally available. If you’d like to read more about the partnership, check out CIO.com’s recent write-up. It’s easier to read than the press announcement and adds a bit of context to the partnership.
Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.
