As larger data sets start to take root across various industries, it is going to be important to put those “big-data” results into a more manageable picture for end users and analysts. Many of the existing “big-data” end users are already familiar with the data sets and how they wish to look at those data sets.
However, the true value of “big-data” or analytics on “big-data” is going to be presenting the information to the end user who may still be thinking about analytics in “small-data” ( … or relatively small data… ) terms.
For example, new “big-data” analytics provides a “richness” of information and an increase of the dimensions that “small-data” systems cannot match. Yet, many users in marketing or product management may not understand how to make the leap from “big-data” aggregates to “big-data” detail because they don’t have the context of the “big-data” detail(s) they are looking at.
Mixing and Match with Big-Data
The twin challenge associated with the ability to handle and analyze “big-data” is the ability to put that analysis into context. “Big-data” often refers to senor, geographic or application data. However, not many people in end user/analyst communities have the ability make the leap from those “big-data” details to an end “so what picture?”.
This week Tableau announced the next edition to their business intelligence / data visualization product line – Tableau 6 – which supports the ability to “blend” data sets for end user visualizations that will tell the story that marketing and product management will understand and have that “AHA!” moment. While the data visualization is nothing “new”, the ability to perform with “big-data” data sets will be the key aspect. If the visualization takes too long, the marketing analysts and product management teams will lose interest and use less detailed analysis tools.
As telecom data rockets further and further for social media, location based services and overall smartphone usage; “big-data” is going to hit head long into telecom BI/DW teams. And while those teams are struggling with the ingestion of the data, end users are going to demand analytics and visualization tools that don’t hold back their “day jobs” from being completed…
Using data visualization tools, like Tableau’s new offering, will offer the ability to match the potential of the data with promise of the analysis.
How is your telecom BI/DW team positioned to meet end user requirements for visualizing big-data? Strictly using aggregates? or big-data detail?
Post your comments below or email (John.Myers@BlueBuffaloGroup.com) / twitter (@BlueBuffaloGrp) me directly.