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Choosing the Right Advanced Data Viz Tool For You

“There’s data visualization and then there’s ‘advanced’ data visualization,” writes Doug Henschen in an InformationWeek article. As organizations are able to collect more and more data about…well pretty much everything, making sense of it is becoming a serious concern. It’s one thing to be able to collect vast amounts of data on your customers, it’s quite another to be able to take that information and make recommendations based upon it.

The good news is that you are not alone. Trying to make sense out of all the data organizations now collect has quickly become big business. According to IDC’s latest BI and analytics market share stats released in June, the data visualization company, Tableau Software, was the largest growing vendor in BI in 2011 with a 94.2% increase in software revenue. Data visualization is particularly hot because it makes data analysis easier. According to an InformationWeek study According to Henschen, “Just about every business intelligence and analytics vendor out there has released an advanced data visualization module or add-on capability within the last year.” From IBM, to Oracle, to SAP, to Microsoft, name a large BI player and odds are they’ve now added some form of an advanced data viz component to their offerings. But just because everyone and their parents now offer advanced data visualization tools, doesn’t mean selecting the right one is any easier.

What is Advanced Data Visualization?

So just what is the difference between data visualization and “advanced” data visualization? Well, for starters Henschen offers some sage advice: Forrester Research came out with a report earlier this summer identifying six traits that “separate advanced visualization from static graphs.” Here’s the top 5:

  • Dynamic data – Dynamic data is the ability to update visualizations as data changes in real-time.
  • Visual querying – You have the ability to change the query by selecting or clicking on a portion of a graph or chart (think of drilling down in a data set for example).
  • Linked multi-dimensional visualization – Selections made in one chart are reflected as you navigate into other charts.
  • Personalization – Gives users power to tailor the tool according to their individual proficiency. For example, power users can personalize the tool to see in-depth data and analytics while giving newbies a much simpler view and a more limited access to features and data.
  • Actionable alerts – Visualizations are only beneficial if you see them. Having the ability to set alerts to act as a safeguard, keeping you aware to what’s going on is hugely important.

Picking the Right Tool for You

Understanding what constitutes an advanced visualization is only half the battle. As every major BI vendor now has some type of advanced visualization offering, selecting the right tool for your needs can be a bit confusing to say the least. Henschen suggests that a good place to start is Forrester Research. They break down their scoring of leading BI tools giving you a more transparent view as to each tools offerings and their respective strengths and weaknesses. For example, Forrester weighs 50% of its overall score on “Strategy”. Within the “Strategy” component, 40% was based on “commitment and 45% on product direction, with only 10% based on pricing and 5% on transparency. The nice thing about having this level of transparency is that it allows you to reprioritize categories that are important to you. For example, Henschen writes “Personally, I would make the strategy scores account for 40% of the overall score, and I would raise the weighting of ‘pricing and licensing.’” So, as you can see by reprioritizing you can easily create a short list of vendors to consider.

Advanced data visualization tools are new and complex. I hope that by demystifying what advanced data is along with what the tools do, will help empower you in choosing the right tool for you and your organization.

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