February 2013
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Month February 2013

Seven dirty secrets of data visualization

Visualization is the new ‘must-have’ element in project proposals and personal portfolios, and startups like Platfora, Datameer, and ClearStory Data and Chartio are raising millions for analytics platforms with browser-based visualisation interfaces. “Click” and read on…

What is “dark data?”

Answer: It’s that neglected data that accumulates in log files and archives that nobody knows what to do with. Although it never sees the light of day, no one feels comfortable destroying it, because it might prove useful someday.

Could This Be The “Someday” You’ve Been Waiting For?

With all the recent press about the value of “big data,” you may be thinking that now is the time to dive into the secrets of the dark data hiding in your organization.

But before you invest in expanded storage capacity or sophisticated data analytics tools, take time to ask the big questions first — the ones that seek out the real value of the data for your business.

The authors of the CIO.com ebook, Big Data Analysis: What Every CIO Should Know, suggest that you start with such blue-sky questions as:

If only we knew . . . 
If we could predict . . . 
If we could measure . . . 

Determine what information you need in order to answer those high-value questions and use that as the standard by which you evaluate all the available data, including the dark data that has never been a part of your regular business operations.

Is Your Dark Data a Business Intelligence Gold Mine?

By itself, some of that dark data may not have much value, but combine it with data you already collect or purchase and you may have a digital gold mine. Those web log files that were once just digital clutter could be the key to unlocking changing patterns in customer behavior that can put you ahead of your competition.

By taking the time to assess the data’s value to your business and investing in the tools you need to shine a light on dark data, you may be able to turn those digital “black holes” into real business intelligence that you can put in the hands of your decision-makers.

Big Data—Opportunity or Hype…?

Big data. Over the past few months, this term has become all the rage in the business world. But, does it deliver real results and opportunity? Or, is this just hype to sell more software and services?

Whether created within or outside your data center, some executives and analysts are starting to see its inherent value: gaining insights that no other competitor has… That said, there are others who are still quite skeptical.

For example, Greg Szwartz, Director of Deloitte, believes that although big data may provide “game-changing insights,” it is impractical to believe that the average business can undertake the effort needed to analyze large volumes of data. In fact, it is a battle to analyze the data they already have.

However, Gartner analyst Mark Beyer believes there can be no such thing as too much data. Big data is simply a fundamental shift in the way data is viewed. If firms don’t gain control over this massive amount of information, they will miss out on an opportunity that can help them beat the competition and grow.

Before you write off big data as just the trend of the moment, the article “Big data: all you need to know” has outlined five questions that every executive should ask themselves:

  1. What do you wish you knew? Decide what you want to find out from big data that you can’t get from your existing systems.
  2. What are your data assets? Determine if you can cross-reference this data to produce insights and build new data products on top of them. If you can’t do this, explore what you need to accomplish this.
  3. What is the most valuable opportunity for using big data techniques and technology? Prepare a business case for a proof of concept, keeping in mind the skill sets you’ll need. Talk to the owners of the data assets to get the full picture and build a team of advocates.
  4. Can you prove what benefits Big Data will bring to your business? Start the proof of concept. Also, make sure that there’s a clear end point so that you can evaluate what the proof of concept has achieved.
  5. Are you getting real insights delivered? Once your proof of concept has been completed, evaluate whether it worked. Find out if your concept is yielding real results and if it could be extended to other parts of your organization. Plus, see if other data could be included. By knowing how far you can take your big data initiative, you’ll soon realize whether you should expand, change, or scrap your implementation.

It’s time to get started…