Key Features to Look for in Advanced Visual Analysis Software

“In 2009, more data will be generated by individuals than in the entire history of mankind through 2008.”
– Andreas Weigend, former Chief Scientist, Amazon

“Between the birth of the world and 2003, there were five exabytes of information created. We [now] create five exabytes every two days. See why it’s so painful to operate in information markets?”
– Eric Schmidt, CEO, Google

Enterprise data will grow 650% over the next five years. Of that, 80% of that will be unstructured. The amount of new information generated next year alone will amount to more than the previous 5,000 years. Finally, the number of text messages sent in the last 24 hours is one for every human on the planet.
– David Cappuccio, Analyst, Gartner Group


We all recognize that big data is only getting bigger, and with all the hoopla surrounding big data, what’s not to be concerned about? Big data is typically presented as a monstrous beast that is growing exponentially and spiraling out of control, and our ability to make sense of this data has not been keeping pace.

However, when equipped with the right tools to organize and manage your data, you can navigate seamlessly through the growing universe of data and turn the big data problem into big insights. Traditional analytics techniques are slowly starting to be deemed limiting. Many forward-looking organizations are incorporating advanced data visualization coupled with social network analysis capabilities, or advanced visual analysis, into their data analytics toolkit to proactively identify relevant actionable insights in a timely basis in ways not possible before.

Advanced visual analysis is the new generation of transforming potential liabilities caused by big data into invaluable business assets. Graph-based visualization, together with social network analysis capabilities, are most effective for seeing critical relationships, trends, anomalies, and patterns in your data that are not readable by computers but by the most powerful pattern-recognition system available – the human brain.

As you or your organization start to include advanced visual analysis into your analytics toolkit, here are some features to look for that are essential to maximizing the business value of your big data.

1. Access to Any Data Source, Any Time
Aside from traditional data sources such as Excel, XML, and text formats, new types of data are flowing into organizations at an exponential rate, such as clickstreams, GPS, biometric, cell phone intercepts, blog posts, Twitter feeds, point of sales, text, video, audio, seismic, Web logs, and RFID data. It is important that your advanced visual analysis application can access data from disparate data sources and integrate them into a single view.

2. Incremental loading
When you have a lot – even up to millions and billions – of data points, it is never effective to load or display all of this information at once. Loading all your data at once is slow and the amount of data presented might be overwhelming. With an incremental loading mechanism, you can incrementally load a subset of data from the data source that is relevant to your visualization purposes and analyzed in-memory for interactive analysis.

3. Filtering
Once you have your data mapped out, a key element of data and insight discovery through these applications requires sophisticated data filtering techniques. This enables you to focus on key trends, patterns, and outliers that matter to you for uncovering actionable insights without being distracted by other data.

4. Customizability
No matter what industry you’re in, you are the domain expert. Everyone’s usage models will differ from organization to organization. There are plenty of “out-of-the-box” solutions, but many of them don’t understand the unique context in which you are working in. Customizing your advanced visual analysis applications to fit your usage model will enable the most effective visual analysis experience, and help you identify insights that matter most to you.

How are you dealing with big data?