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

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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?

Big Data = Big Opportunities through Advanced Visual Analytics

We live in a fascinating data-driven world full of challenges and opportunities – the world of Big Data. With the continuing, explosive growth of data in terms of quantity, diversity of sources and types, and speed, there are tremendous opportunities to explore this “Brave New World of Big Data” to discover new insights that were hard to uncover in the past.

In recognition of these new opportunities, more and more organizations are adding data visualization applications powered with advanced analytics, such as Social Network Analysis (SNA), into their portfolio of advanced analytics – what is often called advanced visual analysis. The growing recognition of the role of advanced visual analysis as part of analytics toolkits is highlighted by recent acquisition of i2 Technologies by IBM, growth of visualization based business intelligence products from QlikView, TIBCO/Spotfire, and Tableau as well as the recent move by Facebook to provide Open Graph as part of their makeover. This is indeed an exciting time for advanced visual analysis.

The growing use of advanced visual analysis applications, especially graph-based systems powered with SNA techniques, have led to remarkable recent track record of success in combating global terrorism, cyber warfare, and criminal fraud activities in various industries. New technologies such as pad computing devices, GPS and biometric based systems, and next generation network management systems for integrated communication of audio, data, and video, the continuing growth of online social communities, as well as integrated demand-supply chain systems have led to rise in demand for using these applications to discover insights from not just highly structured data in traditional enterprise repositories but from all data types across all types of information repositories. The increased success of these applications in different industries will continue to fuel the growth in advanced visual analysis applications of all types in the coming years.

The ongoing industry recognition of the power of advanced visual analysis will yield better integrated analytic systems in many cases, better defined visual analysis infrastructure in others, and overall a superior experience and results for organizations focused on maximizing the value of their Big Data.   This is a fascinating and exciting time for those of us involved in visualization, advanced visual analytics, and advanced data analytics of all types. We are entering an era where our ability to discover actionable insights in the right context is leading to a fundamental paradigm shift in how we leverage our data assets to create more agile, efficient, and intelligent organizations everywhere.