Complex business decisions require the analysis of impossible volumes of data, and the collection and presentation of this information is generally referred to as ‘Big Data’. 
In the 1990s, you might have heard the terms ‘data warehouse’, ‘data marts’ or ‘executive information system’ tossed around by large enterprise solutions players, including major OEMs like IBM and database vendors such as Oracle.  The approach at the time was to attempt to gather the data into one place, but the user’s ability to query and understand the data was severely limited.
Late in 1998-1999, Google launched with little more than a one-line query interface sitting atop a huge indexed database of text snippets and URLs.  Their solution did not rely upon a ‘name brand’ relational database.  Google was built around a more distributed and purposeful approach to storing data, something they called, and still call, ‘BigTable’, built upon the ‘Google File System’.  BigTable does not support rich SQL queries and is built for a single purpose – to distribute petabytes of data across multiple devices for fast access.
In the early 2000s, focus shifted to increasing the horsepower of the back-end platforms; database server and storage performance, multi-indexing techniques, infrastructure virtualization across drives and servers, and massive parallel processing.  To keep up with the explosive growth of the Internet, systems had to ingest ever increasing rivers of data and run faster performing queries against that data to find the answers that business needed.
Then in 2002, something interesting happened.
In 2002, the film “Minority Report”, starring Tom Cruise, was released.  In that film, Cruise played a detective of the future, leveraging big data to predict crimes before they happened.  Of particular interest were the methods depicted for manipulating data through the use of glass panels and hand gestures to visualize and cull through mountains of information. 
A PhD from MIT, John Underkoffler, was engaged to help imagine the future of gestural data analytics for the film.  After that film was released, John formed a company to do exactly that, Oblong Industries, a case of life imitating art.
Since 2002, Big Data has become ever more sophisticated and specialized, and new companies are developing exceptional data analytics capabilities.  Examples include Kestrel, acquired by Boeing Defense in 2008, Hadoop, an open source distributed computing platform, and Teradata, perhaps top of market in this space, with a focus on robust data analytics capability.
A more recent entrant, Saffron Technologies, takes a very different approach.  Rather than providing a query engine where the user asks for specific information, Saffron creates an analytics model that operates more like the human brain, something they refer to as ‘distributed associative memory’.  In essence, Saffron is able to cross-correlate all data within a data collection, and when prompted with a search word, returns information correlated by relevance, effectively allowing users to understand answers to questions they didn’t even think to ask.
The current wave of M&A consolidation arguably began in July 2010 with the $400M acquisition of GreenPlum by tech giant EMC.  Greenplum's technology was widely viewed as strategic to EMC's virtualized Private Cloud infrastructure to enable their customers with a big data solution. The price tag, estimated at nearly 14x revenues, was the highest multiple recorded for a data-warehousing vendor at the time, but clearly worth it since Greenplum has served as the foundation for EMC’s widely-praised big data division.
The world today is ten times deeper in data now than it was when EMC plucked GreenPlum.  With less than 1% of collected data created being analyzed, there is still plenty of room for additional acquisitions to pay off with a quick expansion of markets.
In 2012, several Hadoop-related deals were executed to enable the acquirers to swiftly turn products loose amidst the green fields of big data.  For example, W2O broadened its appeal with a patent and technology buy out of Austin incubator graduate Ravel.  UK public company WANdisco drove into the Hadoop segment for $3.6M in stock plus $1.5M in signing bonuses.  Additionally, less than a month after Dell closed its multibillion dollar buy of Quest Software, Quest announced it would buy content mining and analytics provider Kitenga. 
In big data’s functional core, old guard companies continue to be challenged by younger firms such as QlikTech and Tableau, plus a host of new niche players that are assembling new capabilities acquired through M&A.  In the first half-year of 2012, that included Opera Solutions, which completed its stack for ad hoc analysis of government and enterprise big data with Boston-based BIQ, and Lexington Analytics. Pricing wasn’t disclosed, but Opera’s top tier PE owners had dropped $84M on the upstart a couple months prior.
In 2013, new entrants in the space are moving beyond infrastructure, engines and the analytics, and are focused now on re-architecting enterprise applications so they can make sense of the galactic volumes of big data.  A stealthy San Francisco startup, Jut, recently received $20M in a Series B financing by Accel, Lightspeed Venture and Wing.  Jut is working on solutions that live ‘above’ the big data infrastructure and provide better ways to derive insights from complex data.
The month of October 2013 saw several notable M&A transactions involving big data companies, including Monsanto‘s acquisition of big data weather company Climate Corp for more than $1B, IBM’s acquisition of Daeja Image Systems, Intuit’s acquisition of Level Up Analytics, and Facebook’s acquisition of startup Onavo. 
One potential takeover that would make big news in this space is Splunk, the first of the big data companies to go public.  Splunk debuted with an IPO in April 2013, and its price has nearly tripled since then, with a current market cap of $6.4B and a sales multiple of 25.6x.
We believe the big data infrastructure and analytics market will continue to heat and begin to specialize further into industry verticals, with a strong emphasis on the intelligence, healthcare, and finance sectors.ary Beyer