UPDATED 12:10 EDT / MAY 09 2012

How Big Data Helps Ericsson through Mergers, Deals and a Solo Future

Ericsson’s coming into its own after a split with Sony and decreasing sales in CDMA and network operations, having been selected by T-Mobile USA as their first North American partner for the Ericsson Antenna Integrated Radio (AIR) solution.  It’s an LTE initiative expected to transform T-Mobile’s network, deploying LTE technology across the carrier’s key US market with Release 10 capable hardware.  And it’s a $4 billion network overhaul for T-Mobile, which is on a solo path all its own after a failed merger with AT&T, left to compete in an LTE-anxious world alongside Verizon and other rival carriers.

With the deal, T-Mobile will be the first to use Ericsson’s AIR technology, expected to improve existing coverage and hasten LTE launches in the US.  Ericsson will install the radio, tower and switch room equipment, while also providing consulting and systems integration, as well as rollout services.  It’s a turnkey service for installation, commissioning, integration and migration, building on a relationship Ericsson’s had with T-Mobile for nearly six years.

But Ericsson has an even older relationship that’s helped solidify its networking solutions for over a decade, having inadvertently discovered the benefits of Objectivity/DB to store and process complex structures (collections, trees and networks) for managing their own data.  Objectivity, having developed a niche competency for networking, has aided the development and management of CDMA Intelligent Base Station Controller, building and learning alongside the needs of the telecommunications industry.

Ericsson was aware of Objectivity early on, but didn’t recognize their potential until acquiring them as a consultant and service provider when they merged with Marconi in 2005.  An acquisition of this scale required a great deal of technology integration, and that’s when Ericsson had to come to terms with their own limitations.

“Ericsson was very compartmentalized and depended on landline operations for infrastructure,” says Leon Guzenda, founder of Objectivity.  “They had their own operating system and language, and we never actually got a product built there.  out of the blue they acquired Marconi and Nortel, and instead of monetizing their own infrastructure they quickly realized ours was better and extremely flexible.”

The epiphany was a turning point for Ericcson, which worked with Objectivity on a number of independent applications, eventually making Objectivity the base of their real-time framework.  “It’s a very strong relationship,” Guzenda notes.

The big data crossroad – a necessity in creative growth

Objectivity’s work with telecoms and other industries in big data management mimics the type of story we hear from many data scientists today–a cross section of disciplines and interests enables a data scientist to connect the dots needed for creative solutions and increased productivity today, especially as big data finds its technology being applied to a very broad range of enterprise departments and layers in the stack.  Simplifying it all is Objectivity’s angle, and it’s been quite successful for the company so far.

A bubbling background in C++ and groupware helped Objectivity get into the telecom business, working with Nortel as their dial-up traffic grew and forced a change in their services.  Ongoing work with Sun Microsystems gave Objectivity insight to highlight faulty tolerant hardware etc., finding another area of application in the telecom world.

As the telecom industry finds itself in the midst of another revolution, meeting the demands of broadband technology and enhanced networking, it’s faced with the same dilemmas as any other enterprise–work smarter and leverage analytics to overcome compounding data and slow decision-making processes.  For Ericsson’s growing network, that means real-time management and big data solutions.

“They have an awful lot of data but their databases were relatively small,” Guzenda recalls.  “Things like call records get big really fast.  They’d done the individual element management well, but what they hadn’t done was give customers tools to analyze the other stuff like long term log correlation.  They saw we were already doing this.  We’re managing in Big Data systems deployed by the Intelligence Community on active cases and that really got their attention.”


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