In 2011, we saw Big Data pick up steam and emerge as a sought-after solution to companies’ business intelligence problems. Big Data, however, spent the year sharing the media spotlight with other IT trends, namely cloud computing and mobile. This won’t be the case in 2012. According to IDC, Big Data will assert itself as the “must have” competency of 2012 as the volume of digital content grows to 2.7 zettabytes, up 48 percent from 2011. The year 2012 will surely be the time in which the concept of Big Data is fully realized, and organizations will no longer be asking “What is Big Data?”, but instead, “How can we use Big Data?”
What Did 2011 Teach Us about Big Data?
For one, Big Data has inundated nearly every industry, and it has thrown a bright spotlight on the role of the database. In 2011, NoSQL became the face of Big Data for many business leaders as they looked to it to help scale processes that relational databases couldn’t. Industry leaders quickly realized, however, that this was a temporary fix, and although NoSQL is an improvement from outdated relational databases, it still wasn’t able to conquer complex business processes and models. Ultimately, we concluded 2011 with a better grasp on the Big Data techniques required to ensure data models are scaled in a way that is cost effective, timely and efficient for businesses’ crucial practices, but we lack an explicit sense of the technologies needed to actually make that happen.
In 2012, then, organization will be looking for the supporting Big Data technologies that have already proven to be successful, and one such example with quite a long history of success is the object-oriented database (ODB).
Early adopters, such as the U.S. Federal Railroad Administration, have already reaped the benefits of ODBs: expecting rail freight traffic to double by 2020, it created the RailEdge Movement Planner application to perform analysis of highly complex object models more than 30 times faster than a relational database could achieve.
The RailEdge data schema needed to organize minute details and readings from a vast network of information sensors and physical items—the number of engines and cars per train, weight and payload, rail traffic, congestion at depots and so on—all against the backdrop of time. That is worth repeating. Being able to analyze and shuffle all this data as it relates to time really creates Big Data. Moreover, when a relational database couldn’t process it quickly enough, huge efficiency gains were lost. The new system, though, underpinned by the object database, has improved fuel-efficiency and average train velocity such that it saves hundreds of millions of dollars annually in capital and expenses.
What Does 2012 Have in Store?
According to a Forbes article, the biggest obstacles for business leaders will be determining how to properly analyze the record-breaking amount of data that will be coming in from all directions and how to make it fit into business’s very complex business models and strategies. IT and business leaders will continue to search for examples that show how technologies like ODBs can be applied to their specific Big Data needs.
One such example is online ticketing service Travelocity.com, which uses Sabre’s Sonic Inventory System, the most used ticketing inventory system in the world, to support behind-the-scenes data management tasks. In an industry where data is input at a record pace, processing the data quickly and efficiently is a necessity. The massive amount of transactional throughput of the online ticketing service creates massive pressure on databases to handle every detail quickly and—far more importantly—accurately.
The sheer amount of data Sabre must process makes relational database technology unusable. The Big Data needs of each airline feeding into the system—30 at last count—mean that an object-based data model was the only way to effectively maintain high performance while controlling the costs of unnecessarily bloated IT infrastructure. Harnessing Big Data to quickly and accurately process millions of transactions per day has created value for Sabre in cost savings and by boosting the brand’s reputation for delivering high-quality services. The system allowed the company to switch from using multi-million-dollar, high-end mainframe and data center hardware to relatively low-cost commodity infrastructure without sacrificing system performance and availability. The system is truly “always on,” exhibiting zero downtime since switching it on more than three years ago.
For value beyond simply dollars and cents, harnessing Big Data has actually empowered climate-change scientists to operate on a timescale of minutes rather than years. Tracking the effects of arctic ice sheets on the world’s climate is an intricate process that requires analyzing an immense amount of both historical and contemporary data. Scientists must monitor volumes of incredibly minute pieces of data in the petabyte range.
But the National Snow and Ice Data Center (NSIDC) did just that. The NSIDC’s scientists must process billions of complex data objects with true database functions to allow a time-centric change analysis of the Greenland ice sheet. Dealing with time-series data sets at Big Data size required an object-oriented model that was driven down into the object database’s architectural implementation. Digging through this amount of information without a powerful object-based data modeling schema would take years, rendering the results a matter of historical record rather than actionable intelligence.
Although 2011 saw Big Data gain momentum, 2012 will surely be the year in which Big Data actually starts to deliver, and it will throw the role of the database into an even starker light. Those ahead of the curve have already identified the direct correlation between using Big Data and gaining the ability to innovate and be successful. Business leaders from all industries are sure to follow suit, and indeed many of the database technologies in numerous data centers will likely appear different by the end of 2012. In this new era, it is becoming essential for companies to take advantage of Big Data to realize big opportunities.
About the Author
Versant Corporation’s VP of Technology, Robert Greene, has over 15 years experience working on high-performance, mission-critical software systems. He provides the technical direction for Versant’s database technology, used by Fortune 1000 companies such as Dow Jones, Ericsson and China Telecom.
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