“Big Data” was all the rage in 2012. Everyone from your company’s president, to President Obama to a passerby on Main Street had something to say about it. Whether any of them could actually define the term was another matter; not even the experts seem to agree on what it means.
2012 at a Glance
We spent the year interviewing and listening to vendors and early adopters talk about Big Data. We knocked on the doors of both brick and mortar firms whose businesses aren’t web-based and on those that are -- Linkedin, Eventbrite, Kaggle and Match.com are just a few examples.
And while the latter group spoke of pushing the envelope with Hadoop and machine learning, the others were dazed by all the Hadoopola -- they were excited by Big Data’s possibilities, but not yet ready to implement meaningful enterprise-wide strategies, to invest in the required technologies, to hire data scientists and so on.
It’s worth noting that some of these firms did run Big Data pilots, but that’s as far as they got.
“Big Data is really, really hard,” many of them told us.
That’s why we say that history will show that 2013, not 2012, was the year of Big Data. It will go down as the year in which companies talked less about it and began to adopt and reap real benefits from it.
And though we’re tempted to make bigger, but more specific predictions, we’re going to leave them to the experts in the market.
We asked them one simple question, “What’s your prediction for Big Data in 2013?” Here are the best of their largely unedited answers. It’s a lengthy read, but interesting, mind-bending and provocative.
John Schroeder, CEO and CoFounder, MapR
Revenue generating use cases (of Big Data) will trump cost saving applications.
- Hadoop will pull away from the other Big Data analytics alternatives.
- Hadoop expertise is growing rapidly, but a shortage of talent remains.
- SQL-based tools for Hadoop will continue to expand.
- HBase will become a popular platform for BlobStores (BLOB=binary large objects).
- Hadoop will be used more in real-time applications.
- Hardware will become optimized for use with Hadoop.
- HBase emerges as attractive platform for lightweight OLTP.
Laura Teller, Chief Strategy Officer, Opera Solutions
Wall Street is going to use Data Equity to Value Companies
As the year goes on, Wall St. is going to increasingly use "data equity" to value companies, much as they have used brand equity in the past. A company's ability to gather and leverage large amounts of exclusive forms of data will form a new axis in computing a company's long-term value. New fortunes will be made with this equation.
Big Data Apps will be a major trend in 2013
Big Data helps us finds new and different answers, but with Big Data's impact spreading across many markets, industries and fields of research, the answers also require new ways of asking the right questions.
In 2013, the real money will not be in data management platforms like Hadoop and NoSQL, or in how a business collects and processes data. Because most businesses will be naturally hesitant to rip and replace database and storage infrastructures that took years and often hundreds of millions to build, true innovation won’t take hold there. The real emerging market and money, or innovation in this case, will be in Big Data applications -- custom applications that help quickly answer domain-specific questions.
Herb Cunitz, President, Hortonworks
Emergence of vertically aligned Apache Hadoop “solutions”
As the keynote of Hadoop Summit last year, Geoffrey Moore characterized Apache Hadoop as currently crossing the chasm and that we would know it has landed on the other side and is enjoying adoption by the mainstream when vertical solutions arise.
As more and more companies gain success we will see patterns and solutions arise that are custom-fit for a challenge found in a particular industry. As the system integrators and consultants become more and more expert on Apache Hadoop, they will wrap solutions in packages and we will see the emergence of these vertical solutions. Facilitating the growth of this ecosystem is a core strategy at Hortonworks.
David Jonker, Head of Big Data Strategy, SAP