Top Big Data Trends For 2014
Updated · Dec 19, 2013
There is a lot going on in the business intelligence field, not the least of which is Big Data. When we asked a selection of industry experts what BI trends they anticipated for 2014, therefore, it was no surprise that Big Data loomed large. (Pun intended.)
Here are their predictions for the coming year:
Time to Get Real (Time)
The last couple of years have been focused mainly on improving the performance of queries and reporting on stored data. In reality, that meant making the most of historical data. These days, that isn’t fast enough. More and more organizations want the ability to recognize and respond to events in real time.
“2014 will be the year businesses develop situation awareness by implementing real-time analytics and real-time computation platforms to be able to process, analyze and react to massive amounts of data,” said Phu Hoang, CEO and co-founder, DataTorrent. “This trend mandates the support of massive throughput and the guarantee of high availability, linear scalability and ease of use.”
Internet of Things
Connected products are increasingly going to broadcast data back to product manufacturers and users. This has given rise to the concept of the “Internet of Things” whereby consumer devices, for example, are loaded up with sensors which report on such items as impending component failure, refills and the like. For example, jet engines will transmit operational data in flight so their fuel consumption can be adjusted to optimize fuel costs.
“The Internet of Things phenomenon will revolutionize how companies approach product planning, development and customer support,” said Srikanth Desikan, vice president of Products for Glassbeam. “The machine data analytics market is poised to take off as more companies wire their products to phone-home data. This data can be used strategically for product and service improvements, as well as to provide enhanced services.”
Big Data Clouds
The overwhelming amount of data that can now be put to work is causing problems, such as where to store it and how to access it efficiently. Instead of trying to keep it all in-house, look for cloud-based BI and Big Data services to increase in popularity this year.
“Many are predicting an acceleration in the number of Big Data workloads that are run in the cloud, due to two factors a) more big data sources will be cloud-originated and b) the low-cost, scale-out, elastic nature of the cloud will increasingly be recognized as the preferred environment for these workloads, as witnessed by the growth of such services as Amazon’s Redshift petabyte-scale data warehousing service,” said Karl Van den Bergh, vice president of Products and Alliances at Jaspersoft.
Big Data and Business Goals
Stefan Andreasen, CTO and founder, Kapow Software, believes that many companies’ first experience with Big Data failed to deliver business value because they analyzed existing data without setting goals for why they did it, what they were looking for and how to turn findings into actions.
“The next wave of Big Data projects will originate from the need to answer specific business questions such as what do top customers really think about our brand, and how can we increase our sales intelligence and close more deals,” said Andreasen. “Determining what data is important to answer these questions is a critical first step for any successful project.”
Big Data Marketing
2014 is going to be a key year for Big Data, as many of the early adopters start reporting on their successes and followers see results from pilot projects. Big Data implementations for marketing, in particular, will move from being small proofs of concepts into full scale production.
“By the end of 2014, over 70 percent of organizations with over $1 billion in revenue will have implemented or be close to going live with a Big Data marketing solution,” predicted Wes Moore, VP, Integrated Marketing Management, Teradata Applications.
Big Data for the Rest Of Us
The geeks have arisen and rushed to erect Hadoop-based edifices that the average business users find mind boggling. The bottom line is that Hadoop isn’t so easy to understand as many thought. But that’s not the only barrier. The data that Big Data systems spit out often requires interpretation by a highly trained and expensive-to-hire data scientist. That has to change.
“2014 is the year Big Data is made available for the rest of us,” said Mark Sarbiewski, chief marketing officer, Anaplan. “Business analysts need to be able to create their own analytic applications without requiring a lot of calculations and business rules.”
Humanizing Big Data
Sundeep Sanghavi, CEO and co-founder, DataRPM, calls for the humanizing of Big Data. He’s talking about being able to present business intelligence queries to systems using regular speech as opposed to complicated codes or scripts. This trend manifests in a few systems but is about to broaden in 2014.
“Natural Language Question Answering (NLQA) systems are tackling the task of teaching computers to understand human thoughts,” said Sanghavi. “Systems such as Siri, Google and Watson employ natural-language processing and computational linguistics to directly answer consumer knowledge search questions. By eliminating the technology learning curve, these virtual assistants, search engines and cognitive systems enable extremely easy access to information.”
Big Data Security
Like many others, Tibco CTO Matt Quinn thinks the new year will see Big Data become more focused on solving real business challenges, as well as harnessing the cloud to ease storage and analytic processing burdens. But he also expects Big Data to gain ground as its security challenges are addressed.
“Companies will still be apprehensive about sending sensitive data to the cloud, but whatever is already there will remain. New products and service offerings will be created to respond to this behavior,” he said. “I also expect cloud security to get cleaner and clearer in 2014. As this gets better, those same companies will move more data to the cloud than less.”
Drew Robb is a freelance writer specializing in technology and engineering. Currently living in California, he is originally from Scotland, where he received a degree in geology and geography from the University of Strathclyde. He is the author of Server Disk Management in a Windows Environment (CRC Press).
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.