Top Three Big Data Analytics Technology trends to watch for in 2013

  • BLOG
  • July 30th, 2019

2012 was a watershed year in analytics, as Big Data dominated the media, if not data scientists’ lairs. In 2012, the most forward-thinking companies began to incorporate big data analytics into their strategy work, rather than using it as a tactical tool or in reactive mode. What will 2013 bring? Which technologies will still be relevant and which will fade into the background? In 2013, look for more and more organizations to embrace analytics as a key driver of strategy for making better decisions and driving innovation.  We see the following three trends gaining wider adoption in 2013 

1. Building Intelligent Systems and the Rise of the Intelligent Machine

This trend will materialize much more boldly in 2013, especially with announcements from major corporations on the idea of the industrial Internet. This trend can be distilled into integrating data and analytics capability into a machine learning consulting format to optimize its usage patterns. Creating machines that are more intelligent is the next big idea! Machines are producing very large data sets however real-time insights, optimization and predictive capability need to be delivered. How does one build an intelligent system? What are the use cases and business benefits? What are the determinants and technologies for such a system? These are key questions to consider. 

2. Advanced Data Visualization and Analytics Tools that Business People Can Use:

Most analytical shops need to migrate beyond the traditional business intelligence and analytics dashboard view and move to a cockpit metaphor to gain an edge. One way of doing this is to focus on events: Data at Rest vs. Data in Flight. For example, data in flight (evaluating event based data), which has the potential to unleash vast economic and customer value. However, most analytical shops are not equipped to handle event data. It’s a new skillset that needs to be learned, it requires event processing, messaging systems and rules engines to name a few. Implementation and mastery of data in flight will provide a competitive advantage. Also, data analytics firms and businesses today need to introduce more analytics tools that ordinary business people can use. One by-product of the data scientist shortage is the absence of analytics tools that can be used by marketing, sales and others. Look for this void to be filled in 2013, as vendors work to craft new solutions that take the mystery out of data analysis – like a data scientist in a box.

3. The Hadoop Trend Continues to Amaze:

Hadoop 2.0’s flexible and modular architecture for parallel processing frameworks will be positioned towards an operating system for data. Hadoop being the de-facto operating system for parallel processing frameworks such as Map Reduce and MPI, two very distinct flavors of parallel computation required in the Big Data toolbox. Businesses today have a wider range of data analytics solutions to choose from compared to even five years ago. Part of the ‘emergence’ of Big Data solutions has spurred the growing maturity of Hadoop and MapReduce coupled with a plethora of open-source analytical software solutions designed to run on top of it. Stronger analytical solutions have arrived to handle such massive and complex amounts of data faster. This very explosion in the number of affordable and accessible Big Data solutions available has also made the job of picking the right one that much tougher.