Many organizations are acquiring larger and larger amounts of data. Big Data is the massivie and complex data that is now challenging traditional database systems and is one of the major trends in the database industry.

Related: Clearing the Big Hurdles to Big Data

Big Data isn't a replacement for relational databases. Relational databases will continue to support the core mission-critical applications of organizations. However, changes and progress are impacting SQL Server professionals. For example, you can now combine your relational and non-relational data with the PolyBase available in SQL Server 2012 Parallel Data Warehouse.

Going forward, it will be important for DBAs and SQL Server administrators to keep up-to-date on Big Data trends. The following Big Data stories recently caught my eye.

Big Data is Maturing

Big Data has gone mainstream and is now part of IT architecture for most large organizations. Major Big Data themes you'll read about in 2014 include:

  • Structured vs. unstructured data
  • Interactive Hadoop and operational analytics
  • Storage challenges

Learn more by reading Big Data and analytics: The year ahead by Andrew Brust.

Big Data Security

The goal of Big Data analytics for security is to obtain actionable intelligence in real time. However, while Big Data analytics holds promise, there are challenges that must be surmounted. There's no doubt that Big Data tools are changing the security analytics environment.

TechRepublic recently interviewed two Cloud Security Alliance (CSA) members about their research and the 2013 Big Data Security Intelligence report. Learn more about how technologies such as Hadoop are impacting the security landscape from Brian Taylor in How Big Data is changing the security analytics landscape.

Mastering Big Data

Turning data into useable knowledge and actionable intelligence in a timely manner is the focus of Big Data and predictive analytics in 2014.  Forbes' Ben Kerschberg outlines five essential steps needed to master Big Data and drive business growth:

  1. Infer, infer, infer
  2. Empower a C-level data and predictive analytics champion
  3. Assess and modify your supply chain in a multidimensional global context
  4. Give your data time-critical situation awareness
  5. Rely on a core platform that creates derivative intelligence and knowledge in real time

Read the full story at Five Steps to Master Big Data and Predictive Analytics in 2014.

Related: Growing Big Data (new ways to use data sources and unstructured data for decision making)