Big Data Analytics in 2015

Big data is massive and messy, and is increasing day by day. It has gained lot of pace during recent years. Organizations are now making use of sophisticated analytical tools and techniques in order to get insights out of Big Data to solve Business Problems. This blog illustrates the trends of Big Data Analytics in 2015.

With the high velocity of Big Data expansion, organizations are now emphasizing in the domain of Big Data Analytics.  

TRENDS TO WATCH IN 2015

Security Intelligence: Analytics become a critical app for integrated security threat monitoring.

Distributed “Edge” Analytics:  Expects increased interest in pushing analytics closer to the edge devices (e.g. mobile devices, sensors, intelligent routers and actuators)

Self-Service Tools: LOB executives and teams demand access to use simple analytic tools that provide visualization rich output. They want analytic tools to be integrated in enterprise apps.

Mobile Analytic Tools: The demand for mobile-enabled analytic tools that are intuitive, will continue to increase in 2015. Analytic tools of mobile will further drive demand for analytics, big data and visualization capabilities.

Predictive Analytics: In 2015, not just data scientists and specialists, but also LOB analysts to increasingly use predictive analytic algorithms and modeling techniques to help them understand potential future trends in the data.

Real-Time: In 2015, we will see huge demand of executives for real-time analytic capabilities, especially in the area of social analytics and Internet of Things.

Data Visualization: The market for visualization products will continue to grow as decision makers demand dashboards with easy to read graphs. For the convenience of end users, vendors should design easy to use self-service solutions.

Social Media Analytics: It is expected that Social media analytics will become an integral part of business.  All LOB execs will want to learn to analyze social conversations and influencer ecosystem networks in real time.

Customer Insights: CMOs and Sales executive demand insights from all the big data coming from social, mobile, search, web traffic and back-end processes, so that they can deliver individualized, personalized digital experiences across all channels.

Analytic Training: A shortage of skills is urging demand for analytics training. It is expected that new offerings targeted at MBA and college level can help to prepare future business leaders.

In 2015, advanced and self-service analytics tools will be in demand. Also, there are various other predictions which are discussed below:

• Unlike analytics offerings designed mainly for data scientists and analysts predominantly focused on visualization, IBM Watson Analytics reduced manual efforts on steps like data preparation, predictive analysis, and visual storytelling for business professionals across data intensive disciplines like marketing, sales, operations, finance and human resources. - IBM

• While basic analytics provide a general big picture of data, enhanced analytics deliver deeper data knowledge and granular data analysis. - Gartner

• Advanced analytics is a top business priority, ignited by the need to make advanced analysis accessible to more users and widen the insight into the business. Advanced analytics is the fastest-growing component of the business intelligence (BI) and analytics software market and transcended $1 billion in 2013. - Gartner