A report by McKinsey & Company talks about how usage of data analytics is transforming organisations. It also conveys that information on niche segments can also be important.

For more information follow

http://www.forbes.com/sites/mckinsey/2014/01/15/new-ways-for-turning-data-into-dollars-now/

Mark Smith, CEO and chief research officer of Ventana Research, talks about how Location Analytics market is emerging to provide better business insights. With the help of this technology, companies can save time and money, decrease business risks and increase competitive advantage.

For more information follow

 http://www.directionsmag.com/articles/new-generation-of-location-analytics/311467

An article by Omar Zaibak, Head of Marketing at VoiceTrust specializing in B2B demand generation, talks about the latest trends of the call center industry which will help to improve customer experience. Some of them are – Social Media, Voice of the Customer, Cloud Migration, Voice Biometrics.

For more Information please follow

http://www.voicetrust.com/blog/top-10-call-center-trends-2014/

With the advancement of technology, business analytics helps to analyze huge number of data and create predictive models. It also helps in the areas like data mining, statistical sampling and forecasting. The main objective of business analytics is to cluster data from different systems into a common storehouse. Using Business Analytics, smart enterprise set up can be built that benefit businesses to combat the volatile demand.

For more information please follow 

http://dreamfireinteractive.com/industry_insights/accelerating-business-analytics

Data Analytics is very significant for the insurance industry helping to reconstruct the processes. Around 74% of the insurance sector is creating aggressive dominance for their companies by using analytical tools. To challenge and succeed in this charismatic environment, insurers must amend the value of big data. While the industry has upgraded in evaluating the structured data linked with their products but the unstructured and semi-structured information is yet untried. By focusing on the appropriate expertise, the insurance companies will be on the correct path to contend and bloom globally.

For more Information please follow

http://www-935.ibm.com/services/us/gbs/thoughtleadership/big-data-insurance/

Data Analytics is used in an ample number of ways to achieve a competitive advantage over other businesses. The various areas are - Big Data and Information Optimization helps in determining an organisation on how they can apply the present analytical access patterns and skill sets though it is still critical to audit the interaction between the analytical assets and core database system. Visual Analytics and Data Discovery gives guidance in finding a trend in the data set by developing various hypotheses and visualizing the complexity of the diverse data set. Companies need to inspect on different patterns and accord in the data for future benefit using Predictive Analytics. Right Time and Real Time Analytics are used to grasp on how customers are handling data analytics for managing industry. 

For more Information follow 

http://tonycosentino.ventanaresearch.com/2013/03/11/the-four-pillars-of-big-data-analytics/

To find the best tools and techniques for appropriate human resource selection must be the prime focus of a HR manager. The enhancement of the recruitment process can be attributed not only to the social media techniques but also to the data analysis, redefining recruitment. Data analysis helps in making accurate decisions faster which ultimately leads to a proactive business. The employee turnover can be reduced by analysis of the proper reason using sentiment analysis. Predictive analysis helps in eliminating the guesswork factor.

For more information please go to

http://theundercoverrecruiter.com/big-data-recruiters/

Predictive analytics is the next generation of analytics which is important for the engineering and construction industry. Data makes up the building blocks for analytics. But instead of using data analytics to make sense of the past — to understand what we have done and what trends we can pick out from our past behaviour — predictive analytics uses data to predict what is likely to happen. When you use predictive analytics, you let the data tell you the answers that you may not be aware of; that are not obvious to you.  You’re looking at data you may not be collecting yourself. Target is pouring over data and finding the themes, patterns and relationships to build predictive models to achieve business outcomes.