Enterprise Performance Management or commonly known EPM is a management field of Business Performance Management which considers the visibility of operations in a closed-loop model across all facets of the enterprise. 

Nowadays, big data analytics is helping EPM in factoring a lot more unstructured data than what was possible earlier, along with duly capturing customer sentiments and feedback. A second key impact of Big Data on EPM is that analytics will be a function not restricted to the IT team, but the wider organization will be able to deconstruct data with the use of easy-to-use analytics tools.

To read more, Visit the following link:

http://www.informationweek.in/informationweek/perspective/287755/impact-analytics-enterprise-performance-management

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/

Big data and analytics play a major role in any business. According to John Hagerty, program director of IBM, big data and analytics together can improve all the processes from management work to application in any business. Research revealed that with the proper use of these, any business can reach a limit where it can outperform its competitors by 75 percent.

For more information, please go through: http://www.zdnet.com/converting-big-data-and-analytics-into-real-results-7000026720/

Dashboards offer a unique and powerful solution to an organization's need for information. Nowadays it has become a very powerful tool to gather inner facts for decision making.  One can find various ways to create effective dashboards from a visualization and interactive perspective, but there is a need to understand the psychological aspect also. By taking into consideration the various psychological factors, we can develop more effective and informative dashboards. The three most important psychological factors are:

1) The curious nature of humans.

2) An eye for style.

3) The need for autonomy.

 To take a closer look at each point, Please follow this link: http://www.dundas.com/discover/article/the-psychology-of-dashboards/

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/

Well, nowadays retail banks are more focused in implementing data analytics techniques and models into their day to day decision making processes. Data analytics not only provide solutions to attract and retain profitable customers but also by the help of various tools and techniques like data discovery and visualization, it is possible to analyze the various aspects which are associated with customers. Retail bankers are trying to discover the relationships and correlations in large amounts of data using customer intelligence derived from analytics. Big data analytic enable them to track customer behavior and preferences to achieve higher level of customer satisfaction which definitely helps to achieve stakeholder’s wealth maximization. For more information, please go through the link: http://spotfire.tibco.com/blog/?p=22990

‘Big data’ is a combination of four ‘V’s: Volume, Velocity, Variety and Value, in structured/unstructured way. The data should be organised in a proper architectural form and then different analytical tools can be applied. The common analytical tools like agent-based modelling, neural networks, factor analysis, cluster analysis, time series analysis can be used to do proper analysis of the ‘big data’.

For more information, please go through: http://www.scientificcomputing.com/blogs/2014/02/big-data-analytics-continues-evolve

Movies! This word creates a taste of entertainment, a sense of refreshment among the minds of audience. We all would like to see movies that satisfy our genre-wise thirst. Also we prefer watching movies that includes our favorite stars or from our favorite directors or even sometimes we prefer watching movies from our favorite production houses.  don't we? Even, the ratings given by movie rating agencies and critics affects our decision about whether to watch a movie or not.

Now a days, our advantage is that we can predict how a movie will perform by using various analytics models.

Read more at

http://www.kdnuggets.com/2013/12/movie-analytics-india-dhoom-3-to-don-3.html

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/

The last five years, we have seen a massive upsurge of data; we have generated 90 percent of the entire world's data in the last two years!!! Why today analytics is so successful? Just because of availability of data? No! We have to admit the technological advancement we made through the last decade to analyze the available data, also the success can be attributed to the decreased cost of storage space. Twenty years ago, we had all the data analysis tools in place but data was scarce. Today there is a frightening abundance of data... But then what to do with this available data and how! Yeah we got the techniques, but we need the applicability mapping... Think about the applicability of analytics into the telecom sector, which represents an agile supply chain management ...These examples points to the tremendous possibilities that big data offer in telecom sector. But we must never forget the underlying secret: only blue-blooded telecom experts can usher in this exciting telecom future. Today's big buzzword is big data. Its companion, buzzword analytics, is also a big favorite. There are good reasons why this is so. 

For More Information Go To This Link:

http://www.business-standard.com/article/management/a-secret-about-analytics-114030200628_1.html

The numbers are coming in thick and fast but can big data and advanced analytics influence a team’s performance in the Soccer Premier Leagues?

Since the 1950s, when retired RAF pilot Charles Reep’s roughly-researched analytics led to the long-ball strategy, the football community has been enthralled by statistics. Today Premier League teams and their followers are being inundated with data as high-tech cameras capture every pass, dribble, free kick or touch of the ball while monitoring players’ xy coordinates every tenth of a second throughout the 90-minute match! What we call it as?

For more information check the following link:

http://knowledge.insead.edu/operations-management/beyond-moneyball-data-mining-the-premier-league-3155

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.

The traditional ways of handling data do not afford easy ways to handle large number of data(in terabytes) which can nowadays be easily solved by cloud computing.

The main advantages of cloud computing are:

1)      removal of the concept of limited storage infrastructure

2)      elimination of the need of building IT infrastructures to deal with obstacles

3)      reduction of the cost of infrastructures and charges only for the resources actually used

The main challenges for cloud computing are:

1)      shipping of hard disk drives to cloud providers

2)      data transferring through web

According to Gartner's Hype cycle, cloud computing has reached a maturity that leads it into a productive phase. This means most of the main issues with cloud computing have been resolved.

In recent years, data mining has been used widely in the areas of science and engineering, such as bioinformatics, genetics, medicine, and electrical power engineering. Several researchers and organizations have conducted reviews of data mining tools and surveys of data miners. These identify some of the strengths and weaknesses of the software packages. They also provide an overview of the behaviors, preferences and views of data miners. How about reaching a few inches deep into the applicability and usability of data mining which is the analysis stage of a typical KDD in terms of Education?

Please Follow this link

http://www.thehindu.com/news/cities/chennai/harnessing-data-mining-to-revolutionise-education/article5690365.ece