Business intelligence is certainly a good area to be in right now. It is expanding faster than any other area of the enterprise application landscape. According to Gartner (an American information technology research and advisory firm), the business intelligence market (including data warehouses and CRM analytics) is growing nine percent per year. While it was worth $57 billion at the end of 2010, it will surge to $81 billion by 2014 and as high as $136 billion by 2020. Because analytics is the "combustion engine of business," organizations invest in business intelligence even when times are tough. Gartner predicts the next big phase for business intelligence will be a move toward more simulation and extrapolation. Gartner surveys show most users still focus on measurement of the past, with only 13 percent of users making extensive use of predictive analytics. Less than 3 percent use prescriptive capabilities such as decision/mathematical modelling, simulation and optimization. "This trend is changing as organizations express an interest in increasing their use of advanced styles of analytics," said Sallam (analyst at Gartner).To know more go to:

http://www.enterpriseappstoday.com/business-intelligence/gartner-taps-predictive-analytics-as-next-big-business-intelligence-trend.html

The biggest fallout of the big data revolution -- where every type of business gathers and analyzes data -- is a massive human resources shortage. Across the globe, thousands of data analytics jobs are not filled up because of a shortage of qualified manpower. Data analytics is not coding work but thinking work, described Dinesh Kumar, a professor of quantitative methods and information systems at the Indian Institute of Management in Bangalore. "The potential is huge, but we are behind in creating a talent pool," he said. Quality is a worry, and companies are finding it difficult to recruit top-class people, Kumar said. Data analytics as a job discipline became mainstream almost a decade ago, and the demand for trained professionals has been growing steadily since. Given India's reputation for the availability of professionals in varied disciplines at reasonable costs, global banks and financial services firms were the first to migrate their analytics work to India, followed by pharma and life sciences companies. Global retailers, consumer firms, logistics firms, consultancies, and engineering firms have all begun routing their data analytics work to IT services providers and specialized analytics service providers in India. In India, which has long been a hub for outsourced technology services work, the scarcity of analytics talent is particularly acute, as global companies send increasing numbers of data-related tasks to the country. To know more about this go to:

http://www.techrepublic.com/article/indias-high-demand-for-big-data-workers-contrasts-with-scarcity-of-skilled-talent/ .

The supply chain is a great place to use analytical tools to look for competitive advantage, because of its complex nature and also because of the prominent role supply chain plays in a company's cost structure and profitability. Data analytics is the science of examining raw data and drawing conclusions about information. It is used by many business houses to facilitate better business decisions and verify or disprove existing models or theories. Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressure and increasing customer expectations. There are also recent economic impacts such as rising fuel costs, global recession, supplier bases that have shrunk or moved off shore, as well as increased competition from low cost outsourcers. All these challenges potentially create waste in the supply chain that is where data analytics steps in. To know more about the role of data analytics in supply chain visit:http://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important .

Companies are using data analytics intensively and they should remember that to make money out of it and enjoy profits, they have to measure it.

At VentureBeat’s Databeat 2014, experts were of the opinion that companies are not using analytics to its full potential. Data scientists must be engaged with the organizational activities for providing support and insights, based on which the concerned employees can react. In the background are various social networks. By using the right social media tools, they can get a view about their operations from a real – time perspective. They can generate dashboards and graphs which will provide them valuable inputs in terms of revenues. Apart from this, it can be an effective marketing tool also.

All this will zero in the ultimate thing – increase the profitability. But, for implementing analytics, cultural change in the organization is also necessary.

Read at http://venturebeat.com/2014/05/19/some-simple-but-important-reminders-on-how-user-analytics-can-help-you-make-more-money/  to know what the experts told in the conference.

Big data is playing a key role in healthcare and several health institutes are seeking a solution that could bring the very latest drug interaction data right to patients’ bedside. Data analytics helps to analyze massive data volumes and conduct multiple drug studies, test and apply brand-new algorithms to quickly identify drug risk warning signals.

To read cases on how data analytics enhance healthcare follow http://bigdataanalyticsnews.com/10-big-data-analytics-use-cases-healthcare/

In the circuit-based telephony world, watching the status of a few thousand network nodes was a satisfactory answer to assuring network health. But today, the number of alarm points to monitor has scaled to the millions. No operator has the money to constantly monitor the performance issues of individual smart phone users. It is time for operators to get real and invest more in proactive analytics than in reactive alarms. What’s more, the gap between network planning and assurance has to be shortened. Why? Because the cause of today’s customer-experience problem is yesterday’s lack of good data for capacity planning.

During a recent conversation with columnist Dan Baker, big data architect Kelvin Hall, reveals about his firsthand experiences of the problems faced by network operations and big opportunities that await them through a greater mastery of analytics techniques. To read more, visit the following link:

http://www.billingworld.com/blogs/baker/2014/04/from-alarms-to-analytics-the-paradigm-shift-in-se.aspx

The trend towards larger data sets is due to the additional information that can be derived from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data. This is allowing better correlations to be found to spot business trends, determine the quality of research, prevent diseases, link legal citations, combat crime, and determines real-time roadway traffic conditions. Today, the applicability of Big Data analytics is not limited to only organizations. Big Data wings have established a longer reach beyond that sphere. Many apps are already in place to help people find the cheapest flights, improve their diets, even suggests how to become better drivers! From travel to shopping to health to civic life, big data got a role to play. Embracing Big Data analytics has already started paying dividends to the consumers. With more explorations, Big Data analytics is going to help each and every curve of consumer lifestyle in not so distant future!

A recent article posted in wall street journal by famous author Lora Kolodny, gives a detailed view on this subject. To read, click on the following link:

http://online.wsj.com/news/articles/SB10001424052702303369904579423383203100794

Data analysis is an important part of BFSI organisations. It helps to manage huge customer database of the organisations. It also automates the day-to-day transaction process. An article by Mohan Jayaraman, Managing Director of Experian Credit Information Company of India Pvt. Ltd. and Country Manager of Experian India describes that it is necessary to bridge the gap between information and its effective usage. For this, data analytics solution requires ability to manage and draw interferences from large amounts of data.

 For more information, please go through: http://www.informationweek.in/informationweek/perspective/287791/indian-banks-improve-customer-lifecycle-analytics?utm_source=rss&utm_medium=rss&utm_campaign=how-indian-banks-can-improve-the-customer-lifecycle-by-using-data-analytics