Companies take efforts to develop all-encompassing voice of the customer (VOC) programs. The success of these programs is dependent on the quality and variety of data gathered from customers. Increasingly, companies are gathering customer feedback from structured as well as unstructured data. For companies establishing a VOC program, unstructured data seems overwhelming. Because of this, companies may avoid analyzing it. Capturing and analyzing unstructured data can be daunting to VOC program managers. Automation is an important step in successfully optimizing the value of unstructured data in a VOC program. Unstructured data creates excellent insight into the underlying drivers of loyalty, and it's vital that organizations make use of their available information. The companies that listen in the right places, using unstructured data to destroy structured, solicited feedback, and taking action accordingly, will have a huge advantage over their competitors. Unlocking the capacity of unstructured data is manageable if taken one step at a time, and the results will be well worth the effort. Read more at: 

http://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/Unlock-the-Potential-of-Unstructured-Data-for-a-Successful-VOC-Program-97918.aspx

According to a recent survey by the International Data Corporation's program director, Greg Girard, just 14 percent of consumers could be considered "privacy spenders”, 47 percent are "privacy hoarders" and 39 percent of consumers are "privacy value seekers,". Both privacy hoarders and privacy spenders are comfortable with retailers using online purchase data for serving them better. They become cautious when it comes to retailers managing their online behavior via social media or other Web activity. Since different retailers attract different demographics, retailers need to know how their customers feel about privacy. Consumers will protest if they feel that the information they are sharing to retailers is not protected. “Trust is not just individually built with a retailer, but affected by these more "external drivers," Girard explains. The challenge will be "how well retailers individually, and as an industry, exercise the responsibility they have to safeguard their customers' data and to use it correctly to deliver value," Girard underscores. Read more at: 

http://www.destinationcrm.com/Articles/Columns-Departments/Insight/Are-Consumers-Willing-to-Share-Private-Data-97716.aspx

Research Company Gartner suggests that there will be 4.4 million big data jobs available in the next two years. Everything is moving towards data: big data, mobile datasets.  Creating and implementing an analytics program requires four steps: 1) Defining your metrics and developing a plan 2) Collecting the data 3) Developing reporting features and capabilities 4) Ongoing analysis and implementation. Understanding each of these core components enables a company to make the right investments at the right time. Corporate data culture is a spectrum that can often be classified as follows: 1)No or limited data 2)Basic data 3)Deeper data that's soiled or controlled 4)Democratic data access. The idea is that your strategy should take the following points into account: 1) Data collection and reporting. 2) Analyzing the data, articulating the implications for business. Useful data tracking comes down to evaluating: 1) who is coming to your site, and what are those people doing once they get there. 2) What channels are driving buying customers? 3)Who is converting 4)What conversions are deepening relationships 5)What conversions are driving revenue 6)Who is buying multiple times 7)What's your lifetime customer value 8)What are your churn rates. Any solid analytics plan will take your business model into account and develop a set of metrics that maps to your unique needs and buying funnel. Read more at:

http://www.forbes.com/sites/jaysondemers/2014/02/10/2014-is-the-year-of-digital-marketing-analytics-what-it-means-for-your-company/

Insurers are today trawling big data about customers’ finances and other sources. The development shows how access to big data is revolutionizing the insurance industry and companies are accessing a wide range of information on everything from financial probity to shopping habits of the customers to determine the risk premium for individual customer. One official of AA insurance company said that the winners in the insurance market will be the ones that have got the data insights that others don’t have. It could be supermarkets, banks or social media companies. However, ultimately the big data trend means some policyholders will pay more than others not for the climate change only but also for insurers to know more about the risks posed by particular properties. But, as with the sensitive data some companies also go far beyond what customers would expect them to do with it, customers should be given the option to opt in to such analysis than allowing them to opt out. Read more at:http://analytics.theiegroup.com/article/53c7a5c03723a8014f0000cd/Insurers-Trawl-Big-Data-For-Clues

Today,banks are using analytics to control frauds in electronic payments. Private banks such as HDFC Bank have implemented analytics software. The thing is that the out-of-the way transaction would decline if one fails to respond to a phone call or message immediately after the transaction. There are two kinds of fraud detection in payments- One is during the transaction, and the other is using analytics to identify suspicious transactions based on past behaviour. Banks are now specializing in the analytics part. According to an official of an analytics software company that provides banks with software to detect frauds, the software can be used to personalize services, like ATMs, for customers depending on their preferences. Read more at:http://timesofindia.indiatimes.com/business/india-business/Banks-use-analytics-to-check-fraud-in-online-payments/articleshow/38347410.cms

Successful companies in 2014 are expected to take Big Data Analytics and utilize it for growth and competitive advantage. Experts discussed how to use data strategically for a strong analytics culture at the webinar "Fine-tune your analytics strategy for 2014". According to Stephen Sharpe, Director of Global Strategic Analytics of Johnson & Johnson, companies need to start working on a cloud based system to integrate and broader integration and training across the various sectors to share best practices. According to Larry Seligman, VP, Advanced Consumer Analytics, Inter-Continental Hotels group, companies need a new definition of data integration and they need to learn how to value projects and programs and quantify the things which were previously not quantifiable. According to Mazhar Hussain, Leader Big Data Practices, HP, gives insight on the importance of analytics as a service. Mid-sized and small customers will take great advantage of analytics as a service which is going to take up big stream and it is important to have the right kind of strategy implemented in the company. Read more at:

http://www.modernanalyst.com/Resources/News/tabid/177/ID/2915/6-things-to-focus-on-in-2014-analytics-strategy.aspx

Those in the managerial level want data to back up assumptions. We can’t formulate decisions on a raze sensation, or what we recognize our rivals are doing, or what we believe our consumers desire. A lot of time companies have no perception of their purchase. So to ignore taking bad decisions, data is used to back it up. Analytics is checked to see what public are doing. So what are business analytics and how do we acquire them? At this level of analytics we need to know our rivals, and what their digital outlets are. We require a digital fingerprint of the rivalry, and we should also have a good knowledge of our market. What people are wanting and giving the services we propose. Information of the industry is very important to make a plan to assess the true data, and then make an approach that originates our expedition  . Read more at:

http://www.socialmediatoday.com/content/whats-going-your-industry

The desire to be mobile and make a mark is not new to us. Today we use GPS for wherever we go and communicate on a variety of devices. Big data is the phenomenon which has helped in generating and sharing information. The difference between data in ancient times and now is that before, only humans created and collected data whereas now with the rise of sensors and other technology that creates and collects data. However, the big thing about big data is the self-organization i.e. without human intervention and awareness, data is organizing itself.  But, this leads to a big question that-Are we playing with fire? With big data revolutionizing, there comes a new responsibility, because the purpose of managing data is not to predict the future but to shape it which is a huge responsibility. However, revolution hasn't stopped. Changes took place slowly in the evolutionary manner. Using technology that provides insight into data, today's business leaders have a unique opportunity to make thoughtful decisions that will have long-lasting impacts. But along with all this, disruptive changes are happening in every industry around the world which increasingly making us concern about whether today's leaders rise to the challenge of shaping the future in a responsible way or not. Read more at:http://analytics.theiegroup.com/article/53c3f6413723a87216000156/Shaping-The-Future-With-Big-Data-Are-We-Playing-With-Fire

The massive stress, the high expectation, nation’s passion and panic on the shoulders of an enthusiastic but defective Brazilian team. They trapped under the pressure, but there was more to this pressure, or faulty strategy and player’s selection, or inexpert positional play, or a first class German team filled with efficient passers. First-half goal storm saw Die Mannschaft 5-0 up, Miroslav Klose gave his record-breaking 16^th goal at the finals and the brutality continued into the second period with Schürrle.  Mesut Özil missed to make it 8-0, moments before Oscar scored a goal in the final minute of the first semifinal of World Cup 2014. Germany place up in 4-1-4-1 changing from the 4-3-3 they begun with. David Luiz and Dante saw the ball early in deep areas, but with no one to pass and kept missing. Germans moved with instability, interchanges outside the box and played generously, passing football. Read more about this analysis at: 

http://outsideoftheboot.com/2014/07/09/world-cup-tactical-analysis-brazil-1-7-germany-germany-run-riot-to-trounce-brazil/

Cloud, social, mobile and big data technology have been primarily viewed as the drivers behind Customer Relationship Management (CRM). According to a Gartner report, they are now being joined by an emerging driver- the Internet of Things (IoT). According to Joanne M. Correia “CRM will be the heart of digital initiatives in the coming years”. In the report Gartner views that ioT, where sensors connect devices to the internet, create new services previously never considered. Gartner forecasts CRM market to reach $ 23.9 billion this year, with cloud revenue accounting for 49 percent. IoT joins cloud, social, mobile and big data to spur a critical need for more operational CRM, according to Correia. According to an article in Information Week, Gartner predicts that in 2020, there will be 7.3 billion smart phones, tablets and PCs in use- but about 26 billion IoT devices. IoT is driving CRM investments, because the use of cloud- connected intelligent devices is creating new business opportunities for marketing, sales and support executives. Read more at:

http://www.cio.com/article/2453781/big-data/big-data-as-a-driver-for-crm-investments.html

The clinical data analytics market has shifted its focus on new payment models, electronic health records. As a result many healthcare groups are looking to analytics solutions to reduce the risk of the patient population. According to a recent Frost and Sullivan market analysis, clinical data analytics is poised to grow at a CAGR of 37.9 percent from 10 percent, in 2011 to 50 percent adoption by 2016. Despite strong market growth it is not smooth for data analytics. Managing such complex and extensive data is a difficult task. Such analytics can be very expensive. Claims based analytics is still very much a reality. Many analytics vendors have tried to align their brand with PHM by any means necessary, which has increased competition making it difficult for them to differentiate in the market. Also researchers have found a very immature buyers' market, which has raised the doubt as to how far the capabilities of analytics solutions will bear results. Read more at:

http://www.healthcareitnews.com/news/clinical-data-analytics-get-red-hot?page=0

Could business analytics provide a solution to the pressures faced by the American healthcare system? As in the case of Mount Sinai Medical Centre in Miami, business analytics generated a very high payoff because it involves efficiency driven, intensive, statistical exploration of an organization's data. In the above case, it determined that the center was overpaying for the pacemakers. At the HIMSS conference, we witnessed plenty of startups peddling immediate business analytics solutions to healthcare organizations. Eventually healthcare organizations will adopt business analytics, but the process will take several years for the following reasons: Lack of Compatibility between Systems as introduction of business analytics and then integrating it with existing infrastructure is challenging. For business analytics to get to market it needs to undergo trials in one or two hospitals. Organizations require their softwares to be customized. So suppliers require time. Staff members need to be trained on how to use the software correctly. All these are time consuming. Hospitals should approach their management strategy from a higher level, planning systematic solutions. Read more at:

http://www.informationweek.com/healthcare/analytics/business-analytics-will-help-healthcare-just-not-overnight/a/d-id/1279087

Importance of Big data and Talent Analytics is a much discussed topic for the last couple of years. One just has to know how to use talent analytics as it can do a whole lot of difficult task like quantifying different behaviors, skills, intelligence, and mindsets of a HR. Talent analytics uses data in management decisions like talent acquisition, retention, placement, promotion, compensation, and succession planning. By analyzing the skills and attributes of high performers in the present, it enables organizations to build a template for future hires. Advanced software algorithms can identify talent and match it to an organization's needs. Some intangible aspects like social skills, flexibility, emotional intelligence, initiative, attitudes are now measurable- thanks to talent analytics. Along with these, new mobile apps also make talent searches a matter of anytime and anywhere. However, as it's still growing, Gartner predicts that the market for Big Data and analytics will generate $3.7 trillion in products and services and generate 4.4 million new jobs by 2015. Read more at:http://analytics.theiegroup.com/article/53b2b9c13723a81923000046/Talent-Analytics-A-Crystal-Ball-For-Your-Workforce

Today big data is able to change the way real-estate professionals, buyers, sellers and even banks think about transactions involving property. Companies, promoting services that plug consumers into big data real estate information which gives a better education and insight.There are five key ways through which big data is changing the game of real estate business. They are- 1. Big data helps to democratize data for the real-estate customer. Companies such as Zillow combine big data with real estate and offer services like- Mining census information, the results of consumer surveys, listings of homes for sale and rent etc. 2. Big data is not only providing new information to consumers but also new ways of looking at developments and community planning. From that gathered information, real-estate developers can learn what kinds of spaces work best in terms of tenant health, energy efficiency and other points. 3. Institutions like banks are also able to plug into big data resources. 4. As an expert real estate advisor knows recent sales, incentives, and inside secrets to getting the best deal, buyers should have to be careful and should start property searching with the help of big data sites. 5. Finally, Big data let the professionals know what visitors are doing when looking for real estate online and they adjust their paid and organic efforts based on this data daily. Read more at:http://analytics.theiegroup.com/article/53be79af3723a84f1000003f/5-Ways-Big-Data-Is-Changing-Real-Estate

The launch of big data analytics has brought confidentiality concerns as a rising subject for the customers. Obtaining data is important in order to improve its ability to connect their business to the target consumer by analyzing customer behavior. Casting uncertainties from the consumers on how entrepreneurs use their personal information while collecting data endanger the trust that every business enterprise should build. The consumers are aware of the value of their private data. To a reasonable extent the consumers are willing to share. Privacy is more important to the consumers and they expect marketers to give it owing admiration. Businesses that do not respect the privacy of their customers will be likely to mislay their faith. some strategies to be taken to re-establish the trust of customers between business and the customers. Many customers are prepared to share their personal data if they are guaranteed of their privacy. Read more at: 

http://www.socialmediatoday.com/node/216026

The performance metrics for ads shown against brand and generic queries can differ majorly, many advertisers choose to analyze these two categories separately. Many advertisers with paid search campaigns advertise on queries mentioning their brand (e.g., “Motorola smartphone” for Motorola) and also on generic searches (e.g., “smartphone reviews”). A new feature is introduced, that automatically identifies brand-aware paid search clicks tracked in Google Analytics,to make analysis of brand and generic performance easier. It involves a combination of signals (including the click through-rate, text string, domain name and others) to identify query terms showing awareness of the brand. Back in 2012, George Michie from the Rimm-Kaufmann Group, a leading online marketing agency, called analyzing brand and generic paid search together “the cardinal sin of paid search”. To know more go to:http://analytics.blogspot.com/2014/06/segmenting-brand-and-generic-paid.html

Analytics for Small Medium Businesses (SMB) today, is a much discussed topic. SMBs face the challenges of effectively using analytical tools to gain precious business insights from data generated. Today markets are able to provide solutions to SMBs which were costly before and this was made possible by the advent of Qlikview, Tableau etc. in Analytics sector. SMBs are realizing that analytics can help them understand customer preferences, expand their market share, cut down cost, increase efficiency and give them a competitive advantage even against the big players. Moreover, with the advent of new technologies like cloud, social media and open source platforms like Pentaho and Hadoop, the requirement for big infrastructural set-up and capital cost have been reduced considerably. The success of Analytics tools depends to a large extent on collecting and managing data and in such case ERP and CRM tools are a must for success. For successful implementation of analytics tool, SMBs need to assess the external market as well as their internal systems and processes. However, SMBs will soon be able to adapt their systems to bring in the external big data from social media like any other big enterprises and hence make their analytics more robust. Read more at:http://www.informationweek.in/informationweek/perspective/296888/value-analytics-businesses

Many companies are discovering that big data can also be used for security by offering a broader view of risk and vulnerabilities. In today's complex network environments, Advanced Persistent Threats (APTs) and other cyber threats can be wiped out by leveraging intelligence from data providers. Six ways for using big data to wipe out cyber threats include DNS feed which can provide lists of newly registered domains, domains commonly used for spamming and newly created domains, which can be incorporated into black and white lists, C2 systems which provide black lists of IP addresses and domains, threat intelligence which may be used to help determine if an address is safe or not, network traffic logs help to log all of the networks traffic  or even just parts of it, honeypots can be effective in identifying malware targeting a particular network and finally data quality is important to call attention to the data feed itself. By utilizing big data organizations can create more robust threat and risk detection programs. Read more at

http://www.informationweek.in/informationweek/news-analysis/296971/tips-wipe-cyberthreats/page/2

 A McKinsey study last year stated that companies using Big Data and data analytics effectively show high productivity rates and profitability. But implementation of data analytics is challenged by lack of skilled manpower. Recently many B-schools are stepping up and have emphasized on advanced analytics techniques such as 'Clustering', however very few institutes teach Big Data technologies like 'Hadoop'. The hiring companies which look for data analytics include digital companies, ad agencies, and IT companies and so on. Internationally a vast number of management schools including New York University, University of Texas at Austin, Georgia Tech have had Analytics certificate programs for the last five years or so.Read more at

http://www.business-standard.com/article/management/learning-the-abc-of-big-data-114062900615_1.html

Today, a smartphone app would tell one what to eat, how much to eat, when to visit a doctor etc. based on analysis of medical research, medical history of that person, family medical records etc. Quality of our health will be increasingly improved by the quality of data and the ability to bring it all together. The growth of big data in the health industry will only take place once privacy concerns are addressed because health data, unlike the marketing data, is lot more personal. Big data analysis is already being used to make diagnoses in some hospitals. In Canada, Toronto Hospital uses big data to detect blood infections in premature babies. It could save the American health care system $300 billion per year and the European public sector €250 billion, according to a 2011 report. Doctors today are using Watson, IBM's supercomputer, to keep up with health research and to leverage the latest breakthroughs. Big data analytics also could be used to follow epidemic outbreaks. For example, Big Data enabled doctors and scientists to learn so much about the Severe Acute Respiratory Syndrome (SARS), and how quickly it spread, within weeks of the World Health Organization's initial warnings. In such case social networks and mobile data are used to ensure the delivery of real-time information. Read more at:http://analytics.theiegroup.com/article/53b6b4c43723a83b82000035/Big-Data-Could-Help-Your-Health-If-You-Let-It