Big Data means different to different industry e.g. to computer manufacturers, big data analytics could mean demand for expensive servers and storage arrays; to the communications or cloud industry, the movement of data. But, for general people it means Big Data Analytics. The impact of change could be far-reaching and unpredictable. The budget spent on advertising via electronic, print and display media could costs double for data collection and analysis with impact which is immense. In the age of analytical marketing, we see firms collect more and more data in order to fine tune their analysis and increase competitive edge. To know more, follow Barry Schaeffer (principal consultant with Content Life Cycle Consulting)’s article link: http://www.cmswire.com/cms/big-data/look-before-you-leap-into-the-big-data-revolution-026873.php

The National Hockey League (NHL) is focusing on making a substantial investment in analytics to evaluate players' performance. Other than ticket pricing, analytics can be applied in other revenue stream like sponsorship investments by corporate partners. Using analytics in sports sponsorship provides answers to sponsors like why they are getting value by working with a sports organization. It also helps to state issues when a team or athlete is unsuccessful in competition. Thus, a wealth of new data is available to sports organizations. To know more, go through the article by Adam Grossman, Ben Shields, Irving Rein (authors of The Sports Strategist: Developing Leaders for a High-Performance Industry) at: http://blog.oup.com/2014/10/advancement-sports-analytics-business/

According to John Sculley (entrepreneur and the former CEO of Pepsi-Cola and Apple) a drastic change is taking place in marketing with the expansion of incredible new technologies like big data, cloud computing and numerous miniature sensors as well as mobile devices, making customers smarter. Nowadays customers value each other's opinion more than the producers'. With the beginning of a big-data marketing era, the prospects for entrepreneurs to disrupt and build companies have improved because technology costs have reduced. Read more at: http://www.entrepreneur.com/article/238363

Finding balance between data size and analytical modeling needs can be a problematic process in big data analytics. But it is essential for the success of big data analytics projects. The size of big data sources at social networking companies can obstruct analytics efforts. So, restraining the opportunity of an analysis by using data sampling techniques can be helpful. On the other hand, there are many businesses that lack the data needed to answer key business questions. For those organizations, development of effective analytical models can only take place after new data types are acquired and their analytics infrastructure is built. To know more, go through the article by Ed Burns (site editor of SearchBusinessAnalytics) at: http://searchbusinessanalytics.techtarget.com/feature/Balance-required-between-big-data-volume-analytics-needs

According to Dermot O'Kelly (Senior Vice President for Oracle UK, Ireland and Israel region) for the past few years the stage is being set for an analytics based future in which large volumes of valuable information can be collected and used to take informed decisions more efficiently. The rise of big data has been rapid. But very little emphasis has been placed on trying to understand exactly how big data can impact and improve our lives. Big data tools help in linking all information together and assess it from various standpoints at once in the hope of detecting new insights, to approach difficult questions from a fresh angle, or to process huge data sets very quickly. They also make the collection and processing of this data exponentially faster than before. Read more at: http://www.in.techradar.com/news/world-of-tech/Big-data-in-the-real-world/articleshow/42649169.cms

There is no privacy in the era of big data. Personal data is collected and traded and there are few ways to control it. "We're being monetized in essence. We are being mobilized as products with inducement of the services of we use such as Facebook and Twitter" says Rob Livingstone, a fellow of the University of Technology and the Head of a Business Advisory Firm. However, major problem that regulators are facing is - how they can regulate the collection, storage and trading of personal data on the internet, when all of these activities, and corporations, operate across multiple continents and jurisdictions. Read more at: http://analytics.theiegroup.com/article/53a4371c3723a8398400014e/Little-Privacy-In-The-Age-Of-Big-Data

Information available about consumers on the web is enough to scare marketers. There are large rewards for those who confront and harness big data. Big data can create problem for brands. Information collected from large, complex data sets weblogs, social media, smartphone analytics and even medical records is difficult for brands to manage and process within traditional database systems. According to a report from the McKinsey Global Institute, Big Data is the next big thing for innovation, competitive advantage and productivity. But, some companies are missing this opportunity because of a lack of data management expertise. Retail is one industry that has a great potential for big data. Customer transactions (on & offline), conversations and intentions can all be brought together so that brands can get ideas how to reach potential consumers. Read more at: http://analytics.theiegroup.com/article/53a2f6693723a807f3000029/Big-Data-Embracing-The-Elephant-In-The-Room

According to author Shreya Sharma, with Big Data becoming an essential part of an organization, it is getting harder to balance it with data privacy. Marketers should be clear about the data they are collecting and make sure that data storage and security infrastructure are safeguarded, otherwise it can have serious effects on the company as most consumers expect a company to protect their personal data, and their consuming behavior depends on this. It is therefore crucial to bear a high level of awareness with regards to the significance of data privacy and protection. The responsibility should be seen as norm and not just be restricted to people who are directly involved in mining big data. To know more, please follow: http://analyticsindiamag.com/in-action-how-companies-should-follow-a-data-centric-security-approach/

Big data enables understanding of complex customer sentiments and intent which improves service management. Today it is easier to process customer sentiments and intents through social media and develop social customer relationship management or social CRM. To make this effective it is important to capture the natural language knowledge and rapidly and securely making those insights available to tye best pay off channels. 

This podcasts bring together customer analytics services provider Attensity, with its natural language processing technology, and HP Vertica with Big data analytics capabilities to explain how effectively listen to social Web and rapidly gaining valuable insights and actionable intelligence.

Some participants are Howard Lau, chairman and CEO of Attensity, and Chris Selland, vice president of marketing and business development at HP Vertica. The discussion is moderated by Dana Gardener, principal analyst at Interarbor Solutions.

more at: http://www.crmbuyer.com/story/80826.html

Big Data is about making something out of enormous and high speed structured data as well as unstructured data, but most organizations do not have a business case for the use of Big Data and invariably, a not so conducive culture to leverage Big Data technologies. The main area of focus in India seems to be-Real Time Reporting on Transaction Systems. Through the partitioning/ clustering, distributed computing and in-memory processing methods, Big Data can run high quality real-time reports, with the ability to drive additional queries. But it will be not be the best use case for Big Data. If we focus on this use case, Information Technology will just end up being a cost center. Big Data investments should address either the fraud prevention story that helps the bottom-line, or the customer offer story that helps the top line of a company. The immediate need however is to get the data fixed to achieve the goal. Data quality continues to remain a huge challenge across more than 80 percent of the mid and large organizations. Read more at:

http://www.informationweek.in/informationweek/perspective/297428/companies-artists

Ever since the video gaming industry has entered the online space, this fast-paced industry is almost bursting. Bringing in about $20 billion of revenue a year in the U.S. market alone, this industry is now scaling new heights with vast data out-pours and advances in big data analytics. In the world of online and offline video games, joystick movements and every interactive step is a source of valuable data-points, which can deliver fascinating solutions for enhancing gamer experience and increasing revenue streams. The world of games is like any other form of entertainment-it requires addictive rewards to make the gamers come back again and again. According to reliable market reports, a large, video-game manufacturer has the potential to generate around 50 terabytes of data each day. In US, the gaming industry is certainly bigger than the movie industry in terms of revenue generation. Now that this prolific industry is rapidly embracing big data technologies, the industry is expected to make waves in novel methods of customer engagement, optimized and targeted advertising, and enhance the end-user experience.

Read more at: http://www.mapr.com/blog/big-data-revolutionizing-video-game-industry#.U-d_4vmSxvM

Malware and cyber-attacks have become increasing concerns among companies. Many of them struggle to predict and mitigate threats, which can spring and evolve quickly. Companies also have some concerns about the physical security of their infrastructure. The result is that they are in search of more comprehensive resources to address these challenges. Big data analytics, particularly when they are coupled with machine learning, represent a logical solution because it allows companies to consider multiple threat scenarios and determine the best response. 

In today’s complex network environments, Advanced Persistent Threats (APTs) and other cyber threats eradication may be accomplished by getting intelligence from data providers. 

For these cyber threats, appliances should be monitoring threat feeds from trusted providers for indicators of compromise (IOCs), including big data feeds like domain name systems (DNS) feeds, command and control (C2) feeds, and black/white lists, in order to correlate and hunt threats in a data set and recommends six steps to combat the potential threats.

Read the article at: http://www.darkreading.com/analytics/6-tips-for-using-big-data-to-hunt-cyberthreats/a/d-id/1278970

Big data has been big news in the travel industry for a few years now. It offers the chance for travel companies to increase the number of sales and improve the travel experience of customers. While big data is a vast, complex challenge for many organizations, it is one of the key factors driving the evolution of the travel industry today and for the foreseeable future. Airlines, hotels, cruise companies, travel management, railways and travel agencies have an opportunity to improve their business and the customer experience by effectively handling the big data at their fingertips. That's not to say it is easy to collect, identify and analyze all of the bits of disparate data types that comprise big data. Travel companies can make better decisions based on the data aggregated from their customers to personalize services like travel booking to make them easier to navigate. For many years, CRM systems have allowed companies to create relevant, targeted marketing campaigns. Big data, however, uses customer information to create a truly personalized service. It allows travel websites to recommend a specific hotel to a specific user based on their previous holidays, requirements and preferences.

Read more at: http://www.forbes.com/sites/centurylink/2014/04/30/how-big-data-is-transforming-the-travel-industry/

Proficiency in Big Data provides a competitive advantage to banks. Banks too often depended on traditional technologies such as aggregation and normalization of data which resulted in several weaknesses like lack of flexibility in responding to upstream and downstream data changes. Data lineage may be lost after aggregation and summarization and data governance is likely weakened when several constituents retain responsibility for an extended, multi-stage data flow. These weaknesses are detrimental to the success of big data initiatives. So a new approach is required.  Big data represents a new way that banks can interact with and leverage their data. As a result, banks need to shift the paradigm for designing, developing, deploying, and maintaining big data solutions with new approaches to data storage (e.g., NoSQL databases)  and maturity of distributed-computation software frameworks (e.g., Hadoop). The approach to Big Data implementation also needs to change through rapid, iterative, and incremental deployment of solutions in a way that aligns well to the speed at which the underlying data are measured, understood, and parsed. This will take banks to an acceptable level of competency and capability. Read more at:

http://www.informationweek.in/informationweek/news-analysis/297426/mean-banks

Huge amounts of data are being created with every passing day.The UN has called for a 'data revolution' to come up with new development goals - so that sustainable development can be better practiced and can be integrated into making decisions and also provide transparency. But finding out trends hidden within data takes skill - and so the question is whether jury is out as to whether nations and development organizations have the capacity to interpret the so-called 'big data' by themselves. The question is how best to make up the ground. The problems faced in implementing Big Data involve lack of expertise to train staff to use big data, and also awareness of the technology needed for analysis. Lack of money is another concern, particularly in developing countries. If governments do wish to see big data used for development, their best bet could be to allow the private sector to do the groundwork. In many developing countries, problems of patchy internet connections, intermittent power supplies and poor reach of high capacity cables are being faced. But the digital divide challenges may be circumvent by other sources of data, for instance, call data records (CDRs).The barriers facing big data becoming a useful tool for development are numerous and great. But, they are not insurmountable. There is reason to believe that big data can fulfil its promise in the years to come. Read more at:

http://www.scidev.net/global/data/feature/obstacles-big-data-development.html

Big data analytics is increasingly playing a role in the fight against crime. Publicly shared information combined with data from local authorities, social services and intelligence gathered by beat officers is helping police forces around the world spot trouble before it starts. It helps the police be much less reactive, and slowly starts to reveal the real trouble spots and troublemakers in a neighborhood, estate or street. When information like that becomes clear, the police can do something about it long before anyone dials 999. And that counts for people as much as it does for pubs or clubs. Law enforcement is finding new ways to use technology and big data against crime. CCTV cameras are no longer impotent. They are commonly used in police cars and carried by officers to create a permanent digital record of everything going on around them. 

 This will make it harder for criminals to commit crimes. In recent years we have witnessed criminality moving off the streets with a huge increase in the amount of credit card and online identity fraud. But even there new big data algorithms are being developed to detect fraudulent behaviors in real time.

Read more at: http://smartdatacollective.com/bernardmarr/199521/big-data-analytics-and-criminals

This is the age of Big Data and the amount of data surrounding us is actually huge. The rate at which new data is created almost doubles every month. Some examples to show the trend of data driven decisions in almost every sphere are as follows. The big business of sports has led the charge. We're using our smart phones, watches, and other wearable devices to gather data about ourselves to better understand fitness, nutrition, health, and behavioral tendencies. Local and national governments are contributing too with significant movements towards transparent publication of data on websites. The approaching Internet of things -- as governed by new devices such as the Nest Thermostat, Quirky devices, or even the Waze service that uses consumers' GPS-enabled smart phones to gather information --have such companies as GE and Google making substantial investments based on their potential to both generate and find value in big data. Though there exists so much of data some companies still face problem in dealing with it due to existence of some challenges. Read more at: http://tdwi.org/articles/2014/07/08/turning-big-data-into-smart-data-1.aspx

Results show that over 75 percent of the organizations have gained big payoffs with the application of big data and analytics in their organization. Also the Return on Investment (ROI) has increased within six months of application. Certainly executive support as well as their involvement in analytics is vital to value creation since in organizations with low levels of executive support, analytics implementations are hampered by lack of funding, resources and follow through. Besides, strong governance and security are important in instilling confidence in the data, and trust is necessary. Also the direct factor which has implication on organization's value is the trust between people within an organization. This is not trust in the quality of the data but the old fashioned trust that is earned by getting to know someone's character and what they are capable of delivering. The level of trust - a belief that others will do a competent job, deliver on promises and support the organization's best interest - among executives, analysts and data managers significantly impacts the willingness to share data, rely on insights and work together seamlessly to deliver value. Read more at: http://www.informationweek.in/informationweek/perspective/286293/roi-about-trust

Big data is a key infrastructure in the Internet of Things (IoT), but it's far from the only piece of the fabric. In the coming global order, every element of the natural world, and even every physical person can conceivably be networked. Everything will be capable of being instrumented. If you think that the world of driverless cars, robots carrying out maintenance in hazardous locations like oilrigs, or advertising that reads and responds to individuals' unique facial expressions sound like science fiction. As these trends come to fruition, each of us will evolve into a walking, talking, living beneficiary of the Internet of Things. These are all developments happening today and they're prompting a new exciting phase in analytics that needs to be addressed now. Those that embrace data will be more likely to be surfing on top of the wave of creative destruction, instead of having it crash down on top of them.

Read more at: http://blogs.computerworld.com/business-intelligenceanalytics/23447/internet-things-what-it-and-what-does-it-mean-analytics

Data is more than just power. Organisations across all industry verticals are upgrading their data management systems, investing in new resources, and using their rich databases to streamline the practices of their departments. Indeed the message from experts is clear: organisations that fail to adapt and evolve to meet the emergence of big data, face the prospect of falling behind. As with any phenomenon, however, there are lessons to be learnt. 

The way data is being used in sports is a poignant example. Moneyball, the popular book inspired by Oakland Athletics manager Billy Beane, explained the core philosophy of the manager’s vision for the baseball team: using statistical analysis to maximise player acquisition and performance with a low budget. 

The Moneyball philosophy had huge ramifications for the sporting world. People started adopting variants of it in all sports – from soccer to basketball to football. Arguably the most noticeable application of Beane’s philosophy was by Andy Flower, the former England cricket coach. Flowers was known for his admiration of Beane’s work, and he too would use statistical analysis to not only determine who would be on the field but also what decisions players should make once they were selected and enjoyed notable victories also. Both of them have stood by data analytics and the benefits it can bring. Yet, what is often untold is that data was both a virtue and a vice for both men.

His 5-0 defeat at the Ashes last year was one of England’s most disappointing performances to date. As commentators suggested, it was a classic case of overreliance on data, replacing intuition with numbers, and allowing data to dictate rather than inform. Flower ultimately got the balance between trusting people and numbers wrong. He was in good company, those who thrive will not be those who use data most—but those who use it most smartly. But data is emphatically not a substitute for intuition and flair - either in the office or on the cricket field.

These instances of sports analytics are particularly relevant for organisations looking to add big data analytics to their existing operations. The example of Beane and Flower show how data does not have all the answers, and relying too heavily on it can have devastating effects.

Read more at: http://www.espncricinfo.com/magazine/content/story/724435.html