The Sports Industry is evolving. With the requirement to be accurate and the presence of data far beyond what humans can perceive and make collective sense of, there has risen a need to be able to observe, process and evaluate the actions of both teams. With the availability of large amounts of data to train the system, we can now accurately predict and develop strategies for the team. Machine learning is already being used to understand the conservative strategies of away teams at the English Premier League. It can also be applied to predict the behavior of individual players such as cricket bowlers in the IPL. Researches are also working on ML Algorithms to identify talented sportsmen based on their psychological characteristics and practice history. Read at: http://www.science20.com/the_conversation/machine_learning_and_big_data_is_changing_sports-155628

Advanced analytics is considered as a game changer in all industries today. The benefits received from its application are tremendous. These benefits can also give the user firms – a competitive advantage- which further gives them a lead in their industry. Gavin Seewooruttun, in his article at abc.net, has listed five top applications of advanced analytics, that will prove to be a winning element for its users. They are:

• Gaining the whole customer view
• Customer micro targeting: upselling and cross selling
• Customer micro targeting: acquisition and churn management
• Customer micro targeting: value addition
• Proactive maintenance

To understand them in detail, please visit the following link:

http://www.abc.net.au/technology/articles/2015/06/04/4248646.htm

Analytics has eventually gained importance in the banking sector. From cost optimization, risk balancing to revenue growth, analytics does it all. Operational analytics: reporting, basic forecasting with data and Advanced analytics: model driven, focusing on the predictive aspects- these are used by the banking sector. Slowly customer analytics and risk analytics are also coming into the picture. These help in revenue growth, investment banking, improving customer experience and save the bank from the uncertainties of the market. Analytics is giving the banking sector well defined strategies, changing paradigms with the advancement of technology. With this evolution of analytics, the need for professionals who can bridge the gap between IT and businesses is immediate. Banks are already employing personnel to read into the data offering growth, efficiency and risk management. Read more at:http://www.businessworld.in/news/economy/analytics-&-banking/1719002/page-1.html

To more than a billion cricket frenzy people in the country and outside, how can cricket be made more interesting? Is there a way organizers of the game can make fans grip to it with increasing fervor? Apparently these are the key points ICC tried to focus on in this world cup. Predictive analytics is what ICC banked on to increase fan engagement. ICC Cricket World Cup 2015 was considered as the most digitally advanced in history. ICC, with support from SAP, came up with the much insightful Match Center through which statistics, comparison techniques which earlier used to be available, albeit not very advanced, to coaches of teams, and commentators were available to any owner of a smart phone with the touch of its app. ICC has increased its use of analytics lately, and will sure rely on it more than less in coming years.

To read more, follow:  http://www.financialexpress.com/article/industry/tech/when-cricket-married-predictive-analytics/58534/ 

A famous chain that oversees the operation of 514 restaurants across the US, has found a way to integrate Big Data with Business Intelligence Services. The system works on data from point-of-sale, marketing, promotions and customer surveys to provide feedback on sales in real time. This not only helps them maintain a competitive edge, but also maximize profits. Big Data was used to select which item to put on the restaurant's menu too. After evaluation of sales, simplicity of preparation, profitability, quality and brand. Only once they met the required target, were they made permanent on the menu of that restaurant. Read more at: http://www.forbes.com/sites/bernardmarr/2015/06/02/big-data-at-dickeys-barbecue-pit-how-analytics-drives-restaurant-performance/

According to Scott Langfeldt (Teradata) “Big data is changing the way the world works- By combining with faster processor speeds and innovative analytic tools- helps in detecting fraud, part failure, and churn.”
For implementing big data and analytics into the company- analytical, business and IT departments need to work together. But they usually have differences.
Scott Langfeldt (Teradata) discussed some ways to solve these differences:
• Categorize your business and mission critical process.
• Make sure that flexibility is built into “business critical” process.
• Create a partnership between the IT developers and analytical teams.
• Develop “business solution” specialist on the analytic team.
• Develop “analytical experts.”
To know more about these ways, follow this link: http://www.forbes.com/sites/teradata/2015/06/02/avoiding-the-drift-into-analytics-oblivion-turning-your-business-into-an-analytics-driven-one/

With the advent of Big Data and technologies that can handle data in real time, Big Data is now reshaping the landscape of security with radical changes in the analytics methods being used. While most security specialists admit that perfect protection is not possible, using Big Data can help in increasing the prediction accuracy of attacks. Generating data for each user signature for example and storing them in NoSQL databases made them scalable. The motivation was to allow relocation of security information and improved monitoring for systems. As companies move from descriptive analytics to predictive analytics, the scope of Big Data in security greatly increases. Read at: http://www.techrepublic.com/blog/big-data-analytics/how-big-data-is-changing-the-security-analytics-landscape/

According to Kevin Mahaffey (CTO at a security firm Lookout) "The more ways we make data more convenient, the more risk there is to access the data and access things without your knowledge". Such is the case with Apple watch. It expands the data set freely over the internet. Not only your location can easily be traced, your heart rate and activities can also be monitored by which your mood and choice can easily be deduced. To know more about the new technology, follow: http://www.cmswire.com/cms/mobile-enterprise/is-the-apple-watch-a-security-threat-029105.php

Rolls Royce, a company that is a leader in the manufacture of engines that generate large amount of power in a high-tech industry has begun to look for Big Data solutions to increase profits and reliability. Its engines and machine parts are fit with scores of sensors that monitor their operation and detect change in real time. Royce now employs Big Data in design, manufacture and after-sales crunching of data. With over 3TB data generated per manufacturing component a year, there is no doubt that there is a need for integration of Big Data. Read more at: http://www.forbes.com/sites/bernardmarr/2015/06/01/how-big-data-drives-success-at-rolls-royce/

The increasing amount of data available to retailers, are giving them quite a sweat, when it comes to extracting the required data from such a large pool. Big data yet again proves to be the savior of the day. Big data helps in segregating consumers, and sending them promotional offers on the basis of their purchasing patterns and location, thus improving 'customer opinion' in the process. It has been observed that customers, now-a-days are increasingly doing online study about their desired product before making the final purchase from offline stores. Big data integrates this data along with the data of actual purchases, including the location of the purchase, to filter the segregation of customers and give them better service. Read more at:

http://channels.theinnovationenterprise.com/articles/using-big-data-to-improve-consumer-sentiment

Customer analytics deals in the evaluation of consumer satisfaction, from the purchase of a product or service. The insights obtained from the data, assists in assessing a company's principle performance indicators, the sales division's performance and in making future sales forecasts. Customer loyalty aids in generating profits for the company. Customer relationship management (CRM) analytics, when applied efficiently, generates the best insights on customer satisfaction. CRM analytics analyses data, ranging from the profile of the consumer to customer feedback, to ensure the best possible results. Read more at:

http://channels.theinnovationenterprise.com/articles/the-secret-to-measuring-customer-experience

Optimizing production for manufacturers with complex operations is not an easy task. There can be volatility in costs and prices, managing multiple plants and figuring out the combination of inputs for products are complex operations. These complexities are abundant in the chemical industry. Advanced data modelling and analytical techniques have helped this industry perform better. Data about companies’ performances can be put into a mathematical model which predicts production under different conditions. The resulting model brought sea changes in the companies’ production decisions, increased plants’ EBIT returns and production capacity. This change was not without a side benefit: better cross-unit collaboration and decisions were made with all constraints and trade-offs in mind. Read more at: http://www.mckinsey.com/insights/operations/taming_manufacturing_complexity_with_advanced_analytics

News agencies are venturing into analytics. A news agency also cleans the Internet for news, indexes it, and then allows users to ask questions of that data. It also allows you to extract facts and do trend analysis. Firms are taking data collected by machines or people, and using that data to generate news. Thanks to big data technology, it's becoming more practical to incorporate the field intelligence into the predictive models that executives increasingly rely on to make good, fast decisions.  Read more here: 

http://www.datanami.com/2015/05/29/how-big-data-is-changing-how-businesses-use-the-news/ana

Nowadays, companies are focusing on the best possible answers than asking the right questions to get the minutest details. To get the best details, a set of connect questions has to be answered which requires using a connected set of data sources. This is called unified analytics. It will enable the access and analysis of data from multiple sources on a single interface. But we need to keep certain things in mind like integration of unstructured and structured data which is not an easy process. Also, we need to look beyond traditional sources within firewall and focus the data strategy on customers. Read more at: 

 http://www.analytics-magazine.org/web-first/1266-unified-analytics-a-new-mastery-over-the-data-wave

A Formula 1 car (F1) may take 5 months from the drawing board to production. Testing programs of the car's speed, stability, aerodynamics and tire degradation around a racetrack is done by the engineers and data analysts. Some teams uses technology which enables its existing systems to process this data faster than ever before.  It is not just about interpreting analytical information, but being able to make strategic decisions as a team. It would be interesting to see the sport getting audiences more integrated with real-time data. Exposure to basic forms of live data via a mobile app may give viewers an indication of why teams make the strategic decisions that they do. The F1 car technology shows how the sport is in pole position in terms of technology innovation especially with data. Read more about this article at: http://channels.theinnovationenterprise.com/articles/f1-and-data-analytics-it-s-a-numbers-game

 Customer Relationship Management (CRM) is the approach of managing a company’s interactions with customers. It involves various technologies that organize and automate marketing, customer service and technical support. Companies employ Business Intelligence (BI) tools for the same. A BI tool is useful when it has rich, in-depth data to analyze from a CRM system. It helps companies organize and manage customer data by improving tactical and strategic decision-making for company growth.

Objectives of integrating BI and CRM:-
1. Collecting and consolidating data, lowers overhead
2. Missing data is lesser as it stores data in a central location
3. Duplicate data can be detected easily.
The methodology for the above integration follows Review, Analyze, Plan, Implement, and Deploy (RAPID). Read more at: http://searchcrm.techtarget.com/tip/Integrating-CRM-with-business-intelligence-tools

Statistical analysis is being used extensively in all sorts of sports now-a-days. However the growth of analytics in soccer has been quite slow, mainly because of its orthodox nature. Hence, enters Thomas Bayes’ famous theorem, the Bayes’ theorem, according to which, the chances of an event taking place, is updated, by integrating the former chances of its occurrence and the new information that might affect its prospect. The Bayes’ theorem completely encourages the use of analytics to revise our perspectives regarding players and teams. Stats refer to raw data collected from each match regarding both the individual player’s performance and the performance of the team as a whole. Analytics manipulates this data, thereby extracting the desired information, which helps in predicting future game scores. Read more at:

http://www.sportsnet.ca/soccer/soccer-analytics-premier-league/

According to Gene Pease, CEO of Vestrics, "The power of predictive analytics is you can understand where your investments are working". In the last few years, the idea of hiring, retaining and training employees has been a foreign concept for many companies due to the downsizing. Thus, predictive analysis in collaboration with HR is proving to be one of the ways managers are modernizing with their hiring and engagement practices. Organizations can thus create the profile of workers that should fill a particular position. According to writer Anne Loehr, "The biggest benefit is that predictive analytics can help remove human bias". Thus customized on-boarding and leadership development programs may evolve out of predictive analytics in the near future.  Read more about this article at:  http://fieldservice.com/2015/05/26/predictive-analytics-a-magic-bullet-for-field-service-hiring-managers/

The present day drug traffickers are very proficient in using modern technology, manipulating it for obtaining new marketing opportunities for their drugs. These criminals are using digital networking to a large extent for distributional purposes via secure methods, provided by modern day technology, which go undetected.  Often investigators fail to identify the disturbance they must be looking for, whose data lies well concealed under suitable digital protection. Advanced crime analytics incorporates big data and advanced analytics along with crime science study to detect anomalies, often their sources and the associated people. Advanced crime analytics is also essential in controlling cross-border drug trafficking by not only protecting witness details but also speeding up the entire process. To know more follow the article by Craig Richardson (chief executive of the Wynyard Group) at:

http://www.canberratimes.com.au/comment/crime-analytics-software-proves-powerful-weapon-in-war-on-drugs-20150414-1mkp6r.html

Ski resorts now-a-days are using certain frequency recognition systems, whose data is used to upgrade skier's experience, in multiple ways. For example, the system has led to the replacement of the old paper system, which unnecessarily consumed a lot of excess time. Stats collected from individual skiers are used by programs, to get an idea about the number of lift rides taken, number of days spent in the slopes, height scaled etc. Skiers can also get rewards based on their performance as directed by the data, thus leading to a gaming experience, which is attracting more and more skiers to the slopes. Big data also ensures that the ski resorts can efficiently transfer proper information to the consumers using data management. Big data not only helps the resorts in predicting weather, with the right stats, but also helps in strategizing suitable marketing techniques. Read more at:

http://channels.theinnovationenterprise.com/articles/even-ski-resorts-are-benefiting-from-the-big-data-explosion