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

SWOT Analysis must contain a two-dimensional look from both a product and a brand point of view. JIM JOSEPH (Contributor), writes in this article about some points which are important in any business. They are:

1. Business strength should become unique competitive advantage.
2. Challenge is the key word and focus on the factors that keep us from being competitive and identify our weakness.
3. Business house must think of various ways to expand their brand, because opportunities will be likely to impact business.
4. Business must identify the potential threats, and finally, focus on actionable items to make SWOT analysis realistic.

Read more at: http://www.entrepreneur.com/article/246434

In business, the 'black swan' is a form of disruption, which is usually least expected by a firm. Again, 'ugly duckling' refers to the day to day disruptions, which are always expected, and the firm remains prepared for it, hence, the coining of the term.  Companies don't pay attention to these disruptions with the expectation that they will remain small and never grow up to be as big and disruptive as the 'black swan'. Majority of the companies have risk management departments who focus on regulations and the traditional risks, completely ignoring the extreme ('black swan') cases. The 'black swan' has the capability of even surpassing the traditional data analytics procedures. Hence, comes into the picture, big data and advanced analytics, which gathers newer insights even about the most uncommon and worst case scenarios that may happen in the near future. Armed with information, much beforehand, the companies can make themselves immune, even to the worst of the situations. Predictive analytics thus plays a major role in recognizing 'black swan' events, often from the data of past 'black swan' episodes. Read more at:

http://www.teradatamagazine.com/v15n02/Features/Ugly-Duckling-or-Black-Swan/

The pursuit of data and analytics is helping companies to venture into new fields, transcending the fine lines between different industries. For example, a well-known sports company has ventured into the market of wearable technology, with the release of its fitness tracker, containing sensors, which automatically collects data regarding one's sleep patterns and the number of steps taken in a day.  Consumers must first download the fitness tracker app in their laptops or mobile devices. So, indirectly the company is also involved in the software business. Since the objective involves collection and analysis of data, to get customer feedback, the company is also involved in the analytics business. Cable and satellite suppliers are also using analytic tools to get deeper insights into viewing trends and ideas about more profitable programming opportunities. Read more at:

http://blogs.teradata.com/bill-franks/big-data-blurring-industry-lines-nike/

More and more music companies are turning to data analytics as people are increasingly listening to music online. Social media is providing newer ways to reveal the variety of factors affecting the different artists' sales. Music analytics companies now have access to information regarding the frequency, a song is heard, when it's heard and by whom, which help them in forecasting future hit records. Musicmetric, a music analytics platform, also focuses on gathering customer opinion from social networking sites to gain information regarding different artists' popularity for understanding the best platforms to market them. Even data related to ticket sales to live concerts can help in planning tours. To know more about music analytics, follow:

http://channels.theinnovationenterprise.com/articles/how-is-analytics-changing-the-music-industry

60% of CLOs are dissatisfied with their internal learning analytics capabilities. Most of the CLO are dissatisfied with their traditional organizational approach Kirkpatrick to evaluate learning. They want an analytical enhanced approach in learning. Modern analytical enhanced approach measure overall management and development of a company's employees. Laurie Bassi (CEO of McBassi & Company) and Dan McMurrer (Chief analyst of McBassi & company), talks about how to transform an organization's learning analytics:

1) Create an “authentic” learning impact evaluation by embedding it in a more holistic framework.
2) Stop waiting for the perfect data warehouse. Instead, create a “data hut.”
3) Don’t let the perfect become the enemy of the good.
4) Choose your initial analytics project carefully.
5) Start under the radar.
6) Insightful reporting trumps data dumps.
7) Use learning evaluation to improve the effectiveness of learning.
Read more at: https://www.td.org/Publications/Blogs/Learning-Executive-Blog/2015/05/7-Steps-to-Using-Analytics-to-Improve-the-Evaluation-of-Learning

Data analytics, especially the predictive ones, enable companies to obtain forward-looking insights they wouldn't otherwise have been privy to -- such as forthcoming changes in customer behavior and buying patterns, or the formation of new market segments as-of-yet unserved by the industry. The problem is that while you typically can't achieve the competitive edge you're looking for without analytics, you can't achieve it when you over-analyze, either which becomes a balancing act. Optimization is certainly a critical part of what companies should seek to derive from analytics, so too is innovation. Analytics becomes exclusively about finding ways to cut costs whereas also about finding ways to be cutting edge. It becomes about protecting today's existing revenue stream and should also be about finding tomorrow's new one. Thus, focusing too much on optimization can have the unintended effect of making organizations afraid to take on any risk. To know more, please read this interesting article by Joanna Schloss at: http://www.cmswire.com/cms/analytics/why-companies-cant-afford-to-go-overboard-with-analytics-029179.php

It has been documented that traffic can change for a certain website or app while reviewing analytics report. It is difficult to prepare an analysis as most often it is not clear from where to start the diagnosis. There is no best way to start the analytical reporting, the key being finding the exact reason behind the traffic drop; whether technical or marketing influence.  Traffic declines can be categorized into two category i.e. sharp declines or gradual decreases. Sharp declines over short stretches can point to technical issues while gradual declines may be inclined towards marketing and digital influences. Various solutions are available for change in traffic due to technical issues. To know more, follow:

http://www.cmswire.com/cms/analytics/where-did-it-go-understanding-traffic-drops-in-google-analytics-028468.php#null/  

Sustainable development is the development of the society, keeping in mind the needs of the present as well as future generations. It is this development that is the ultimate goal of every nation. For this, UN will launch a new set of Sustainable Development Goals (SDGs) in 2016. These goals will give rise to various important questions such as:

• How will we achieve these goals?
• Who will finance these goals?
• Which countries will need most resources and of what type etc.

For answer to these questions, the decision makers refer to the data provided by various international institutions like UN, IMF, World Bank, etc. But while doing this, they face a big hurdle i.e. Incompatibility of Data in terms of definitions, methodologies and sources.

Now, with the data revolution going on and big data and analytics taking the centre stage, we now have an opportunity to collect and produce high quality data that will provide the right information on the right things at the right time. The need is – its correct implementation.

To know more, please read the following article by Gail Hurley and Jos Verbeek at brookings.edu:

http://www.brookings.edu/blogs/future-development/posts/2015/05/26-financing-for-development-hurley%E2%80%8F

Big data combines unstructured data with structured data to produce a report which provides a complete view of the organization. This report helps in decision making. Big data provide real time or near real time data. According to Mark Shacklett (President of Transworld Data), big data analytics results have impacted corporate revenues, expenditure and customer satisfaction. Web-based analytics on e-tail users helps in generating more sales by assessing customer preferences. Network diagnostics toolset analyze network and machine-generated data and produce predictive reports. This tool set gives a real-time view of network traffic. Sensors placed on railways and tram tracks, help crew members to proactively repair or replace equipment and railway tracks before they fail. Read more at: http://www.techrepublic.com/article/4-ways-real-time-analytics-lead-to-competitive-advantages/

According to James Heskett, Predictive analytics have the potential power to produce remarkable services and longer lives. Now, predictive analytics is also applied on humans. Recently, companies are sending information to target customers about products of their interest. With the advancements in big data and cloud computing, the accuracy of this science is improving now. Predictive analysis is also essential for organizations focusing on customer satisfaction in delivery time. Read More at:http://hbswk.hbs.edu/item/7527.html

We have come across the word "Smart city" frequently in recent times and we will see it more frequently in coming years. What exactly is a Smart City and how is it created?  The idea of smart City is to embed the technologically advanced devices which are making the Internet of things a reality into our surroundings. Once the technology is hard wired with the infrastructure, we can interact with these devices using our smart phones or computers and also devices can interact among themselves. For example, a car will be guided to an empty parking space without any human intervention.

In order to realize these smart cities, software and hardware applications for the internet of things are being encouraged. Some of the applications planned for smart cities are intelligent street lighting systems to conserve energy, mapping energy use around the city to understand demand and mapping how people maximize use of bicycle and foot paths. People are also raising caution over this new technology as it will hurt privacy.Read more at:http://www.forbes.com/sites/bernardmarr/2015/05/19/how-big-data-and-the-internet-of-things-create-smarter-cities/2/

In the age of Big Data, the data tables are going to grow enormously in size. Millions of rows of data will be obtained. Computational techniques available now will no longer be efficient in analyzing and interpreting the data. Enter this June; MIT researchers will present a new algorithm that will reduce the size of the data tables by leaving out bunch of rows. The data/rows remaining will be the representative ones of the total data. This is called condensed data/matrix of original data/matrix. To know more about how to handle Big Data, follow:https://newsoffice.mit.edu/2015/algorithm-shrinks-big-data-0520