Analytics is being widely used in many areas and sports is no exclusion. Data analytics has successfully scripted victories for many teams, already. Data analytics can be applied to any sport be it tennis, baseball or cricket. But, sports analytics is a completely new concept in India. Sports analytics is the amalgamation of sports and information technology. Sports teams are now hiring data analysts who feed data in their algorithms, which then process the data fed and perform numerical calculation to figure out the strategy for the next match. The analyst then informs the coach and the team players about the prescriptive strategies. Read more at: http://www.cio.in/feature/big-data-is-here-to-have-a-good-innings

Social media is no more just the place to catch up on old school friends and college buddies; it is now being used for diverse activities. People, nowadays, are using social media to look for products and services, research and review companies and ask for recommendation from friends. Social media has now become the place for branding, opening channels of communication with customers, building loyalty, being transparent and establishing goodwill. Reaching out to customers is far less expensive on social media enabling marketers to achieve higher marketing ROI. Digital marketing has replaced traditional marketing techniques as consumers these days are more tech savvy and active on social media. Read more at: http://www.business2community.com/social-media/social-media-advertising-roi-01247591

A recent study has revealed that there is a growing gap between the amount of data that firms are gathering and their staff's ability to analyze it. A major difficulty that the companies are facing is that as the value of data analytics is being recognized the competition for capable analysts is also increasing. Employees are more attracted to companies with a pre-established analytics framework than to newly established ones. To mitigate this problem several companies are outsourcing their analytics work. But having data analysts internally is beneficial as it allows for easier transformation of analytical insights into business actions. Companies should partner with higher education institutes to initiate analytics courses to meet their needs. Firms should also recruit multi-talented analysts and also offer training to existing staff. Read more at: http://channels.theinnovationenterprise.com/articles/the-analytics-skills-gap

A chunk of healthcare information is being generated through electronic medical records, wearable devices and centralized databases leading to improvement in care, lowering of costs and driving efficiency. Healthcare, in recent times, is characterized by data-driven technologies thus leading to betterment of treatment, quality, safety and efficiency. These modern data-driven techniques also raise serious privacy and security questions as pointed out by Chris Boone, executive director of the Health Data Consortium. Concern over security arises when organizations pile sensitive consumer data. To mitigate the problem of data privacy, researchers recommend encrypting health data both in transition and at rest as healthcare companies are the popular targets of cyber criminals. Read more at: http://www.cio.com/article/2914170/healthcare/how-to-balance-data-privacy-and-healthcare-improvements.html

Companies now are emphasizing on converting data into action as quickly as possible. This is being done by unifying the databases used for operational applications with those used by analysts. This leads to continuous up gradation of models and adjustment of business functions as things are happening. Information is essential in a number of areas, targeted marketing being one of them. Due to the advent of online shopping and real-time processing of data, retailers are now being able to sell their goods at unadvertised low prices, without loss of profits, to customers who leave their website without purchasing the goods in their cart. In these cases, data handling and extracting data to deliver real-time actionable analytics is a challenge. Read more at: http://channels.theinnovationenterprise.com/articles/driving-real-time-decision-making-with-business-analytics

With plenty of big data on its hands, the healthcare industry will be able to improve quality and patient outcomes only if it is able to extract meaningful, actionable insights from this bounty of raw information. To reap the benefits of healthcare big data analytics, organizations should bring about cultural and leadership changes to promote analytical approach to the practice of medicine. Research puts it that to achieve improvement, multiple types of data are required which can identify opportunities, measure progress, and help users understand what works. Using predictive analytics to identify high-risk patients, reducing infections and adverse cases through implementing evidence based protocols and realizing the importance of patient-centred care are some of the measures that have been reported to have made an impact. Read more at: http://healthitanalytics.com/news/healthcare-big-data-analytics-plays-critical-role-in-quality

Organizations usually direct their data analysis efforts on transactional data i.e. the information generated when a customer purchases a product or service. In the process of collecting transactional data, large amounts of additional information are also generated commonly referred to as dark data. Dark data when approached in a correct way can reveal all kinds of patterns and insights that would have been otherwise missed. The key to unlocking dark data lies in the ability to understand the relation between unrelated pieces of information. With several databases offering completely new ways of reading traditional datasets, discovering the business value of dark data is becoming straightforward. Monetizing dark data requires analyzing it to discover hidden patterns, developing hypotheses and then putting the insights to use. Read more at: http://channels.theinnovationenterprise.com/articles/7407-tapping-into-dark-data

Getting around in big cities without facing traffic jams is almost impossible. After the businesses, it's the city planners and transportation experts now who are resorting to Big Data when making improvements to city transportation. Commuters have certain patterns they like to keep to while travelling. By analyzing these actions and the factors responsible for them, transportation experts understand why certain routes and modes of transportation are preferred over others. Gathering call data records help provide access to data about travelers, which data scientists can use to decode the transport pattern of travelers. Countries like Australia and Brazil have already implemented Big Data to upgrade public transportation to keep up with the current demand of metropolitan cities. Read more at: http://channels.theinnovationenterprise.com/articles/big-data-s-impact-on-public-transportation

“Starting from today i.e. 15^th June, 2015, Zimbabwe will phase out its official currency Zimbabwean Dollar and adopt US Dollar as its official currency”

This may be shocking news to some because a country is completely doing away with its own currency but actually, this is rather a late move by Zimbabwe as this country has been facing hyperinflation for the past few years. Hyperinflation is not just a theoretical concept, in the last century, it has two such instances had been observed. They are:

• Germany in the 1920s
• Hungary post WWII

Both of them were consequences of World Wars but such was not the case with Zimbabwe. In Zimbabwe, the main reason was an ineffective monetary policy managed by the ruling government rather than its Central Bank.

Reckless printing of currency notes was done, while ignoring the quantity, cost and time constraints. The heights of printing were reached when they even issued notes of $100 trillion. This reduced the status of the currency to just that of token with not much buying power and thus this currency was ruined by 2009.

Since then, US Dollar has already been in use for day to day transactions. The Zimbabwean currency has been left as a memory or in old bank accounts. This move of completely phasing out this currency is just an attempt to clean up the banking system.

As a result of this move, Zimbabwe will lose its rights to control its own monetary policy but this also has been seen as a welcome move by some economists, hoping that this would improve the situation.

To know more, please read the following article by Tim Worstall, Author of the book, “The No Breakfast Fallacy, why the Club of Rome was wrong about us running out of resources”, at Forbes:

http://www.forbes.com/sites/timworstall/2015/06/13/this-isnt-the-death-of-the-zimbabwe-dollar-this-is-the-long-overdue-burial-of-it/

Big data developments in 2015 show significant change in terms of data storing as well as data analyzing techniques. Measuring data agility is becoming more and more popular, as opposed to the conventional system of storage and management of data resources. The investment and scope of big data projects will be directly related to the impact and of an organization's response to changing trends among consumers, markets and competition. Another big trend organizations will focus on in 2015 is usage of data lakes. Using data lakes, Hadoop and BI systems and cloud computing, real time data analysis and decision making is expected to be fast. So the dynamic change in technology will bring revolution in terms of business decision making. Read more at: http://channels.theinnovationenterprise.com/articles/advancements-in-big-data-in-2015 

The Internet of Things (IoT) is one of the most hot and debated issues in context of Big Data Analytics. It provides huge and enormous volume of data and reduces the cost of obtaining data significantly. It is estimated that within the next five years there will be more than 50 trillion gigabytes of data. The huge volume of data may provide valuable insights into the market and may be useful for development of technology related to business expansion. Sometimes it may be a challenge to handle such large volume of data and extract useful information out of it. But with rapid progression in technology, analyzing such data is becoming less difficult, and it importance in modern business practices is rising exponentially.  Read more about this article at: http://www.content-loop.com/search-true-value-internet-things/

Mobile applications are an integral and inseparable part of modern data analytics. Mobile applications not only influences consumer`s decision to make purchases, but also allows companies to get insights into consumption pattern and market demand. Enterprises seek immediate-data from a wide range of sources, to fuel business processes by means of big data and analytics and this is provided by different types of mobile applications. It plays an important role, particularly in the field of global supply chain management and predictive analytics. On the other hand mobile applications are also being fuelled by data analytics, so that it cannot only collect the data but also analyze it and process it simultaneously to provide instantaneous results in real time. Read more about this article at: http://www.forbes.com/sites/benkerschberg/2014/12/17/how-big-data-business-intelligence-and-analytics-are-fueling-mobile-application-development/ 

With significant increase in online sales and more customers opting to purchase through mobile devices, high street retailers are facing difficult times. No wonder it is time to elevate shopping experience to a whole new level. Though Retails Analytics is not a new concept, the approach faces challenges in brick-and-mortar stores. Investing in real-time Wi-Fi analytics, where modern in-store analytics technologies can integrate with existing in-store Wi-Fi infrastructure to capture precise and real-time customer behaviour in stores, can be a solution. Creating an inclusive shopping experience that effectively combines the online and offline experience is the need of the hour. Read More at: http://www.fourthsource.com/mobile/future-analytics-retail-19148

The Internet of Things has the ability to benefit the healthcare sector vastly in the future. With EHR clinical analytics and sophisticated machine learning combining with big data from wearable, home monitors, medical devices, the Internet of Things has a huge potential for creating a productive environment of predictive analytics and prescriptive insights. Yet the concept is met not without challenges. In order to successfully reap the benefits, Jennifer Bresnick suggests development of certain core competencies, like "Developing the Mindset", "Building the health IT infrastructure" and others. Read More at: http://healthitanalytics.com/news/five-core-competencies-for-the-healthcare-internet-of-things

Yes, a $10 supercomputer swept Wall Street away. Braxton McKee, math and computer whiz, is tapping into the cloud to fetch all that market data inexpensively and built a software that employs Machine Learning algorithms to understand this data. Thanks to Cloud Computing and Big Data analytics getting cheaper, many startups and businesses can now employ their functionalities to provide services that are efficient, fast and scalable. The large amounts of data is mostly unstructured data, such as corporate documents, transcripts and social media and with the rise of Cloud Computing, the process is finally cost effective. Entities have begun leveraging cloud power to help hedge funds and other financial players run complex, big-data computer models. Maybe Cloud based Big Data analytics is the future. Read more at: http://www.smh.com.au/business/markets/10-hedge-fund-supercomputer-sweeps-wall-street-with-power-from-the-cloud-20150521-gh68hx.html

For start-ups and SMEs, Open Source (OS) software will be the most attractive option because it’s free and also there is no vendor lock in. So there are no contracts to break. The biggest advantage of OS software is that is gives us the option of operating, sharing, and modifying the software as we choose. Collaborators are able to access the software from around the world to share ideas and add features that could improve it. Its drawbacks involves low costs, which gets further complicated by a lack of support with OS software. Lyndsay notes four questions that needs to be answered in Wise’s book, Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize ROI. Read more about this article at: http://channels.theinnovationenterprise.com/articles/is-open-source-analytics-software-the-right-option 

Big Data Analytics has started to make significant strides in less explored areas like improving manufacturing performance. No wonder the theme of ARC European Forum, 2015 was intended to help develop some clarity over emerging related concepts such as Industrie 4.0 and the Industrial Internet of Things (IIoT). Several use cases about how "applying these concepts can deliver tangible benefits in real-world industrial production across a broad cross-section of industrial sectors" were presented. Read More at: http://www.automationworld.com/industrial-internet-things/big-data-analytics-improve-manufacturing-performance

Predictive marketing has taken hold of enterprises today. Marketers are now making use of predictive analytics and this has given birth to predictive marketing. Predictive marketing is the application of algorithms and machine learning tools to Big Data in order to help marketers direct their efforts in the most profitable direction. Using predictive analytics tools, marketers can gauge future sales and thus formulate appropriate marketing strategies to help boost sales. Predictive analytics can be used for segmenting customers, deciphering the pattern in their behavior and thus offering them the appropriate deals. Marketing and sales are the areas where predictive analytics is most used. Read more at: http://www.cio.com/article/2934274/why-marketers-are-betting-big-on-predictive-analytics.html

Predictive Analytics is making its entry into the toolbox of small companies. Predictive Analysis is a three-part formula- analysis of past performance of situation under consideration, understanding the present and applying the past to present to predict the future. For small businesses, it can be applied for customer retention, target marketing, demand forecasting, and overall marketing. However, it is crucial to ascertain the purpose for using Predictive Analysis, as the technology may not necessarily be right for every company or for every situation in the small business sector. Read more at: http://www.smallbusinesscomputing.com/News/Marketing/can-predictive-analytics-help-your-small-business.html

The role of risk management has become more pronounced than before and companies are resorting to predictive analytics along with business insights to visualize and manage risk. Predictive analytics has gained immense popularity in the area of risk management due to its ability to identify and predict vulnerabilities, fraud, security breaches and the quality of control systems and governance, as pointed out by Rita Sallam, a research Vice President and analyst. Several firms are utilizing the advanced techniques for data extraction to manage risks. Post data gathering and visualization, firms are able to identify risks and mitigate them. Firms engaging in risk modelling produce impressive returns. Read more at: http://channels.theinnovationenterprise.com/articles/risk-visualisation-and-predictive-analytics-in-risk-management