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

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/ 

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

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

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

As cybercriminals are trying to penetrate into each and every system, leading to huge losses, some steps that can protect an enterprise from cyberattacks are: 1. It is important to enable full disk encryption technology, so that all data on the storage drives are scrambled, which makes it impossible to restore the original data, when in wrong hands.
2. However, a concern dealing with sensitive data can maintain a separate encrypted file volume for its most sensitive files, by installing it before the first usage.
3. It is preferable to use hardware-based encrypted USB flash drives for data transfer, which provides seamless encryption of data, as it gets copied onto the drive.
4. A private cloud hosted on a network-attached storage device can be maintained for data synchronization among privately-owned devices.
5. It is always preferable to use password managers in systems.
6. Multifactor authentication should be enabled, which requires an additional information for final authentication, like maybe a pin code sent via text message.
7. It is important to have some backup account (say email id) registered to get information of any password reset, which may happen in a cyber-hijack.
Read more at:http://www.cio.com/article/2933183/cybercrime/7-steps-to-protect-your-business-from-cybercrime.html

Mobile is a much more personal, interactive, engaged platform than desktop, and should be used as such. - By Ari Brandt (CEO and co-founder of MediaBrix). In this competitive era, if a company won’t recognize the opportunity first, a chance of losing the games increases. And mobile phone is one of the biggest opportunities to maintain a close relationship with your customers. But most of the ad companies are failing to recognize the demands, challenges and opportunities of mobile phones. Rule to crack the opportunity of mobile phones:
• Leave old ad methods behind.
• Take advantage of unique mobile capabilities.
• Put the customers first.
• Leverage new measures of campaign success.
Read more at: http://mashable.com/2015/06/11/mobile-marketing-innovation/

Big Data and analytics have a huge role to play in the future of healthcare. Data will play a major role in deciding how healthcare companies, practitioners and technologies interact with their patients. Big Data ensures efficiency and accuracy in predicting treatments. Using data, doctors can make more accurate predictions based on the specifics of the patient rather than using a general rule for treatment. Major companies are venturing into healthcare by formulating pre-defined algorithms; making it easier to cure complex medical conditions. With the advent of Big Data in healthcare, people will have the opportunity to keep a track of their health; doctors will have a better idea of somebody’s health thus allowing them to provide health advices on the go. Read more at: http://channels.theinnovationenterprise.com/articles/big-data-has-a-huge-part-to-play-in-the-future-of-healthcare

Data mining results can be used by organizations to prevent losses ahead of time. Organizations usually use indications like inventory levels or employee turnover, which occur later in the business cycle to gauge shrinkage cost but by that time the losses start to incur and there is nothing much that can be done. According to a report by PricewaterhouseCoopers, if companies gather and analyse data, they are able to get better insights into the business and use the early warning indicators to stop losses from happening by making informed, strategic decisions, thereby saving time, money and effort. Read more at: http://www.tibco.com/blog/2015/06/03/strategic-data-analytics-to-help-reduce-shrinkage/

Big data is set to change the healthcare landscape offering better patient care, minimized hospital re-admission, and reduced costs but every new tool has a learning curve and so does this one in the healthcare industry. Big data in healthcare is referred to as Electronic Health records (EHRs), though relatively easy to collect but volume does not mean insight, it is necessary to extract data relevant to the heart of the specific problem. Apart from the 3Vs in big data – Volume, Variety, velocity, healthcare analytics also has another V, Veracity i.e. truthfulness or credibility, since it involves life and death decisions. But it is still a goal and not reality since the quality of healthcare data is highly variable. Another challenge is that the methodology requires technology and professional expertise for predictive analysis to fully utilise the data mining results to improve patient care. Read more at: https://www.healthcatalyst.com/3-reasons-why-comparative-analytics-predictive-analytics-and-nlp-wont-solve-healthcares-problems/

Nowadays, daily sales are not enough to ensure longevity of a business. Markets are beginning to realize the necessity of predicting future sales. They are tapping into the business trends and applying machine learning algorithms on big data to allow businesses to maximize their efforts in the most profitable areas. By knowing ahead of time, what a customer will buy, profits can be maximized and businesses can be tailored accordingly. Predictive Analytics allows us to segment customers, find patterns in their behavior and take preemptive measures to reduce churn. Analytics can be used to identify correlations and also to find causation. It can allow us to predict an individual's purchase behavior once we understand the causation underlying a pattern. Read more at: http://www.computerworld.com/article/2934086/business-intelligence/marketers-are-betting-big-on-predictive-analytics.html

Social media, due to its immense popularity, is being used for branding. It is paving a way for small businesses to compete with their bigger counterparts. Social media has led to consumer empowerment thus allowing them to interact with one another, ignoring the established channels of marketing. Adopting a mobile strategy is critical for marketers, and almost every individual in today's world possesses a mobile phone. Social media can both strengthen a brand or lead to its demise. Companies should be able to quickly adopt new strategies in response to consumer preferences to be successful. Read more at: http://www.businessnewsdaily.com/7953-social-media-branding.html

Marketers need to think creatively for building an effective and creative campaign. On the other side, they have to give returns on investments. So, marketers are feeling stressed. To improve the performance of the marketers, they need to make standardization a priority across their organization. Standardization is an essential practice to improve the performances and gives long-term benefits. Scott Vaughan (CMO of Integrate) in his article at marketingland.com, discussed about five areas where marketers should start standardizing are:
• Process
• Data
• Key technology systems
• Metrics and Benchmarks
• Team Expectations
Read more at: http://marketingland.com/marketers-time-stop-standardize-130267