The success of a company is vested on its employees. It’s the employees who ensure that resources of the company are utilized to their full potential. But at times it becomes difficult to identify the best members of the staff. Workforce analytics comes into play here. Workforce analytics enables organizations to get a complete picture of their workforce and identify ways to improve it. It allows organizations to identify and retain their most important staff. Workforce analytics involves analyzing large sets of employee data to find correlations and patterns. Statistical techniques like tests of significance, factor analysis and multivariate analysis are applied and charts are produced to bring together all information available about a team. HR department can then leverage these insights to achieve high retention rates. Read more at: https://channels.theinnovationenterprise.com/articles/workforce-analytics-are-you-retaining-your-highest-performers

As researchers and scientists get access to the plethora of information of weather patterns, they are getting better equipped to deal with upcoming disasters. This data however is massive and highly complex thus the data gathering serves as only a part of the solution. Governments today are realizing the need for data-driven forecasting to keep up with the volume and variety of information required for smarter forecasting. Predicting weather anomalies more effectively could save thousands of lives during natural disasters. The process requires delivering more accurate forecasts and delivering them sooner. Data analysts use the voluminous data gathered to develop reliable forecasting models. Making sense of the data and building actionable intelligence will largely help protect the public from natural disasters. Read more at: http://www.forbes.com/sites/centurylink/2015/07/08/hurricane-forecasts-get-better-give-more-warning-thanks-to-big-data/

Lean Six Sigma or LSS is a combination of two business management techniques, where lean strategizes in waste reduction and Six Sigma uses a methodical five step (Define, Measure, Analyze, Improve &Control) approach to solve business problems. LSS helps to save money, optimize and streamline internal processes and communication. Implementation helps in efficiency, higher quality and better customer service. The benefits are: 1. Increased Efficiency
2. Higher Quality Output
3. Better Customer Service
4. A Safer Workplace
5. Program Implementation. Read more at: http://www.pddnet.com/articles/2015/06/benefits-lean-six-sigma-methodology-culture

Public Sectors Bank (PSBs) can’t lend as long as they have huge Non Performing Assets (NPAs). According to the latest financial stability report by RBI, stressed assets have risen from 10.7% to 11.1% in March 2015 from Sept 2014. The process of dealing with loans is very slow which leads to inefficiency. In order to de stress these assets, either provide extra capital to PSBs or get rid of NPAs from the balance sheet. The former is difficult since the scale of capital needed for the purpose is huge, which the current fiscal situation would not permit, latter being the only resort available. Cleaning up NPAs would also give the much needed capital for lending. Read more at: http://blogs.economictimes.indiatimes.com/Myth-n-Reality/unburden-banks-of-non-performing-assets-for-faster-economic-recovery/

There is a call for new school of cyber defense,since the perimeter security cloud cannot prevent cyber-attacks anymore. The first step is to mitigate the damage. The best way is to run a fully updated , layered  ,in depth set of security tools and educating the end users about how to falling for attack lures. Second step is to prepare for the aftermath of the attack. The approach here should be data centric. Prepare a written plan as to who to contact and what to do in case of security breach. Read more at: http://www.darkreading.com/attacks-breaches/twitter-chat-how-to-prepare-for-a-cyberattack/a/d-id/1321216

If the country is changing faster than the expectations, then organizations are faced with the challenge of moving with those changes. It is affected by fast evolving markets, ever changing technology, increasing competition and changing preference. So how to react to these changes? First is by gathering intelligence, using big data analytics to discover patterns by tracking commercial data, for example in consumer spending, movements of competitors. Next is to look for the unexpected. This involves constantly improving your business model, inculcating the changes that raise inside and outside the industry. Read more at: http://www.forbes.com/sites/bensimpfendorfer/2015/07/07/the-agility-factor-in-asias-competitive-markets/

Hadoop, for many years, was the leading open source Big Data framework but recently the newer and more advanced Spark has taken over. Spark is reported to be 100 times faster although it lacks its own distributed storage system. For this reason many projects involve installing Spark on top of Hadoop, where Spark’s advanced analytics can make use of data stored using the Hadoop Distributed File System (HDFS).
What really gives Spark the edge is speed. Spark handles most of its operations ‘in memory’- copying them from the distributed physical storage into far faster logical RAM memory. Spark’s speed of handling advanced data processing tasks such as real time stream processing and machine learning is much more than what could be achieved by Hadoop. Faster dynamic data handling gives Spark the upper hand over Hadoop.
However it must be concluded that these two frameworks are not necessarily mutually exclusive and do not perform exactly the same tasks. In fact using both of them together can actually provide better results than using either one separately.

For more information visit:
http://www.forbes.com/sites/bernardmarr/2015/06/22/spark-or-hadoop-which-is-the-best-big-data-framework/

All major corporates employ customer call centers to incline to the needs of their customers. A client usually calls the customer center and the first impression he receives is that of the service tended to him by the customer care representatives. So, organizations have started using automatic voice response systems to reduce the workload of their agents, attain to their customers round the clock and reduce operational costs. However, it has been found that many customers are disappointed with the automatic voice response systems due to various reasons. Companies need to design effective voice response systems that are brief and serve the needs of the customers. Find the detailed view point here: 

CRM systems are used in organizations all over the world to collect and maintain data about customers and prospects in a structured form. However, what about the huge amount of data that is present in vague formats before it is structured in CRM systems. "Content Intelligence" is a natural language processing system that extracts meaningful data from E-mails, reports, customer interaction meeting minutes and assigns metadata to the content for ease of access by the CRM system users. This reduces a lot of workload for them as they do not have to read through vast amounts of customer interaction data. For more visit:

http://it.toolbox.com/blogs/insidecrm/harnessing-unstructured-data-for-crm-68008

With every passing day it is becoming very important to safeguard data by companies both small and big. It can be done in the following ways:
1. Prioritize the issue – The issues must be computed and addressed regularly.

2. Understand what your data assets are – It will be beneficial if the data assets of a company are identified beforehand.

3. Learn about what you are up against – The Company should have at least an idea on how the hackers might steal or compromise the data.

4. Communicate issues with employees – The employees should be encouraged to take up habits that reduce data breaches and awareness should be spread.

5. Be ready to react – The Company and its IT experts should be alert and ready to react in any emergency situation.

Read more at: http://www.smartdatacollective.com/keithrbr/326717/5-tips-protecting-your-data-assets-more-effectively

These days recruiting a new employee accounts for a huge investment by the company. A major section of the company’s revenue is spent on staff salaries. Thus with improvement in technology, improved strategies and planning can be used in the recruitment process.
Klout scores are used by companies to rank users according to their social influence, especially for recruitments in sales and marketing roles. Gild is another service used in the field of technical programming jobs. In this, service software development professionals are assessed based on their contribution to public and open sources and their experiences in the past.
Thus Big Data helps in eliminating the guess work in the recruitment process thus finding a more scientific approach of recruiting staff.
Read more at: http://www.smartdatacollective.com/bernardmarr/327498/how-big-data-changing-recruitment-forever

Market intelligence can be used to assist almost every decisions faced by a company. Market intelligence helps a company to increase revenue, profit or market share. Three basic steps on how to go about gathering market intelligence and what types of market intelligence will deliver useful insights are:§ Don’t reinvent the wheel –A huge amount of learning can be gathered using workshops specially if guided by skilled external moderator.
§ Choose your battleground – Clearly stating your key objective will help in your business plan and actions will be taken.
§ Don’t stop digging –It is not only important that market intelligence is acted upon when it is collected but also a constant feedback is needed. Read more at: https://www.b2binternational.com/publications/guide-to-market-intelligence/

Keeping tabs on products just got easier for manufacturers and retailers. Smart sensors, a part of IOT has enabled tracking of products from manufacturing till the time it gets sold. This technology has drastically reduced waste. Not only that, usage data could be collected throwing light on usage patterns and thereby helping improve the product from a consumer perspective. Interestingly it would help optimize product revenue and collect specific information related to individual consumers that might be used to expand sales or even invalidate warranty.  This sort of monitoring does not go down well with a section of consumers who believe this is an invasion of privacy. In this age of IOT, clear boundaries should be set demarcating what is acceptable in consideration of the benefits. To know more, please follow: http://www.dataversity.net/are-smart-products-getting-too-smart/

Starting off as a small time entrepreneur it might be difficult to see the use of Big Data for your company’s growth. After all Big Data seems to be a term befitting multi million dollars firms, not for start-ups. In reality this isn’t true. Your small start-up can grow exponentially at a affordable cost using data resources which can be availed online by almost anyone.
Here are a couple of ways how it can work for you.
Customer Relationship Management (CRM):
A very important resource for any business is CRM software. Owners can set up a simple CRM spreadsheet, even if it’s just one single webpage, lets you to grab your customer’s feedback which helps towards your company’s growth.
Marketing:
As a small business owner you cannot afford to waste your valuable resources on a  misplaced advertisement or trying to market your product when there is no demand for it. You can use Big Data to analyze the market trends to key in on when and where buying habits are highest.
Big Data is everywhere and you can make use of it easily as long as you keep it simple & streamlined and not overdo it.

Read more at: http://www.smartdatacollective.com/keithtullyy/322521/how-small-business-can-use-big-data

The first step in applying analytics to healthcare data is to create a centralized repository of all the available information extracted from EHRs, health information exchanges, claims data, etc. The main motive remains in interpreting the data to derive valuable insights, which will not only benefit health management, but also fuel business growth. This methodology is also being used to tackle mental healthcare data. Analytics is being used on community data, available in a centralized manner, to identify patients, with more vulnerability to certain mental illnesses. However, since complete information of patients is not always available in such centralized data platforms, inconsistencies in analyses remain. Read more at: http://healthitanalytics.com/news/mental-healthcare-big-data-warehouse-illuminates-care-trends

The first step in effective implementation of a health management initiative is stratifying patients according to the costs incurred by them, in order to properly target the healthcare programmes. It has been observed that the majority of healthcare costs are concentrated in a small fraction of the total patient population. Focusing on the healthcare of this fraction of patients, can greatly reduce costs for the entire population, while providing the appropriate care, valued by the patients and their families. Risk analytics incorporates claims and EHR data into risk scores, in order for health care providers to target their services efficiently. Read more at: http://healthitanalytics.com/news/population-health-management-starts-with-flagging-high-costs

Hadoop works on extracting voluminous unstructured data to interpret business performance, customer relationship management etc. Large business houses are at a distinct advantage in handling big data, but with features like Excel reporting in Hadoop, small businesses can also take advantage. Some salient features are:
1. Hadoop is being used with cloud storage platforms to expand storage capabilities.
2. Third party tools and add-ons help tighten up big data security, as big data security is vital.
3. Allowing big data processing through integration with IT systems.
4. Hadoop allows modifications, to extend functionality and accessibility.

To know more: http://www.business2community.com/big-data/hadoop-keeps-even-small-businesses-loop-big-data-analytics-01257559

Our computational capabilities required to handle human genome data will rapidly exceed those of Twitter and YouTube. Computer scientists are realizing that they are not equipped with the growing flood of genomics. Almost 2 Billion human genomes would have been sequenced by the year 2025 according to a journal - PLoS Biology. The data-storage demands for such data could add up to around to 2-40 Exabyte (1 Exabyte is 1018 bytes).  The journal states that Genomic data would outstrip YouTube's projected annual storage needs of 1-2 Exabyte of video by 2025. Storage however would only be a small part of the problem. The computational requirements for acquisition, distribution and analysis of genomics data could be even more demanding. Genomics furthermore lack the standards for conversion of raw sequence data into processed data. Read more at: http://www.nature.com/news/genome-researchers-raise-alarm-over-big-data-1.17912

Healthcare is perhaps the most valuable and personal data. The risk of data breach is growing as there have been millions of data breach cases. Health data stores are mostly held in on-site software solutions, or, at cloud services, where the data stores are managed by third party hosting providers. But since cloud is not immune to such attacks, this may not be the perfect solution. A recent report by sky-high networks shows that around 93 % of these cloud services pose a security breach threat to the healthcare organizations. Since it is an open source, the origin of the threat is sometimes hard to detect. Read more at: http://www.forbes.com/sites/danmunro/2015/07/06/healthcare-moves-to-the-cloud-but-is-the-cloud-ready-for-healthcare/

It depends on the enterprises' ability to find value in IOT generated data and come up with metadata fabric that enables efficient data analysis. Metadata fabric works in sync with IOT to benefit the enterprise. It can be viewed as the storehouse of business intellectual property. It makes data driven decisions a lot easier. Metadata fabric transforms unified interpretation of data and analytics into layman format and interface easily understood by businesses. IOT ecosystem often throws challenges as the number of unique data sets collected is smaller than the number of applications that need it. Introduction of an intermediate curation layer can solve this governance problem. The aim of the governance system should be to reduce onboarding cost with increasing chances of success. Optimization should also check for homogeneity in the collected data. To know more, please follow:

http://www.dataversity.net/data-governance-the-metadata-fabric-and-the-internet-of-things/