Most companies are deriving benefits from open source software's, as numbers of programmers and developers are provided access to the source code. This has helped employees gain domain expertise through collaboration. Open source brings higher visibility and better business opportunities. The reasons for growing prominence are:
1. Intellectual property concerns no more hindering the use of open source.
2. Enhancing reach and learning of the community by diversity of thought and better technique.
3. Providing better opportunities for interoperability between competing firms.
4. Increase analytics penetration.
5. Demonstrating technical ability, where ability to think innovatively can be measured by a potential customer.
To know more: http://bridgei2i.com/blog/why-open-source-is-important-to-analytics-industry/

Big Data Analytics which is nowadays so useful in sports, also couldn't save England cricketers during their recent World Cup match against Bangladesh. The then coach of England, Peter Moore started believing in numbers more than the spirit of the cricketers. But a great-turnover came up over the team when they defeated New Zealand in a series of one-day match by 3-2. Both teams broke one-day records and entertained the English cricketing public like never before. This wasn't done by analysis of numbers but by abilities of cricketers. Thus, Big Data is all-time powerful but can never be more than what human spirit is. Same example goes for recruitment. Read more about this article by Matthew Reaney, Director and Founder (Big Cloud) at: https://channels.theinnovationenterprise.com/articles/big-data-and-the-human-spirit

Some of the unconventional ways in which Internet of Things (IoT) creates economic and social value are by detection of earthquakes in hospitals and alerting the administration for evacuating patients, reporting and assessing severity of car crashes and thus helping the victims to get help faster.
Certain examples that show how IoT is integral to several industries:
• The era of “Agriculture 3.0” was characterized by farmers whose decisions about what crop to plant and when and where to plant them was based on analysis of sensor data, weather data and other factors. This form of farming helps increase the yield in a cost and resource efficient manner.
• European airplane manufacturing company uses scanners In airplane assembly lines in order to send required information to robots who then finish the work accordingly.
• Internet of Things is used in Restaurant business for ensuring data-driven quality control.
With decreasing cost of connected devices, the scope of IoT will keep increasing in the future.
Read more at: http://www.smartdatacollective.com/joshua-new/329188/internet-ordinary-things-still-extraordinary

There had been a misconception that discovery analytics is hacking. Every discovery process involves going through some data, analyzing it, making some conclusion. So why would some people judge it as Hacking? Highly prioritized business problems that occur in mind led to discovery process. After having some discussion the major component which addresses the problem is analytics. Analytics brings up the new ideas that could be solution to the business problems. One can have analytics as the strategic component of his business; just the requirement is that he has to invest in analytics like other components say core products and services that his company provides. Discovery analytics cannot be considered as hacking than any other research and development activities are. But truly speaking both of them are the same. The products sold in the market have to go through some background processes that are invisible to buyers. Huge investment, many trials and experiments are required to get a finished product. Discovery analytics are much similar to that. Not all attempts will give appropriate results, but if choosing the right doors it will result in high level of strategic value. Most of the people are familiar with R&D because it is viewed as rational, scientific, disciplined approach to developing new ideas and products. An analytics R&D function can be built just by letting few number of human and technology resources to address only a few critical business problems. When you get positive results, apply it to more number of problems. If every thing goes in right direction then we will get a stable and well functioning analytics research and development function. Read more at:http://www.smartdatacollective.com/billfranks/329559/discovery-analytics-it-s-not-hacking-it-s-rd

Data management has become the epicenter of success model for any organization. Human beings are generating huge amount of data everyday but most of the data is in unstructured form. The need to effectively manage data and create new flexible systems for effective integration of data across all databases is the need of the moment. Junk records, duplicate records and outdated records have only added to the costs of the organization and success for any organization will be how effectively its employees are able to create and manage the data on regular basis. The duty of cleaning up the data is often imposed on the IT department but they are just the gatekeepers and it is the employee who needs to take care of his or her data, be it a clerk, manager or even the CEO. To know more:

http://it.toolbox.com/blogs/insidecrm/why-is-data-so-difficult-to-control-68067

The amalgamation of big data and analytics isn't enough to deliver insights especially in the area of pricing and margin optimization. In this competitive world, every company strives to be better than the other and some have already gone ahead to boost sales and margins by using levers. Here are five important tips to ensure an improved pricing and margin optimization. They are:

•  Increased focus on revenue management rather than on pricing and promotions.
•  Hiring outstanding candidates and having a more effective organizational structure.
•  Adopting decision based data management techniques.
•  Choosing or designing tools using easy-to-use solutions that are understood by all.
•  Having dedicated leaders who can drive all others team to achieve an insight-driven leadership.

Read more at: https://channels.theinnovationenterprise.com/articles/7715-it-takes-more-than-big-data-to-get-pricing-and-margin-optimisation-right-for-your-business

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/

Evidences showed that recruitment have not been so easy during past years. Recruiting new employee requires a huge investment for most companies, specifically in managerial or professional role, which absorbs large proportion of company’s revenues. In the presence of big data, planning and strategies can improve recruitment process. US financial services company used big data analytics to examine the performance of employees. What they observed was that top performers were mostly those who had higher education. Office equipment manufacturer Xerox used analytics to study the performance and profile of candidates recruiting for its call centers which reduced the staff turnover of 20%. Big data is attracting employees and with the help of some tools such as Cornerstone and TalentBin (tools to crunch data) made it easier to find candidate for the right position. Online recruitment services are also enjoying the benefits of big data. Say for example it made easier to look at what are the areas of interest, average spending, experience, location of service. So, it is easier to plan ahead and prioritize. Read more at:

http://www.smartdatacollective.com/bernardmarr/327498/how-big-data-changing-recruitment-forever

Today, enterprises have come a long way dealing with the big data challenges. But there are more to go. Revisiting a few of them would help understand the task ahead. Timo Elliott, innovation Evangelist for SAP, in his blog Business Analytics talks extensively about the following 5 challenges:

• There’s still a lot of technology to learn

• The right people are still hard to find

• The right business case is key

• Integrating with existing systems is more important

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

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

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

Employment of analytics professionals into the marketing world goes far behind the usage of visualization techniques and data processing. Marketing enterprises are keen on hiring data and analytics professionals. It's a well-recognized fact that analytics not only help companies to take profitable decisions but also provides them with opportunities to build strong relationship with customers, increase sales volume etc.  Daniel Kehrar (VP Marketing, MarketShare) in his article on Forbes listed out the five ways in which brand marketers can innovate with analytics and they are as follows:

1. Use insights to enrich what you offer.

2. Perfect your programme.

3. Eliminate digital and channel silos.

4. Be predictive.

ITOA or IT operations analytics is a recent entry to the field of analytics. ITOA automates the process of collecting, organizing, and identifying patterns in highly distributed, diverse and fast-changing service and application data to identify problems faster and improve IT system performance. IT Operations Analytics can be applied to the modern IT Infrastructure and Operations environment. What it exactly does is that it Collects, index and monitor logs and events for abnormalities, perform ad-hoc searches of all log data across the entire IT environment from a single console and correlate log data with events and service models, or application groups. This helps in detecting and resolving service issues more quickly than ever before. Read more at: http://insidebigdata.com/2015/06/09/it-operations-analytics/

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/

Big Data may be relatively new but data has been a hot topic of discussion for over a 100 years. Interesting to note, the challenges in fetching and understanding it remain fundamentally the same. We are told that this is the era of Big Data but its roots go back to 1914. Willard Brinton wrote the first book on communicating data, Graphic Methods for Presenting Facts. He had stated that those who possessed cutting-edge data technologies would be the pioneers in their field. Processing and visual representation of data as information would allow us to give just the required information and facts to allow those who aren't proficient in data, actionable insights into their problems. In 100 years more, we would hopefully understand analytics and effective data visualization. Read more at: http://www.computerworld.com/article/2942728/big-data/big-data-the-100-year-old-buzzword.html

Although most modern enterprises run on data, it becomes useless if we cannot derive intelligence from it. Data includes all the information that is available including raw facts about companies and individuals. Intelligence is when we look at the data and try to find a relation to better interpret challenges and opportunities in the market. Insight with data and intelligence deals in adjusting strategies in response to the market. To develop predictive models about the market, we need intelligence and insight alongside data. Raw data is often mistaken for insights. For smarter decisions, internal and external data sets should be used as starting points and then create intelligence to draw sensible insights. To know more:  http://www.smartdatacollective.com/ray-renteria/327508/data-does-not-equal-intelligence-predictive-analytics-enterprise

Industries are flooded with data and this data can be used to extract a lot of money if only we knew how to use it. With the rapid advancement of technology, we have high-speed networks and improved algorithms for analytics. Various industries including healthcare and financial services are basically resting on terabytes of valuable data and information. Six best methods for monetizing data are as follows:

1. Building up trust and neutrality among the customers.
2. Anonymization and aggregation of data is required.
3. To acquire permission of utilizing the data that is not owned by the company.
4. To consider spinning out the data monetization unit.
5. Provision of data analytics in real time.
6. Furnishing customers with self-service capabilities.

In order to know more about data monetization, please follow the link: http://www.cio.com/article/2941291/big-data/memo-to-cios-cash-in-on-that-data.html

Cloud has changed the dynamics of data analytics. It is believed that in the coming five years, organizations will be spending more on cloud based big data and analytics solutions than on the on premise solutions. Dave Wang, senior product marketing manager at Databricks, lists down 5 major reasons why data analytics in cloud is becoming a top priority for organizations trying to build a competitive edge through analytics. To know which among them has an upper hand and why, follow the link http://insidebigdata.com/2015/05/08/5-reasons-data-analytics-in-the-cloud-will-take-center-stage-in-2015/