The Energy industry is set to benefit largely from the usage of big data and analytics. Efficient use of information and improved analytics will help meet the difficult economic and environmental goals, bringing energy into the next century. For this we must update our energy infrastructure with the necessary software for collection and analysis of the required data. The potential of big data is such that it can help all customers support energy savings along with providing an environmental upside. Big data once employed correctly can improve operations for the benefit of businesses, customers and our environment. While the energy industry’s use of big data is future-focused, real progress is being made and these investments have improved operational efficiency and reduced the cost of energy all while helping protect the environment. Read more at: http://thehill.com/blogs/congress-blog/energy-environment/247559-big-data-means-big-energy-savings

Big Data is nowadays drastically affecting people's lives by its various uses. 1) With the growing population, infrastructure also have to grow. Hence, Transport for London (TFL) is going through a data-driven approach to increase the network access across England's capital city. This helps in informing people about alternatives when there are closures in a route. 2) With considerable growth, the necessity to plan proper waste management has increased. Greater Manchester Waste Disposal Authority (GMWDA) in UK collects data to increase the recycling level to move more towards a sustainable age. 3) Accuracy of weather forecasting is increasing with the help of big data using complex and more accurate devices. It still isn't perfect but is on the track to get that accuracy helping outside worker plan ahead of time. Read more about this article by Chris Towers (Big Data Divisional Head) at: https://channels.theinnovationenterprise.com/articles/big-data-in-real-time

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

In technology adoption, the healthcare sector is still lagging behind, due to its intricate compliance and security requirements. The healthcare sector has been mainly focusing on medicines, which is evolving continuously. However, the scenario is changing, as healthcare providers have started to compete for market share. Healthcare marketers are trying to identify prospective patients, most likely in need of their healthcare services and retain them in their institutional networks. Hence, predictive analytics is being applied to big data, in order to determine consumer behaviors and patterns in their operational areas, according to their healthcare service usage. Read more at: http://www.techrepublic.com/article/the-underexploited-big-data-sweet-spot-for-healthcare/

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

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/

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

• New business models are the next big opportunity

For an enriching account of each of them follow the link http://timoelliott.com/blog/2015/05/top-big-data-challenges-revisited.html

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

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

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

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/

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

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/

Healthcare is being revolutionized by the advent of big data. New gadgets and technologies are aiding this transition. A continuous stream of health related data promises us the concept of continuous healthcare. This data will enable us to study behavioral changes among patients and diagnose problems better and faster. Real time disease management is fast becoming a reality and it will be even possible to tend to patients in the early stages of their disorders and take steps accordingly. Real time monitoring of treatment efficacy will immensely help in post-operative care, drug therapy. It also holds the power to point out which patients merit additional intervention. Read more at:

http://www.dataversity.net/how-big-data-will-enable-continuous-healthcare/

Data science techniques are becoming increasingly popular these days to improve business outcomes. Hadoop, already showcased the broader use of big data technologies and their impact on businesses. In this new age, the limits of machine learning are constantly being tested as innovators are trying new techniques that decrease human intervention as much as possible. Companies are ready to work with the data they have in Hadoop. Penetration of SQL on Hadoop has been a great help as they have created an environment that has made data accessible to downstream apps and learning algorithms. Machine intelligence is catching up in all spheres, data science is becoming a new trend with data scientists coming in demand. To know more, please follow:

http://www.dataversity.net/predictions-for-data-science-over-the-coming-years/

Amalgamation of data, technology and marketing helps the manufacturing industry acquire new opportunities for earning profits. Data obtained from the customers are stored in various different systems like inventory, billing etc. And normally the manufacturers have to gather information from a common source thus having no competitive advantage in the market.
Industrial manufacturers are now gradually shifting from traditional marketing methods to data-driven ones so as to gain more prospects. Solutions such as Data-as-a-Service (DaaS) are influencing the Big Data ecosystem increasingly. It mines the appropriate data required from the Big Data sets. Patented Web Mining is also an effective and efficient way to find new prospects. Social media also actively helps in promoting the manufacturers.  Thus industrial manufacturers can increase their market share to a great extent by shifting to data-driven strategies.
Read more at: http://www.smartdatacollective.com/lbedgood/327457/how-manufacturers-can-use-big-data-acquire-new-customers

Many business have been extracting the benefits that come from applying big data as years go by. But there are still a few start-ups left who haven’t yet reaped its benefits. It’s crucial to know that now is the correct time to get into big data as it has considerably improved in the past few years. The reasons why big data should be employed now are:

• It keeps the data secure and all the sensitive data stay well protected in the system.

• It opens up brand new revenue sources and gives us a clear perception about the market which is very valuable.

• Big data provides an advantage of supplying better data which helps compete against others in the market when trying to innovate.

• It provides better visuals as well as it is very easy to set up big data in the business of any size.

• It helps the business expand and can efficiently cut down on maintenance costs.

• With big data employment, it’s easier to analyse the risk and create better improved products in the market.

• Lastly, big data improves company-customer relationships helping the business in every possible way.

Read more at: http://www.smartdatacollective.com/rick-delgado/323981/10-reasons-why-now-time-get-big-data

Data is the most important thing for marketing today and most marketers understand this pretty well. Simply collecting data won't help. It should be able to tell a story. Insights derived from data are very important. Data should be able to help marketers identify their customers and the appropriate offers for them. In an organization, every department holds some data on customers. The first task of the marketer is to get rid of data silos and gather all the marketing data at one place. Once this is done, robust analytics tools can be applied to the data to generate a singular customer view. Read more at: http://www.business2community.com/big-data/marketers-big-data-worth-01263023