Data analysis conventionally involves a series of process of collecting data from several sources and then analyzing them after some time. Normally these data come with a expiry time i.e. there is a specific short time by which these data needs to be analyzed, processed and utilized. With development in IT world we can no longer wait for data to be collected and then analyzed and processed. The need of the moment is to shift the Big Data nearer to the data source. Thus the value obtained from the data is more important than the way it is collected. Read more at: http://www.tibco.com/blog/2015/04/14/data-analytics-how-to-be-advanced-pervasive-and-invisible/

At Paris Air Show 2015, Bombardier plans to bring its CSeries jetliner that carries Pratt & Whitney’s Geared Turbo Fan (GTF) engine which uses great swathes of data. But data created by industrial equipment such as jet engines, gas turbines and MRI machines has more potential business value on a size-adjusted basis which makes it valuable than other types of big data being generated from the social web, consumer Internet and other sources. Finally, the Internet of Things is helping manufacturers manage their Pay by Hour engagement models and long term maintenance contracts at lower costs. With rapid advancements in the Internet of Things in aircrafts combined with data analytics, it’s truly exciting to work in the aerospace industry. Read more about this interesting article at:  http://channels.theinnovationenterprise.com/articles/7319-analytics-and-the-internet-of-things-in-aerospace

The big data has penetrated into healthcare. But merely collecting the patient records and keeping them in the form of electronic health records (EHR) is not enough. It starts with using programming software languages like R to sort through the huge database. R is an open source programing software used for statistical computation and data mining. In this case, R can be used to interpret the EHR for different purposes like side effects associate with a particular drug among a typical set of patients with similar records and could also help identify what causes the side effect. R can be customized according to the needs of the patient and the physician and thus can be helpful in providing personalized healthcare .Also, since R is open source software, it involves no cost and a large amount of documentation is available to learn the language. Read more at:http://www.healthcareitnews.com/blog/radical-potential-open-source-programming-healthcare 

Self-learning machines need data to learn. So one possible way to get the data that is being generated from all the devices being used across the world is IoT-Internet of Things. Devices communicate with each other and are interconnected through various networks. This could help advance many fields especially medical field. But a standard protocol has to be developed for devices to communicate with each other. It was proposed that the protocol should take care of safety of humans, security of IT infrastructure.

To read more, follow: http://www.v3.co.uk/v3-uk/analysis/2410409/big-data-and-iot-powered-self-learning-machines-wont-take-over-the-world

Need a big data solution for your project? The 3 V's of big data will bail you out. In an article by Paul Holland (Consultant), he talks about the 3 V dimensions of big data initially discussed in 2001 by META group (now Gartner) analyst Laney Douglas in a research report. Fourteen years hence, big data challenges and opportunities have acquired 8 V dimensions. The author exclusively focuses on the 3 V's:

• Volume
• Velocity
• Variety 

Volume talks about zettabytes of data generated every second. For example, if we look at airplanes they generate 2.5 billion terabytes of data every year. Velocity is about the speed with which data moves around. Unlike earlier times, data is created in real time or near real time. Variety is basically the different types of data. Gone are the days when data used to fit neatly in tables. Today 80% of world data is unstructured (text, images, videos, voice etc.). Read more at:http://makingdatameaningful.com/2015/05/26/characteristics-of-big-data-part-one/?utm_source=rss&utm_medium=rss&utm_campaign=characteristics-of-big-data-part-one

Each human is unique in his own ways. For treatments to be effective, it can't be based on what the averages are. "Biotech has progressed to the point where we're actually able to edit or code DNA …," said Andi Karaboutis, Executive VP of Biogen, who was detected with Greaves disease a decade ago and undergoing iodine ablation treatment. The doctors then did some stratification to the normal range to suit her body needs and within three weeks she was back to normal. "Internet of me", the combination of computing power and health research, can lead to treatments being personalized improving the healthcare benefits. Read more at: : http://www.informationweek.com/strategic-cio/executive-insights-and-innovation/the-internet-of-me-is-getting-real-in-healthcare/d/d-id/1320348?

Digital media publishers have taken their time to incorporate big data tools into their businesses. There have been marked improvements in clarity on use cases for big data and toolsets have also grown accordingly. Big data helps in the content creation side catering to the readers and the advertisers. Keeping the target audience in mind,big data tools optimizes decisions and effectively monetizes generated traffic. Relying on editorial expertise and sound journalistic judgements are fast becoming things of the past. However web analytics softwares like Google analytics, Webtrends also help in tracking content consumption patterns.To know more, please follow:

http://www.dataversity.net/big-data-tools-for-publishers/

Providing good customer service is a challenge for most businesses and the trends are ever changing. Customers embark on an online journey whenever they buy something. The customer data - a string of emails, conversations across the web and social channels, leave a large digital footprint. Measuring and analyzing this information can help brands narrow down their marketing efforts and investments. Irrespective of the nature of the website, sentiment analysis is crucial. It can tell you whether your customers are frustrated, indifferent, or impressed and suggest measures to that accord. Monitoring customer engagement, referral traffic and time spent on pages can help in understanding the buyers’ journey. Thanks to Big Data, we can work based on intelligence rather than guesswork. Read more at: http://www.forbes.com/sites/danielnewman/2015/06/09/big-data-and-the-buyers-journey-measuring-the-invisible/

In coming years, Data generated by IOT devices are predicted to increase more than the available capacity to store, and all data that's generated is not useful for analysis. Only limited part of it is useful. 

According to Computer Business Review(CBR) magazine, there are some data generating areas. It is important to know what data from which area is precious and what is not. Following are the ten of the biggest data generating areas. To know more about these areas, read: 

http://www.cbronline.com/news/internet-of-things/10-of-the-biggest-iot-data-generators-4586937

Companies are collecting datasets to have a competitor advantage in the market. But what exactly are they doing with the collected data? And how are they dealing with the ever increasing data that is inrushing their servers or storage units? 

To answer any of above question, we need to know about a process called Data Mining. Data Mining is a process used to analyze raw information to try and find useful patterns and trends in it. Basically a data miner’s job is to make some sense out of the huge pile of data that is available. There are a lot many techniques available to do this. If you want to know more about data mining and these techniques go through: http://www.businessnewsdaily.com/5947-data-mining.html

Big Data is growing bigger and bigger every day.

But, as it is growing, it is also becoming more complex. And complexities usually lead to discrepancies in interpretation of same information. As it is said that, “Prevention is better than cure.” Similarly, identifying these discrepancies and the reasons behind them at an early stage is better than allowing them to become a bigger problem.

Lisa Morgan, Freelance Writer, in her presentation at Information Week, has pointed out six major causes behind big data discrepancies. They are:

• Same Data, Different Quality
• Data-Cleansing Issues
• Problems with the Algorithm
• Models Differ
• Model Complexity Differs
• Interpretations Differ

To understand them in detail, please visit the following link:

http://www.informationweek.com/big-data/big-data-analytics/6-causes-of-big-data-discrepancies/d/d-id/1320692

Big Data, one of the prevailing trend has changed our mind-set about Internet and other Technologies. The five keys to get an idea of the reach of Big Data are: 1) the amount of Data transmitted through an optical fiber doubles every nine months. 2) The number of cellphones in the world is now equal to the number of people thus becoming the fastest adopted technology ever. 3) Facebook has 1.3 billion active users and one hundred hours of video are uploaded to YouTube every minute 4) The number of IP-enabled sensors are increasing 5) 90% of the world's stock of data was generated in the past two years. Thus, Big Data has many applications in the business world. Read more about this article at:  https://www.bbvaopenmind.com/en/5-data-about-big-data/?utm_source=facebook&utm_medium=techreview&utm_campaign=MITcompany&utm_content=5bigdata 

In the present scenario, the retailers who are combining customer analytics, internet of things (IOT) and data innovation to retrieve and analyze data of consumer preferences, are generating the maximum sales. Others are losing out. Customers now-a-days are well aware of their personal data being collected online by firms and hence expect better retail experience in return. That will only be possible when customers are segmented and served, which is done by analyzing their personal data, using data analytics. Big data can also be used in framing a product's optimal price system and inventory management, according to the prevailing or to be prevailed customer preference trends. Read more at:

http://channels.theinnovationenterprise.com/articles/grasping-the-value-of-data-analytics-in-retail

A famous chain that oversees the operation of 514 restaurants across the US, has found a way to integrate Big Data with Business Intelligence Services. The system works on data from point-of-sale, marketing, promotions and customer surveys to provide feedback on sales in real time. This not only helps them maintain a competitive edge, but also maximize profits. Big Data was used to select which item to put on the restaurant's menu too. After evaluation of sales, simplicity of preparation, profitability, quality and brand. Only once they met the required target, were they made permanent on the menu of that restaurant. Read more at: http://www.forbes.com/sites/bernardmarr/2015/06/02/big-data-at-dickeys-barbecue-pit-how-analytics-drives-restaurant-performance/

According to Scott Langfeldt (Teradata) “Big data is changing the way the world works- By combining with faster processor speeds and innovative analytic tools- helps in detecting fraud, part failure, and churn.”
For implementing big data and analytics into the company- analytical, business and IT departments need to work together. But they usually have differences.
Scott Langfeldt (Teradata) discussed some ways to solve these differences:
• Categorize your business and mission critical process.
• Make sure that flexibility is built into “business critical” process.
• Create a partnership between the IT developers and analytical teams.
• Develop “business solution” specialist on the analytic team.
• Develop “analytical experts.”
To know more about these ways, follow this link: http://www.forbes.com/sites/teradata/2015/06/02/avoiding-the-drift-into-analytics-oblivion-turning-your-business-into-an-analytics-driven-one/

With the advent of Big Data and technologies that can handle data in real time, Big Data is now reshaping the landscape of security with radical changes in the analytics methods being used. While most security specialists admit that perfect protection is not possible, using Big Data can help in increasing the prediction accuracy of attacks. Generating data for each user signature for example and storing them in NoSQL databases made them scalable. The motivation was to allow relocation of security information and improved monitoring for systems. As companies move from descriptive analytics to predictive analytics, the scope of Big Data in security greatly increases. Read at: http://www.techrepublic.com/blog/big-data-analytics/how-big-data-is-changing-the-security-analytics-landscape/

Rolls Royce, a company that is a leader in the manufacture of engines that generate large amount of power in a high-tech industry has begun to look for Big Data solutions to increase profits and reliability. Its engines and machine parts are fit with scores of sensors that monitor their operation and detect change in real time. Royce now employs Big Data in design, manufacture and after-sales crunching of data. With over 3TB data generated per manufacturing component a year, there is no doubt that there is a need for integration of Big Data. Read more at: http://www.forbes.com/sites/bernardmarr/2015/06/01/how-big-data-drives-success-at-rolls-royce/

The new thing about big data is that, the cost of getting the three V’s namely, Volume Velocity and Variety has become very cheap nowadays. So as we consume data, it influences us. In the past, we weren't very much concerned about being caught by camera but today’s surveillance of the whole population, makes us realize about the sensors around us. Crowd-funding sites are a treasure of such smart censored things. The evolution of data collection in a world where every output is also an input poses immense technical and ethical challenges. But it’s also a massive business opportunity, changing how we build, maintain, and recover almost everything in our lives. Read more about this article at:  http://radar.oreilly.com/2015/01/the-promise-and-problems-of-big-data.html?cmp=tw-data-na-article-stca15_72724

The increasing amount of data available to retailers, are giving them quite a sweat, when it comes to extracting the required data from such a large pool. Big data yet again proves to be the savior of the day. Big data helps in segregating consumers, and sending them promotional offers on the basis of their purchasing patterns and location, thus improving 'customer opinion' in the process. It has been observed that customers, now-a-days are increasingly doing online study about their desired product before making the final purchase from offline stores. Big data integrates this data along with the data of actual purchases, including the location of the purchase, to filter the segregation of customers and give them better service. Read more at:

http://channels.theinnovationenterprise.com/articles/using-big-data-to-improve-consumer-sentiment

According to Marge Breya (CMO and Executive Vice President of Worldwide Marketing and Informatica Education), “data is the fuel powering business processes, machines, sensors and customized user experiences.” Using data in marketing gives you a competitive advantage. Some basic steps for making data driven marketing team: firstly, identify a person who has knowledge about data analytics within and outside the organization. Secondly, to create a data driven culture, find a leader. Thirdly, a leader needs to create an environment where their marketing team feels safe in becoming data literate. And to solve the problem of “how to make a data literate team,” use education, exposure and practice. Read more at: http://www.computerworld.com/article/2928800/big-data/how-to-create-a-data-driven-marketing-team.html