Study of human beings is more complex than machines and so is the study of their data. It is important to make accurate decisions which decide life and death matters and thus require error free and credible data. Therefore apart from the 3Vs- volume, variety and velocity; healthcare data should also have veracity. As much as it is required, it is difficult since there are issues in the healthcare data - is the information furnished about the patient, drug prescription, disease correct? Also since the data is huge and frequency is also high.it is difficult to clean the data, thus magnifying the credibility issue. To know more, read the following journal at: http://www.hissjournal.com/content/2/1/3

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/

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

Over the last two years, Big Data and technological advancement have transformed the way industries operate and compete. Financial Services industry, in particular, has adopted big data analytics to inform better investment decisions with consistent returns. It is widely used by investment banks, asset management firms, insurance firms and stock exchanges, to name a few.

The Investopedia article by Trevir Nath, talks about 3 V’s of Big Data i.e. volume, variety and velocity, how they are applied by financial services industry, algorithmic trading and the challenges faced by this industry in the increasing embrace of big data. In the nutshell, this article explains that despite the challenges, the financial services industry is trending towards Big Data and Automation.

Read more at:

http://www.investopedia.com/articles/active-trading/040915/how-big-data-has-changed-finance.asp