Top 5 Misconceptions about Big Data

Big data is a big deal in today’s world of technology. According to the IDG Enterprise 2016 Data and Analytics Survey, over 70% of businesses agree that big data has the potential to fundamentally change the way they do business and create new revenue opportunities in the next one to three years, while 53% of companies are currently implementing or planning to implement data-driven projects within the next 12 months.

Everyone is talking about Big Data. But what exactly is it and how does it work?

Though the term is widely used and accepted, there is still no rigorous definition, which leads to serious misconceptions about what big data actually is.

Big Data is about Data

Surprisingly, it is not. Instead, it is about how you manage it. Simply collecting and storing data in large volumes, or even analyzing it, is not enough. In fact, Big Data is about how you use the information you get from your data, the business value you add, the processes you improve, the decision making you enable. Data per se has no inherent value; smart interpretation and implementation is what makes big data projects valuable.

Big Data is Massive Data Volume

This is only partly true. Big Data has three main aspects, known as the three Vs: Volume, Variety and Velocity. Although Volume is definitely important, Big Data is mostly characterized by another two Vs, where Variety refers to a wide range of data types and sources and Velocity refers to the speed at which vast amounts of data are being generated, collected and analyzed.

Some experts include one more “V” to this list: Value. Actually, it may be the most important aspect of big data that means that huge volume of data has low capacity of knowledge. Big data can deliver value in almost any area of business or society delivering quality analytics, boosting performance and optimizing processes, but we should separate the wheat from the chaff first, adds Oleg Dyrdin, Auriga’s Big Data expert.

Big Data is better than Little Data

Not necessarily true. More is not always better, especially when quality is critical. A huge quantity of information usually has to be sorted and organized to fit within analysis parameters, while little data, which is simply a smaller data set, is often cleaner and more controlled – and, therefore, more valuable and effective.

Big Data is for Big Businesses

Yes, but not only. Big Data technologies are applicable to almost every industry, because most organizations, including smaller ones, produce enormous amounts of data. In the future, large companies will be the primary driver of the big data and business analytics opportunity, generating revenues of more than $154 billion in 2020. However, according to IDC, small and medium businesses will remain a significant contributor.

Big Data is the Answer to All Questions

Unfortunately, this is a myth. Big data cannot answer everything with the push of a button. There is a need for asking the right questions and special algorithms for data analysis. Thus, human input is still needed to decide what data to use, how to sample it, how to integrate it with complementary data sources, and how to implement it to a particular business case.

Yuri Kirkel, Auriga’s Executive Vice President, comments:

Big Data is not “coming soon.” It’s here today and it has brought both drastic changes and unprecedented opportunities to businesses of every scale across all industries. While IT professionals are more focused on revising the traditional rules for how and where data is stored, managed, and processed, market players, reluctant to waiting, are trying their best to commercialize the existing solutions – more or less efficiently. However, one industry is gaining momentum right now: healthcare is enjoying hidden treasures related to big data analytics. Excited by the variety of opportunities Big Data offers, we at Auriga has recently developed a Big Data solution for remote cardiomonitoring, accessible for thousands of patients. I hope our readers will get some insights from the created video and have some fun.