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The first question that comes to one’s mind is, what exactly is in-depth analytics backed by big data? The process of exploring wide-ranging and huge data sets in order to find hidden patterns, trends in the market, unidentified correlations, customer preferences and any other information that is useful for the organization or an individual is called big data analytics. All this information is used by organizations so that they can make decisions that are more informed in the future.

History of Big Data Analytics

Before delving into the benefits of analyzing big data, it is important for you to know what exactly big data entails.

The term “big data” was first coined in the mid-1990s while referring to the ever-growing volumes of data. The definition of big data was further expanded in 2001 by Doug Laney who was working at Meta Group Inc as an analyst. He included the increase in the types of data that organizations have been generating and the speed of the creation and update of data by the companies. You check below image or alternative visit to find trusted tools and media software.

Big Data Analytics

Hence, now the comprehensive definition includes three things: variety, volume and velocity. These three things are also known as the 3 Vs of the big data. This concept was popularized by Gartner who had acquired Meta Group and had Laney as his employee by 2005.

What Is the Benefit of In-Depth Analytics Backed by Big Data?

Big data analytics are driven by specialized software and analytic systems and can find out and point the direction in which a company can go in order to achieve utmost business benefits. The benefits include but are not limited to having an advantage over the competitors, betterment of customer services, new and improved opportunities to get revenues, improvement of the efficiency of operations, and more efficient and effective marketing.

In-depth analytics backed by big data applications let data scientists, statisticians, predictive modelers, and several other professionals to study the ever-growing volume of various kinds of data, including transaction data that is structured, which is mostly left undiscovered by the traditional BI (business intelligence) and various other analytic programs.

If in-depth analytics backed by big data is observed on a larger scale, it can be seen that they provide the users a way to analyze data sets and draw conclusions from them, which can be very beneficial. This gives organizations the power to make more informed and better business decisions.

Where the business intelligence can provide answers to only the most basic questions about the performance and operations of the business, in-depth analytics backed by big data can be considered an advanced form of analytics that provides an in-depth analysis from various features and complex applications having features like what-if analysis, statistical algorithm, and predictive models. These elements are backed by a high-performing analytic system.