Big data analytics are easy to gain acceptance. It is enhancing sales and becoming more competitive. Not only having to store their large quantities of data, but they also want to turn the data into useful information that can help grow their companies. Big data analytics allows businesses to raise sales, reduce costs and become more competitive within their industries. Most businesses make large investments in Big Data analytics. If IT professionals want to stay relevant within their businesses, they need to familiarize themselves with Big Data Analytics. What is Big Data Analytics? Big Data Analytics is a comprehensive method of analyzing massive data sets using a variety of tools and processes to uncover unknown patterns, hidden associations, concrete trends, and other insights to make data-driven decisions in search of better outcomes. Big Data is one of the most important conversations today between market leaders and industry captains. Today we live in a digitally powered world, because of which every organization goes after Big Data to extract useful insights from the enormous amount of raw data. Big Data Types Big data is calculated primarily by the volume of the data. But in addition to this, Big Data also requires data coming in quickly and at large varieties. There are primarily three Data types: Structured Data Unstructured Data Semi-structured Data The Structured data can be stored in a column in tabular form. Examples of structured data are Relational Databases. Taking the meaning of the relational databases is simple. Most modern computers may give sense to structured data. Unstructured data is the one which can’t be processed in a computer. Unstructured data comprises audio, video, and other data kinds that today form such a wide chunk of Big Data. The Semi-structured data contains structured as well as unstructured data. This type of data sets has a proper structure, but due to certain limitations, it may not be possible to sort or process the data. This form of data includes XML, JSON, and other data. The importance of big data analytics: Big data analytics is driven by specialized analytics systems and applications, as well as high-powered computing systems like: Giving you new revenue opportunities More effective marketing Better customer service It improving operational efficiency Competitive advantage over rivals Benefits of Big Data Analytics Business Transformation: Many executives feel that the analytics of big data provides enormous potential for revolutionizing their organizations. Innovation: Big data analytics will help businesses create products and services that cater to their consumers, and help them find potential revenue-generating opportunities. Lower Cost: As a result of a big data initiative, you will see the expenditures decrease effectively. Improved Customer Service: Better Customer Service Organizations also use big data analytics to analyze social media, customer care, sales and marketing details. This will help them gauge consumer sentiment better and in real-time react to customers. Increased Security: IT security is another important field for big data research. A large amount of log data is generated by the security program. Organizations may also detect and thwart cyberattacks that would otherwise have gone unnoticed by applying big data analytics techniques to this data.