What is Big Data Analytics?

Big Data Analytics is the process of inspecting large pairs of data through different tools and operated in order to invent unknown patterns, closed correlations, meaningful trends, and other insights to implement data-based decisions in the pursuit of better results.

Big Data Types

=> Structured Data=> Unstructured Data=> Semi-structured DataThis process can be computed in the form of terabytes and more. However, Big Data sometimes can pass over petabytes. Structured data involves all the data that can be stored in a tabular column. The unstructured data is the data that cannot be stored in a spreadsheet; and semi-structured data is something that does not conform to the model of the structured data. Semi-structured data can be found similar like a structured data, but it does not support the flexibility with which you can do it on the structured data.

Types of Big Data Analytics

 

• Authoritarian Analytics: This is the process of data analytics that deals about an analysis, which is totally based on the rules and regulations, to prescribe a certain analytical path for the organization. At the immediate level, this analytics process will automate decisions and actions on how can I make it happen? Based on the past analytics, neural networks and statistics are applied to the data to recommend the best possible actions that can derive required outcomes.
• Anticipating Analytics: This type of data analytics process make sure that the way is predicted for the future course of action. By replying to the question about how and why questions will reveal specific patterns to detect when outcomes are about to occur. Anticipating analytics develops on the holistic analytics to look for these patterns and see what is going to happen. Machine Learning process is also used to continuously monitor and learn as new patterns emerge.
• Detailed Analytics: Under this data analytics, work is done based on the incoming data. For the extraction of this data, you need to deploy analytics and come up with a description based on the data. Lot of companies have spent years generating detailed analytics—answering the ‘what happened’ questions. This available data is precious, but only issues a top-level, rearview mirror image of the business performance. In Distinctive Analytics, many organizations start to apply Big Data Analytics to answer individual questions like how and why something happened. Some might also call these behavioral analytics.
• Distinctive Analytics: This data analytics is all about looking into the past and finding, why a certain thing happened. This type of analytics generally surrounds around working on a dashboard. Distinctive Analytics with Big Data assists in two ways: (a) the additional data brought by the digital age eliminates analytic blind spots, and (b) the how and why questions brings insights that highlight the steps need to be taken.