An enterprise such as Flipkart & Amazon is the master at analyzing big data. They have a huge a knowledge gathered from analyzing big data to achieve an edge over their competitor. Just think about the Amazon’s recommendation engine. It analyzes the process of buying history, buying habits, and pattern what people like to buying. With big data and predictive analytics, they have to build a marketing strategy and created an extremely successful business model.

So these things should be upon your mind while knowing about the big data analytics because with a rise in computational power, robust data infrastructure, rapid algorithm development, and the need to obtain better insight from an increasingly vast amount of data.

Big Data Analytics: – Types

Explore Analytics It can be used to explore your data in a graphical manner where your data provides some value through simple visualizations. It often used when you have a large amount of disparate data.

Advance Analytics: It provides analytics algorithms for executing complex analysis of either structured or unstructured data. It also includes such as machine learning, statistical model, text analytics and other data-mining techniques.

Operationalized Analytics: Are the part of the business process that helps to achieve operational efficiency by building models. For example, a data scientist for a banking organization might build a model that predicts the identity theft of its customer.

Summary

The capability to analyze big data provides unique opportunities for many enterprises. However comprehending big data can be challenging. Due to algorithms & technologies, basic analysis becomes confusing. It depends upon the scale size which means how many you’re capable for that.

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