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Big Data Managed Analytics

Big Data analytics is a process used to extract meaningful insights, such as hidden patterns, unknown correlations, market trends, and customer preferences. Big Data analytics provides various advantages—it can be used for better decision making, preventing fraudulent activities, among other things.

Types of Big Data Analytics we offer

Descriptive Analytics

This summarizes past data into a form that people can easily read. This helps in creating reports, like a company’s revenue, profit, sales, and so on. Also, it helps in the tabulation of social media metrics.

Diagnostic Analytics

This is done to understand what caused a problem in the first place. Techniques like drill-down, data mining, and data recovery are all examples. Organizations use diagnostic analytics because they provide an in-depth insight into a particular problem.

Predictive Analytics

This type of analytics looks into the historical and present data to make predictions of the future. Predictive analytics uses data mining, AI, and machine learning to analyze current data and make predictions about the future. It works on predicting customer trends, market trends, and so on.

Prescriptive Analytics

This type of analytics prescribes the solution to a particular problem. Perspective analytics works with both descriptive and predictive analytics. Most of the time, it relies on AI and machine learning.

IOTASCALE's approach to Big Data Managed Analytics

Big data increases constantly – including social media, emails, texts, sensor data and more. With natural language processing, machines can sift through volumes of big data to uncover trends, analyze sentiment and identify correlations.

Big Data as a Service (BDaaS) integrates many of the functionalities and benefits of SaaS, IaaS, PaaS and DaaS, and leverages additional resources in the market for analyzing Big Data. Work with IOTASCALE to connect with data from providers to efficiently derive business insights.

Build Analytics with iotascale.io

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