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What is data analytics? Analyzing and managing data for decisions

CIO

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Analytics 319
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AI & Business Analytics: A Smart Guide

Sunflower Lab

Diving into World of Business Analytics Data analytics is not an old concept, it is an essential practice which has driven business success in the past and the present, it will confidently drive the success in the future too.

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Re-Thinking the Storage Infrastructure for Business Intelligence

Infinidat

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

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Data Virtualization with Oracle Enterprise Semantic Models

Perficient

A common symptom of organizations operating at suboptimal performance is when there is a prevalent challenge of dealing with data fragmentation. The fact that enterprise data is siloed within disparate business and operational systems is not the crux to resolve, since there will always be multiple systems.

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Streaming Analytics in the Real World

Cloudera

From leading banks, and insurance organizations to some of the largest telcos, manufacturers, retailers, healthcare and pharma, organizations across diverse verticals lead the way with real-time data and streaming analytics. And Cloudera is at the heart of enabling these real-time data driven transformations. .

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What Is Cloud Analytics – And Why Should You Use It?

Datavail

Analytics is the process of turning raw data into valuable business insights through quantitative and statistical methods. There are three ways of classifying business analytics methods according to their use case: Descriptive methods examine historical data to identify meaningful trends and patterns.

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Quick Guide to Building an ETL Pipeline Process

The Crazy Programmer

It takes raw data files from multiple sources, extracts information useful for analysis, transforms it into file formats that can serve business analytics or statistical research needs, and loads it into a targeted data repository. Dedicate Specific Connectors and Extract Data from Available Sources.