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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

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?

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Digital Twin Use Races Ahead at McLaren Group

CIO Business Intelligence

Meanwhile, the digital twin market is set to grow at a 50% compound annual growth rate, reaching $184.5 For businesses like the McLaren Group, these two trends are at the core of the conglomerate’s digital transformation and competitive strategy, on and off the track. . The data transmitted from each car during a race ?

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Trending Technologies for BI & Financial Planning and AnalysisMaking AI Real (Part 2)

Jedox

Part one of our blog series explored how people are the driving force behind the digital transformation and how it is fueled by artificial intelligence and machine learning. Analytic Evolution in Enterprise Performance Management. Advanced analytics responds to next-generation requirements.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

Combined, it has come to a point where data analytics is your safety net first, and business driver second. Enterprise Artificial intelligence (AI) is a common jargon used to refer to how an organization integrates artificial intelligence (AI) into its infrastructure to drive digital transformation.

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How to choose the best AI platform

IBM Big Data Hub

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.