Remove Descriptive Analytics Remove Forecasting Remove Risk
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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? In business analytics, this is the purview of business intelligence (BI).

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What Is The Difference Between Business Intelligence And Analytics?

datapine

While BI tells you what has happened in the past and what is happening now (descriptive analytics), BA tells you what will happen in the future (predictive analytics). Descriptive analytics : As its name suggests, this analysis method is used to describe and summarize the main characteristics found on a dataset.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. These may not be high-risk discoveries, but they could be high-reward discoveries. Pay attention!

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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

Prescriptive analytics is the area of business analytics (BA) dedicated to finding the best course of action for a given situation. By banking on prescriptive analytics, casinos can not only prepare and plan to take make the most of future opportunities but also avoid and tackle any impending risks and problems.

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How Freudenberg Home and Cleaning Solutions Makes Better Decisions with Enterprise-Wide Planning

CIO Business Intelligence

The company also wanted to improve forecasting accuracy by harnessing the power of intelligent technologies. FHCS integrated its landscape built on SAP ERP and SAP Business Warehouse with specialized forecasting in SAP Integrated Business Planning (IBP). This hampered the company from having an enterprise-wide view.

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

BizAcuity

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management.

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Disrupt and Innovate in a Data-Driven World

Cloudera

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques.