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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. What is the point of those obvious statistical inferences? How does that work in practice?

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What is the difference between business analytics and business intelligence? Prescriptive analytics: What do we need to do?

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

Focus on the technologies and engineering components: e.g., sensors, monitoring, cloud-to-edge, microservices, serverless, insights-as-a-service APIs, IFTTT (IF-This-Then-That) architectures.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis. However, businesses today want to go further and predictive analytics is another trend to be closely monitored. 4) Predictive And Prescriptive Analytics Tools.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

They generally leverage simple statistical and analytical tools, but Power notes that some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems. Commonly used models include: Statistical models. Forecasting models. Analytics, Data Science Optimization analysis models.