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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. The discipline is a key facet of the business analyst role. Business analytics techniques.

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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

The types of data analytics Predictive analytics: Predictive analytics helps to identify trends, correlations and causation within one or more datasets. Healthcare systems can also forecast which regions will experience a rise in flu cases or other infections.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

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What Is The Difference Between Business Intelligence And Analytics?

datapine

We already saw earlier this year the benefits of Business Intelligence and Business Analytics. In an article tackling BI and Business Analytics, Better Buys asked seven different BI pros what their thoughts were on the difference between business intelligence and analytics.

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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. Now that we have described predictive and prescriptive analytics in detail, what is there left?