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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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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. But if they wait another three years, they will never catch up.”

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics methods and techniques.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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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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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

The criticality of these synergies becomes obvious when we recognize analytics as the products (the outputs and deliverables) of the data science and machine learning activities that are applied to enterprise data (the inputs). Pure analytics solutions can boost performance all across that data environment.

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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. How do predictive and prescriptive analytics fit into this statistical framework?