Remove Descriptive Analytics Remove Prescriptive Analytics Remove Risk Remove Statistics
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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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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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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Today, the most common usage of business intelligence is for the production of descriptive analytics. .

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Disrupt and Innovate in a Data-Driven World

Cloudera

Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. Identify those most at risk or most affected by a problem more accurately by using predictive analytics. The model has been shown to be effective in preventing the screening-out of at-risk children.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

The primary objective of data visualization is to clearly communicate what the data says, help explain trends and statistics, and show patterns that would otherwise be impossible to see. Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. Visualizations: past, present, and future.

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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 Embedded Analytics?

Jet Global

Positioning Embedded Analytics for Each Executive Here are some tips on understanding executives’ priorities and getting them on board with the project. Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles. It will help to eliminate some of the development risks.