Remove Predictive Analytics Remove Prescriptive Analytics Remove 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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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? This is the purview of BI.

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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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3 Things Citizen Data Scientists Need in Predictive Analytics!

Smarten

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Complete Set of Analytical Techniques. Descriptive Statistics. Trends and Patterns. Regression.

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

An analytics alternative that goes beyond descriptive analytics is called “Predictive Analytics.”. Predictive Analytics: Predicting Future Outcomes. While descriptive analytics are focused on historical performance, predictive analytics are about predicting future outcomes.

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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. Analytics, Data Science They emphasize access to and manipulation of a model.

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The Power of Graph Databases, Linked Data, and Graph Algorithms

Rocket-Powered Data Science

Chapter 1 provides a beautiful introduction to graphs, graph analytics algorithms, network science, and graph analytics use cases. In the discussion of power-law distributions, we see again another way that graphs differ from more familiar statistical analyses that assume a normal distribution of properties in random populations.

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