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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? 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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Skilled IT pay defined by volatility, security, and AI

CIO Business Intelligence

This volatility can make it hard for IT workers to decide where to focus their career development efforts, but there are at least some areas of stability in the market: despite all other changes in pay premiums, workers with AI skills and security certifications continued to reap rich rewards.

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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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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.