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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.

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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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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. See: Tool: A Living Library of Real-World Data and Analytics Use Cases. We do have good examples and bad examples.

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What Is Embedded Analytics?

Jet Global

Advanced Analytics Some apps provide a unique value proposition through the development of advanced (and often proprietary) statistical models. These advanced analytics become easy for users to apply in their own analyses. Metadata Self-service analysis is made easy with user-friendly naming conventions for tables and columns.