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

Rocket-Powered Data Science

All of that “metadata” (which is simply “other data about your data”) enables rich discovery of shortest paths, central nodes, and communities. Incorporating context into the graph (as nodes and as edges) can thus yield impressive predictive analytics and prescriptive analytics capabilities.

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And the winners are…. Congratulations to the Sixth Annual Data Impact Awards winners

Cloudera

It was deeply gratifying to see so many organizations deploying the tools and techniques of data science and advanced analytics to solve difficult and important problems. I predict that next year’s competition will be even more amazing as we continue pushing the frontiers of data science forward.

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7 famous analytics and AI disasters

CIO Business Intelligence

But according to the UK’s Turing Institute, a national center for data science and AI, the predictive tools made little to no difference. That line of inquiry led to a predictive analytics project that would famously lead the retailer to inadvertently reveal to a teenage girl’s family that she was pregnant.

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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

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How to Choose the Best Analytics Platform, and Empower Business-Driven Analytics

Grooper

Choosing the best analytics and BI platform for solving business problems requires non-technical workers to “speak data.”. A baseline understanding of data enables the proper communication required to “be on the same page” with data scientists and engineers. Applied Analytics. Data science skills.

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How to choose the best AI platform

IBM Big Data Hub

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

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

Andrew White

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.