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Predictive vs. Prescriptive Analytics: What’s the Difference?

Dataiku

The bulk of an organization’s data science, machine learning, and AI conquests come down to improving decision-making capabilities. When during this process, though, should data executives get either predictive or prescriptive?

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. A lot has changed in those five years, and so has the data landscape.

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

Rocket-Powered Data Science

Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.

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

Rocket-Powered Data Science

The book Graph Algorithms: Practical Examples in Apache Spark and Neo4j is aimed at broadening our knowledge and capabilities around these types of graph analyses, including algorithms, concepts, and practical machine learning applications of the algorithms. Your team will become graph heroes.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

As I progressed in my career into management roles for enterprise data systems, I gained a deeper understanding and appreciation of the synergies and interdependencies between system and user requirements. Analytics products represent the user-facing and client-facing derived value from an organization’s data stores.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

Good data can give you keen insights, convincing evidence to make informed decisions. By observing and analyzing data, we can develop more accurate theories and formulate more effective solutions. For this reason, data science and/vs. Definition: BI vs Data Science vs Data Analytics.