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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. Now that we have described predictive and prescriptive analytics in detail, what is there left?

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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. One group has declared , “IoT companies will dominate the 2020s: Prepare your resume!”

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

The criticality of these synergies becomes obvious when we recognize analytics as the products (the outputs and deliverables) of the data science and machine learning activities that are applied to enterprise data (the inputs). Pure analytics solutions can boost performance all across that data environment.

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Want to Drive Industry Breakthroughs or Speed Up Innovation? Start by Optimising Your HPC and AI Workloads

CIO Business Intelligence

Artificial Intelligence (AI) is fast becoming the cornerstone of business analytics, allowing companies to generate value from the ever-growing datasets generated by today’s business processes. Optimising HPC and AI Workloads.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 4) Predictive And Prescriptive Analytics Tools.

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What is a Data Pipeline?

Jet Global

Real-Time Analytics Pipelines : These pipelines process and analyze data in real-time or near-real-time to support decision-making in applications such as fraud detection, monitoring IoT devices, and providing personalized recommendations. For example, migrating customer data from an on-premises database to a cloud-based CRM system.

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Announcing the 2021 Data Impact Awards

Cloudera

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. Data for Enterprise AI: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning.