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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

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Highlights from the Strata Data Conference in San Francisco 2019

O'Reilly on Data

Watch highlights from expert talks covering AI, machine learning, data analytics, and more. People from across the data world are coming together in San Francisco for the Strata Data Conference. The journey to the data-driven enterprise from the edge to AI. Data warehousing is not a use case.

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

The way that I explained it to my data science students years ago was like this. I brought them deeper into the world by pointing out how much more effective and efficient the data professionals’ life would be if our data repositories had a similar semantic meta-layer. What is a semantic layer? There’s more.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

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The key to operational AI: Modern data architecture

CIO Business Intelligence

From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. A lot has changed in those five years, and so has the data landscape. But if they wait another three years, they will never catch up.”

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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

times compared to 2023 but forecasts lower increases over the next two to five years. Whereas robotic process automation (RPA) aims to automate tasks and improve process orchestration, AI agents backed by the companys proprietary data may rewire workflows, scale operations, and improve contextually specific decision-making.