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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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The Future of AI in the Enterprise

Jet Global

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.

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How to Design an Analytics Stack that Humans Actually Use

Alation

It isn’t uncommon for a business user to see something on a dashboard that intrigues them and submit a request to the BI team for that data. It is eventually shared with them in a CSV file that needs to be opened in either Excel or Google Sheets for analysis and visualization. Let People Tell Their Data Story In Their Own Way.

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Five benefits of a data catalog

IBM Big Data Hub

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

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The Future of AI in the Enterprise

Jet Global

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.