Remove Contextual Data Remove Data Analytics Remove Data Warehouse
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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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Regeneron turns to IT to accelerate drug discovery

CIO Business Intelligence

Our vision for the data lake is that we want to be able to connect every group, from our genetic center through manufacturing through clinical safety and early research. That’s hard to do when you have 30 years of data.” At the data pipeline level, scientists use Apigee, Airflow, NiFi, and Kafka.

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How to Design an Analytics Stack that Humans Actually Use

Alation

percent) cite culture – a mix of people, process, organization, and change management – as the primary barrier to forging a data-driven culture, it is worth examining data democratization efforts within your organization and the business user’s experience throughout the data analytics stack.

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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.