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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

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Five benefits of a data catalog

IBM Big Data Hub

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. A business glossary to explain the business terms used within a data asset.

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Regeneron turns to IT to accelerate drug discovery

CIO Business Intelligence

Then the data is consumed by SaaS-based computational tools, but it still sits within our organization and sits within the controls of our cloud-based solutions.” Much of Regeneron’s data, of course, is confidential. For that reason, many of its data tools — and even its data lake — were built in-house using AWS. “We

Data Lake 116
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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. We must resort to black box testing —testing the behavior of the function with a wide range of inputs.

IT 346
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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. It helps solve the lack of visibility and control over “data at rest” in databases, data lakes and data warehouses and “data in motion” as it is integrated with and used by key applications.