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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. As you would guess, maintaining context relies on metadata.

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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. This is accomplished through tags, annotations, and metadata (TAM). Data catalogs are very useful and important. Do not forget the negations.

Strategy 267
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What is data governance? Best practices for managing data assets

CIO Business Intelligence

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. The program must introduce and support standardization of enterprise data.

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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Towards Data Science ).

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

erwin

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

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Data Mesh 101: How Data Mesh Can Be Used in an Organization

Ontotext

This calls for additional planning, documentation, and testing. A data mesh will likely require more engineers to get started, so a critical mass is needed for successful adoption. Each team should be accountable for providing their prepared data sets to downstream systems.

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How to Automate Your Data Catalog for 2022

Octopai

The entry features the data asset description (i.e. the stalk of barley symbol and the circular numeral signs) and the data owner (i.e. This data catalog didn’t need automation. It was perfectly reasonable for an individual to manually manage a Sumerian data collection (especially if you paid him enough barley).