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A step-by-step guide to setting up a data governance program

IBM Big Data Hub

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

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Automate discovery of data relationships using ML and Amazon Neptune graph technology

AWS Big Data

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization.

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Data Landscape – Navigating The Data Jungle

Anmut

After decades in the background, data is currently king of the business world. Visionary companies like Google and Amazon are renowned for figuring out the transformational power of data, using data-driven business models to achieve extraordinary success. It doesn’t have to be this way.

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The Chief Marketing Officer and the CDO – A Modern Fable

Peter James Thomas

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. It may be to introduce or expand Data Governance.

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Empowering data mesh: The tools to deliver BI excellence

erwin

The data mesh approach distributes data ownership and decentralizes data architecture, paving the way for enhanced agility and scalability. With distributed ownership there is a need for effective governance to ensure the success of any data initiative. Gathering this data isn’t possible without automation.

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Breaking down data silos for digital success

CIO Business Intelligence

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

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“You Complete Me,” said Data Lineage to DataOps Observability.

DataKitchen

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

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