Remove 2019 Remove Data Governance Remove Data Lakes
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Why Easier Governance Is Superior Governance

Alation

A new research report by Ventana Research, Embracing Modern Data Governance , shows that modern data governance programs can drive a significantly higher ROI in a much shorter time span. Historically, data governance has been a manual and restrictive process, making it almost impossible for these programs to succeed.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Organizations must diligently manage access controls, encryption, and data protection to mitigate risks. For example, the 2019 Capital One breach exposed over 100 million customer records, highlighting the need for robust security measures. Understand what insights you need to gain from your data to drive business growth and strategy.

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Data Mesh vs. Data Fabric: A Love Story

Alation

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

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Adapting to Change: Finding Opportunity in Crucible Moments

Alation

A restaurant experience of 2019 is much different than one today. So, ARC worked to make data more accessible across domains while capturing tribal knowledge in the data catalog; this reduced the subject-matter-expertise bottlenecks during product development and accelerated higher quality analysis.

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The CDO Imperative: From Process Centric to data-driven

Alation

Today, the scope of the CDO is shifting toward empowering data-driven organizations. Gartner notes that most industries already have CDOs, and predicts that by 2019, 90% of large organizations will have hired a chief data officer. Governing Data Lakes to Find Opportunities for Customers.

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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

Data lineage and auditing – Metadata can provide information about the provenance and lineage of documents, such as the source system, data ingestion pipeline, or other transformations applied to the data. This information can be valuable for data governance, auditing, and compliance purposes.

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