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How to Manage Risk with Modern Data Architectures

Cloudera

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

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5 Data Governance Mistakes to Avoid

Alation

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

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5 Data Governance Mistakes to Avoid

Alation

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

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Automated data governance with AWS Glue Data Quality, sensitive data detection, and AWS Lake Formation

AWS Big Data

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. The Data Catalog organizes this information in the form of metadata tables and databases.

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The essential check list for effective data democratization

CIO Business Intelligence

Truly data-driven companies see significantly better business outcomes than those that aren’t. According to a recent IDC whitepaper , leaders saw on average two and a half times better results than other organizations in many business metrics.

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Why the Data Journey Manifesto?

DataKitchen

Data Journeys track and monitor all levels of the data stack, from data to tools to servers to code to tests across all critical dimensions. It supplies real-time statuses and alerts on start times, processing durations, test results, costs, and infrastructure events, among other metrics.

Testing 130