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The Race For Data Quality in a Medallion Architecture

DataKitchen

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. It sounds great, but how do you prove the data is correct at each layer? Bronze layers should be immutable.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities?

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Data Architecture and Strategy in the AI Era

Cloudera

At a time when AI is exploding in popularity and finding its way into nearly every facet of business operations, data has arguably never been more valuable. As organizations continue to navigate this AI-driven world, we set out to understand the strategies and emerging data architectures that are defining the future.

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Perform data parity at scale for data modernization programs using AWS Glue Data Quality

AWS Big Data

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Data parity can help build confidence and trust with business users on the quality of migrated data.

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From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.