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Build Write-Audit-Publish pattern with Apache Iceberg branching and AWS Glue Data Quality

AWS Big Data

Given the importance of data in the world today, organizations face the dual challenges of managing large-scale, continuously incoming data while vetting its quality and reliability. One of its key features is the ability to manage data using branches.

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Talend Data Fabric Simplifies Data Life Cycle Management

David Menninger's Analyst Perspectives

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. Its code generation architecture uses a visual interface to create Java or SQL code.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. This innovation drives an important change: you’ll no longer have to copy or move data between data lake and data warehouses. Having confidence in your data is key.

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Seamless integration of data lake and data warehouse using Amazon Redshift Spectrum and Amazon DataZone

AWS Big Data

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis.

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Implement data quality checks on Amazon Redshift data assets and integrate with Amazon DataZone

AWS Big Data

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.