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

AWS Big Data

Equally crucial is the ability to segregate and audit problematic data, not just for maintaining data integrity, but also for regulatory compliance, error analysis, and potential data recovery. One of its key features is the ability to manage data using branches. It specifies which data is clean and ready to be provided.

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

AWS Big Data

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. Using Athena and the dbt adapter, you can transform raw data in Amazon S3 into well-structured tables suitable for analytics.

Data Lake 100
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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. Business units access clean, standardized data.

Data Lake 121
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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. Having confidence in your data is key.

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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.

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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. Some customers build custom in-house data parity frameworks to validate data during migration.

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What is a Data Mesh?

DataKitchen

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt.