Remove Data Lake Remove Data Quality Remove Risk
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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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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality. Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks.

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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. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. Why did Orca build a data lake?

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Getting started with AWS Glue Data Quality from the AWS Glue Data Catalog

AWS Big Data

You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

Globally, financial institutions have been experiencing similar issues, prompting a widespread reassessment of traditional data management approaches. Domain ownership recognizes that the teams generating the data have the deepest understanding of it and are therefore best suited to manage, govern, and share it effectively.

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Data Lakes: What Are They and Who Needs Them?

Jet Global

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.