Remove Data Lake Remove Data Processing Remove Data Quality
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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Set up advanced rules to validate quality of multiple datasets with AWS Glue Data Quality

AWS Big Data

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. The data science and AI teams are able to explore and use new data sources as they become available through Amazon DataZone.

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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

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. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

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The essential check list for effective data democratization

CIO Business Intelligence

“All of a sudden, you’re trying to give this data to somebody who’s not a data person,” he says, “and it’s really easy for them to draw erroneous or misleading insights from that data.” As more companies use the cloud and cloud-native development, normalizing data has become more complicated.

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Empowering data-driven excellence: How the Bluestone Data Platform embraced data mesh for success

AWS Big Data

Each data producer within the organization has its own data lake in Apache Hudi format, ensuring data sovereignty and autonomy. This enables data-driven decision-making across the organization. AWS services like AWS Lake Formation in conjunction with Atlan help govern data access and policies.

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Governing data in relational databases using Amazon DataZone

AWS Big Data

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

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