Remove Data Lake Remove Metadata Remove Sales
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How BMW streamlined data access using AWS Lake Formation fine-grained access control

AWS Big Data

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight.

Data Lake 108
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Write queries faster with Amazon Q generative SQL for Amazon Redshift

AWS Big Data

Amazon Q generative SQL for Amazon Redshift uses generative AI to analyze user intent, query patterns, and schema metadata to identify common SQL query patterns directly within Amazon Redshift, accelerating the query authoring process for users and reducing the time required to derive actionable data insights.

Metadata 105
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Amazon SageMaker Lakehouse now supports attribute-based access control

AWS Big Data

Example Retails leadership is interested in analyzing sales data in Amazon S3 to determine in-demand products, understand customer behavior, and identify trends, for better decision-making and increased profitability. The table store_sales has the following schema.

Sales 88
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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture. To achieve this, they plan to use machine learning (ML) models to extract insights from data.

Sales 115
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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 122
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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 115
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Enrich your serverless data lake with Amazon Bedrock

AWS Big Data

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging.

Data Lake 115