Remove Data Lake Remove Machine Learning Remove Strategy
article thumbnail

Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. Delete the bucket.

Data Lake 105
article thumbnail

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
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. Unified access to your data is provided by Amazon SageMaker Lakehouse , a unified, open, and secure data lakehouse built on Apache Iceberg open standards.

Analytics 112
article thumbnail

Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

article thumbnail

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
article thumbnail

How Cloudinary transformed their petabyte scale streaming data lake with Apache Iceberg and AWS Analytics

AWS Big Data

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used.

Data Lake 126
article thumbnail

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