AWS Big Data Blog

A large EMEA company recently decided to migrate their on-premises IBM Netezza data warehouse to Amazon Redshift. Given the volume of data (270TB uncompressed and more than 27K tables), the number of interconnected systems that made use of this data (more than 4.5K business processes), and the zero downtime requirements, we understood that the project […]

The RODA program provides quick and inexpensive access to the global biomedical research resources of the MIMIC-III dataset. Cloud-native analytic tools like AWS Glue and Athena accelerate research, and groups like the MIT Laboratory of Computational Physiology are pioneering data availability in modern data formats like Apache Parquet. The analytic approaches and code demonstrated in this post can be applied generally to help increase agility and decrease cost. Consider using them as you enhance existing or perform new biomedical informatics research.

In this post, you will learn how to use the metadata search capabilities of Lake Formation. By defining specific user permissions, Lake Formation allows you to grant and revoke access to metadata in the Data Catalog as well as the underlying data stored in S3.

In this post, you will create and edit your first data lake using the Lake Formation. You will use the service to secure and ingest data into an S3 data lake, catalog the data, and customize the metadata of the data sources. In part 2 of this series, we will show you how to discover your data by using the metadata search capabilities of Lake Formation.

AWS Lake Formation enables you to set up a secure data lake. A data lake is a centralized, curated, and secured repository storing all your structured and unstructured data, at any scale. You can store your data as-is, without having first to structure it. And you can run different types of analytics to better guide […]

AWS Lake Formation FindMatches is a new machine learning (ML) transform that enables you to match records across different datasets as well as identify and remove duplicate records, with little to no human intervention. FindMatches is part of Lake Formation, a new AWS service that helps you build a secure data lake in a few simple steps.

To use FindMatches, you don’t have to write code or know how ML works. Your data doesn’t have to include a unique identifier, nor must fields match exactly.

A data lake is a centralized store of a variety of data types for analysis by multiple analytics approaches and groups. Many organizations are moving their data into a data lake. In this post, we explore how you can use AWS Lake Formation to build, secure, and manage data lakes.

This post presents a simple approach to aggregating AWS WAF logs into a central data lake repository, which lets teams better analyze and understand their organization’s security posture. I walk through the steps to aggregate regional AWS WAF logs into a dedicated S3 bucket. I follow that up by demonstrating how you can use Amazon ES to visualize the log data. I also present an option to offload and process historical data using AWS Glue ETL. With the data collected in one place, I finally show you how you can use Amazon Athena and Amazon QuickSight to query historical data and extract business insights.

Amazon always works backwards from the customer’s needs. Customers have made strong requests that they want stored procedures in Amazon Redshift, to make it easier to migrate their existing workloads from legacy, on-premises data warehouses.

With that primary goal in mind, AWS chose to implement PL/pqSQL stored procedure to maximize compatibility with existing procedures and simplify migrations. In this post, we discuss how and where to use stored procedures to improve operational efficiency and security. We also explain how to use stored procedures with AWS Schema Conversion Tool.

In this blog post, I use this architecture to demonstrate the combined capabilities of Storage Gateway and Athena. AWS Storage Gateway is a hybrid storage service that enables your on-premises applications to seamlessly use AWS cloud storage. The File Gateway configuration of the AWS Storage Gateway offers you a seamless way to connect to the cloud in order to store application data files and backup images as durable objects on Amazon S3 cloud storage.