AWS Big Data Blog
Simplify data integration pipeline development using AWS Glue custom blueprints
Update August 18, 2021 – AWS Glue custom blueprints are now generally available. Please visit https://docs.aws.amazon.com/glue/latest/dg/blueprints-overview.html to learn more. Organizations spend significant time developing and maintaining data integration pipelines that hydrate data warehouses, data lakes, and lake houses. As data volume increases, data engineering teams struggle to keep up with new requests from business teams. Although these […]
Continuous monitoring with Sumo Logic using Amazon Kinesis Data Firehose HTTP endpoints
Amazon Kinesis Data Firehose streams data to AWS destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, and Amazon OpenSearch Service. Additionally, Kinesis Data Firehose supports destinations to third-party partners. This ability to send data to third-party partners is a vital feature for customers who already use these AWS partner platforms; especially partners […]
Build and orchestrate ETL pipelines using Amazon Athena and AWS Step Functions
Extract, transform, and load (ETL) is the process of reading source data, applying transformation rules to this data, and loading it into the target structures. ETL is performed for various reasons. Sometimes ETL helps align source data to target data structures, whereas other times ETL is done to derive business value by cleansing, standardizing, combining, […]
Implement a slowly changing dimension in Amazon Redshift
Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. A star schema is a database organization structure optimized for use in a data warehouse. In a star schema, a dimension is a structure that categorizes the facts and measures in order to enable you to answer business questions. The attributes (or […]
Prepare, transform, and orchestrate your data using AWS Glue DataBrew, AWS Glue ETL, and AWS Step Functions
Data volumes in organizations are increasing at an unprecedented rate, exploding from terabytes to petabytes and in some cases exabytes. As data volume increases, it attracts more and more users and applications to use the data in many different ways—sometime referred to as data gravity. As data gravity increases, we need to find tools and […]
WeatherBug reduced ETL latency to 30 times faster using Amazon Redshift Spectrum
This post is co-written with data engineers, Anton Morozov and James Phillips, from Weatherbug. WeatherBug is a brand owned by GroundTruth, based in New York City, that provides location-based advertising solutions to businesses. WeatherBug consists of a mobile app reporting live and forecast data on hyperlocal weather to consumer users. The WeatherBug Data Engineering team […]
Automate your Amazon Redshift performance tuning with automatic table optimization
Amazon Redshift is a cloud data warehouse database that provides fast, consistent performance running complex analytical queries on huge datasets scaling into petabytes and even exabytes with Amazon Redshift Spectrum. Although Amazon Redshift has excellent query performance out of the box, with up to three times better price performance than other cloud data warehouses, you […]
Query your Amazon MSK topics interactively using Amazon Kinesis Data Analytics Studio
Amazon Kinesis Data Analytics Studio makes it easy to analyze streaming data in real time and build stream processing applications powered by Apache Flink using standard SQL, Python, and Scala. With a few clicks on the AWS Management Console, you can launch a serverless notebook to query data streams and get results in seconds. Kinesis […]
Authorize SparkSQL data manipulation on Amazon EMR using Apache Ranger
This post was last updated July 2022. With Amazon EMR 6.7, all Apache Spark DDL’s are now supported, except for CREATE VIEW. For details, see the section under “limitations”. NOTE: You will need to redeploy Spark service definition (link) on your Apache Ranger server. Instructions on how to redeploy can be found here. With Amazon […]
Use Amazon Athena and Amazon QuickSight in a cross-account environment
This blog post was last reviewed and updated May, 2022 to include AWS Lake Formation resource sharing model. Many AWS customers use a multi-account strategy to host applications for different departments within the same company. However, you might deploy services like Amazon QuickSight using a single-account approach, which raises challenges when you need to use […]