AWS Big Data Blog
Category: AWS Big Data
Extract ServiceNow data using AWS Glue Studio in an Amazon S3 data lake and analyze using Amazon Athena
Many different cloud-based software as a service (SaaS) offerings are available in AWS. ServiceNow is one of the common cloud-based workflow automation platforms widely used by AWS customers. In the past few years, we saw a lot of customers who wanted to extract and integrate data from IT service management (ITSM) tools like ServiceNow for […]
How GE Aviation automated engine wash analytics with AWS Glue using a serverless architecture
This post is authored by Giridhar G Jorapur, GE Aviation Digital Technology. Maintenance and overhauling of aircraft engines are essential for GE Aviation to increase time on wing gains and reduce shop visit costs. Engine wash analytics provide visibility into the significant time on wing gains that can be achieved through effective water wash, foam […]
Validate streaming data over Amazon MSK using schemas in cross-account AWS Glue Schema Registry
August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Today’s businesses face an unprecedented growth in the volume of data. A growing portion of the data is generated in real time by IoT devices, websites, business […]
Evolve JSON Schemas in Amazon MSK and Amazon Kinesis Data Streams with the AWS Glue Schema Registry
Data is being produced, streamed, and consumed at an immense rate, and that rate is projected to grow exponentially in the future. In particular, JSON is the most widely used data format across streaming technologies and workloads. As applications, websites, and machines increasingly adopt data streaming technologies such as Apache Kafka and Amazon Kinesis Data […]
Handle fast-changing reference data in an AWS Glue streaming ETL job
Streaming ETL jobs in AWS Glue can consume data from streaming sources such as Amazon Kinesis and Apache Kafka, clean and transform those data streams in-flight, as well as continuously load the results into Amazon Simple Storage Service (Amazon S3) data lakes, data warehouses, or other data stores. The always-on nature of streaming jobs poses […]
Securely share your data across AWS accounts using AWS Lake Formation
Data lakes have become very popular with organizations that want a centralized repository that allows you to store all your structured data and unstructured data at any scale. Because data is stored as is, there is no need to convert it to a predefined schema in advance. When you have new business use cases, you […]
Enrich datasets for descriptive analytics with AWS Glue DataBrew
Data analytics remains a constantly hot topic. More and more businesses are beginning to understand the potential their data has to allow them to serve customers more effectively and give them a competitive advantage. However, for many small to medium businesses, gaining insight from their data can be challenging because they often lack in-house data […]
Query cross-account AWS Glue Data Catalogs using Amazon Athena
Many AWS customers rely on a multi-account strategy to scale their organization and better manage their data lake across different projects or lines of business. The AWS Glue Data Catalog contains references to data used as sources and targets of your extract, transform, and load (ETL) jobs in AWS Glue. Using a centralized Data Catalog […]
Ibotta builds a self-service data lake with AWS Glue
This is a guest post co-written by Erik Franco at Ibotta. Ibotta is a free cash back rewards and payments app that gives consumers real cash for everyday purchases when they shop and pay through the app. Ibotta provides thousands of ways for consumers to earn cash on their purchases by partnering with more than […]
Unify log aggregation and analytics across compute platforms
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Our customers want to make sure their users have the best experience running their application on AWS. To make this happen, you need to monitor and fix software problems as quickly as […]