AWS Big Data Blog

How ENGIE scales their data ingestion pipelines using Amazon MWAA

ENGIE—one of the largest utility providers in France and a global player in the zero-carbon energy transition—produces, transports, and deals electricity, gas, and energy services. With 160,000 employees worldwide, ENGIE is a decentralized organization and operates 25 business units with a high level of delegation and empowerment. ENGIE’s decentralized global customer base had accumulated lots […]

Build a modern data architecture on AWS with Amazon AppFlow, AWS Lake Formation, and Amazon Redshift: Part 2

In Part 1 of this post, we provided a solution to build the sourcing, orchestration, and transformation of data from multiple source systems, including Salesforce, SAP, and Oracle, into a managed modern data platform. Roche partnered with AWS Professional Services to build out this fully automated and scalable platform to provide the foundation for their […]

Best practices to optimize your Amazon Redshift and MicroStrategy deployment

This is a guest blog post co-written by Amit Nayak at Microstrategy. In their own words, “MicroStrategy is the largest independent publicly traded business intelligence (BI) company, with the leading enterprise analytics platform. Our vision is to enable Intelligence Everywhere. MicroStrategy provides modern analytics on an open, comprehensive enterprise platform used by many of the […]

Add comparative and cumulative date/time calculations in Amazon QuickSight

Amazon QuickSight recently added native support for comparative (e.g., year-over-year) and cumulative (e.g., year-to-date) period functions which allow you to easily introduce these calculations in business reporting, trend analysis and time series analysis. This allows authors in QuickSight to implement advanced calculations without having to use complicated date offsets in calculations to achieve such datetime-aware […]

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 […]

Gain insights into your Amazon Kinesis Data Firehose delivery stream using Amazon CloudWatch

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. The volume of data being generated globally is growing at an ever-increasing pace. Data is generated to support an increasing number of use cases, such as IoT, advertisement, gaming, security monitoring, machine […]

Centralize governance for your data lake using AWS Lake Formation while enabling a modern data architecture with Amazon Redshift Spectrum

Many customers are modernizing their data architecture using Amazon Redshift to enable access to all their data from a central data location. They are looking for a simpler, scalable, and centralized way to define and enforce access policies on their data lakes on Amazon Simple Storage Service (Amazon S3). They want access policies to allow […]

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 […]