AWS Big Data Blog
Track Amazon OpenSearch Service configuration changes more easily with new visibility improvements
Amazon OpenSearch Service offers multiple domain configuration settings to meet your workload-specific requirements. As part of standard service operations, you may be required to update these configuration settings on a regular basis. Recently, Amazon OpenSearch Service launched visibility improvements that allow you to track configuration changes more effectively. We’ve introduced granular and more descriptive configuration […]
Combine transactional, streaming, and third-party data on Amazon Redshift for financial services
Financial services customers are using data from different sources that originate at different frequencies, which includes real time, batch, and archived datasets. Additionally, they need streaming architectures to handle growing trade volumes, market volatility, and regulatory demands. The following are some of the key business use cases that highlight this need: Trade reporting – Since […]
Preprocess and fine-tune LLMs quickly and cost-effectively using Amazon EMR Serverless and Amazon SageMaker
Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. In general, you can build applications powered by LLMs by incorporating prompt engineering into your code. However, there are cases where prompting an existing LLM falls short. This is where model fine-tuning can help. Prompt engineering is about guiding the […]
Mastering market dynamics: Transforming transaction cost analytics with ultra-precise Tick History – PCAP and Amazon Athena for Apache Spark
This post is cowritten with Pramod Nayak, LakshmiKanth Mannem and Vivek Aggarwal from the Low Latency Group of LSEG. Transaction cost analysis (TCA) is widely used by traders, portfolio managers, and brokers for pre-trade and post-trade analysis, and helps them measure and optimize transaction costs and the effectiveness of their trading strategies. In this post, […]
Use Amazon Athena with Spark SQL for your open-source transactional table formats
In this post, we show you how to use Spark SQL in Amazon Athena notebooks and work with Iceberg, Hudi, and Delta Lake table formats. We demonstrate common operations such as creating databases and tables, inserting data into the tables, querying data, and looking at snapshots of the tables in Amazon S3 using Spark SQL in Athena.
Design a data mesh on AWS that reflects the envisioned organization
This post is written in collaboration with Claudia Chitu and Spyridon Dosis from ACAST. Founded in 2014, Acast is the world’s leading independent podcast company, elevating podcast creators and podcast advertisers for the ultimate listening experience. By championing an independent and open ecosystem for podcasting, Acast aims to fuel podcasting with the tools and monetization needed […]
AWS Lake Formation 2023 year in review
AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. In 2022, we talked about the enhancements we had done to these services. We continue to listen to […]
Enforce fine-grained access control on Open Table Formats via Amazon EMR integrated with AWS Lake Formation
With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many […]
Power neural search with AI/ML connectors in Amazon OpenSearch Service
With the launch of the neural search feature for Amazon OpenSearch Service in OpenSearch 2.9, it’s now effortless to integrate with AI/ML models to power semantic search and other use cases. OpenSearch Service has supported both lexical and vector search since the introduction of its k-nearest neighbor (k-NN) feature in 2020; however, configuring semantic search […]
Disaster recovery strategies for Amazon MWAA – Part 1
In the dynamic world of cloud computing, ensuring the resilience and availability of critical applications is paramount. Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. For organizations implementing critical workload orchestration using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), it is crucial to have a DR plan […]