AWS Big Data Blog

Category: Learning Levels

Enhance data security and governance for Amazon Redshift Spectrum with VPC endpoints

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Furthermore, they are adopting security models that require access to the data lake […]

Simplify access management with Amazon Redshift and AWS Lake Formation for users in an External Identity Provider

Many organizations use identity providers (IdPs) to authenticate users, manage their attributes, and group memberships for secure, efficient, and centralized identity management. You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to […]

Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 2: Real-time monitoring using Grafana

Monitoring data pipelines in real time is critical for catching issues early and minimizing disruptions. AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics, which provide valuable insights into your data integration pipelines built on AWS Glue. However, you might need to track key performance indicators across multiple […]

Secure connectivity patterns for Amazon MSK Serverless cross-account access

Amazon MSK Serverless is a cluster type of Amazon Managed Streaming for Apache Kafka (Amazon MSK) that makes it straightforward for you to run Apache Kafka without having to manage and scale cluster capacity. MSK Serverless automatically provisions and scales compute and storage resources. With MSK Serverless, you can use Apache Kafka on demand and […]

Automate AWS Clean Rooms querying and dashboard publishing using AWS Step Functions and Amazon QuickSight – Part 2

Public health organizations need access to data insights that they can quickly act upon, especially in times of health emergencies, when data needs to be updated multiple times daily. For example, during the COVID-19 pandemic, access to timely data insights was critically important for public health agencies worldwide as they coordinated emergency response efforts. Up-to-date […]

Use multiple bookmark keys in AWS Glue JDBC jobs

AWS Glue is a serverless data integrating service that you can use to catalog data and prepare for analytics. With AWS Glue, you can discover your data, develop scripts to transform sources into targets, and schedule and run extract, transform, and load (ETL) jobs in a serverless environment. AWS Glue jobs are responsible for running […]

Solution overview

Build SAML identity federation for Amazon OpenSearch Service domains within a VPC

Amazon OpenSearch Service is a fully managed search and analytics service powered by the Apache Lucene search library that can be operated within a virtual private cloud (VPC). A VPC is a virtual network that’s dedicated to your AWS account. It’s logically isolated from other virtual networks in the AWS Cloud. Placing an OpenSearch Service […]

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, […]