Category: AWS Glue

The RODA program provides quick and inexpensive access to the global biomedical research resources of the MIMIC-III dataset. Cloud-native analytic tools like AWS Glue and Athena accelerate research, and groups like the MIT Laboratory of Computational Physiology are pioneering data availability in modern data formats like Apache Parquet. The analytic approaches and code demonstrated in this post can be applied generally to help increase agility and decrease cost. Consider using them as you enhance existing or perform new biomedical informatics research.

A data lake is a centralized store of a variety of data types for analysis by multiple analytics approaches and groups. Many organizations are moving their data into a data lake. In this post, we explore how you can use AWS Lake Formation to build, secure, and manage data lakes.

In this post, I show you how to use AWS Glue to extract data from a Salesforce.com account object and save it to Amazon S3. You then use Amazon Athena to generate a report by joining the account object data from Salesforce.com with the orders data from a separate order management system.

Building a data lake on Amazon S3 provides an organization with countless benefits. It allows you to access diverse data sources, determine unique relationships, build AI/ML models to provide customized customer experiences, and accelerate the curation of new datasets for consumption. However, capturing and loading continuously changing updates from operational data stores—whether on-premises or on […]

The financial impact of fraud in any industry is massive. According to the Financial Times article Fraud Costs Telecoms Industry $17bn a Year (paid subscription required), fraud costs the telecommunications industry $17 billion in lost revenues every year. Fraudsters constantly look for new technologies and devise new techniques. This changes fraud patterns and makes detection […]

In this post, I show you how to use AWS Glue’s DynamoDB integration and AWS Step Functions to create a workflow to export your DynamoDB tables to S3 in Parquet. I also show how to create an Athena view for each table’s latest snapshot, giving you a consistent view of your DynamoDB table exports.

In Amazon Simple Storage Service (Amazon S3), you can use cross-region replication (CRR) to copy objects automatically and asynchronously across buckets in different AWS Regions. CRR is a bucket-level configuration, and it can help you meet compliance requirements and minimize latency by keeping copies of your data in different Regions. CRR replicates all objects in […]

Today, data is flowing from everywhere, whether it is unstructured data from resources like IoT sensors, application logs, and clickstreams, or structured data from transaction applications, relational databases, and spreadsheets. Data has become a crucial part of every business. This has resulted in a need to maintain a single source of truth and automate the […]

Clickstream events are small pieces of data that are generated continuously with high speed and volume. Often, clickstream events are generated by user actions, and it is useful to analyze them. For example, you can detect user behavior in a website or application by analyzing the sequence of clicks a user makes, the amount of […]

In this post, we talk about designing a cloud-native data warehouse as a replacement for our legacy data warehouse built on a relational database. At the beginning of the design process, the simplest solution appeared to be a straightforward lift-and-shift migration from one relational database to another. However, we decided to step back and focus […]