AWS Big Data Blog

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 […]

Amazon EMR release 5.24.0 includes several optimizations in Spark that improve query performance. To evaluate the performance improvements, we used TPC-DS benchmark queries with 3-TB scale and ran them on a 6-node c4.8xlarge EMR cluster with data in Amazon S3. We observed up to 13X better query performance on EMR 5.24 compared to EMR 5.16 when operating with a similar configuration.

Today, AWS is excited to announce the availability of fine-grained access control for AWS Identity and Access Management (IAM)-permissioned resources in Amazon QuickSight. Fine-grained access control allows Amazon QuickSight account administrators to control authors’ default access to connected AWS resources. Fine-grained access control enables administrators to use IAM policies to scope down access permissions, limiting specific authors’ access to specific items within the AWS resources. Administrators can now apply this new level of access control to Amazon S3, Amazon Athena, and Amazon RDS/Redshift database discovery.

After reviewing many solutions, 3M HIS chose Amazon Redshift as the appropriate data warehouse solution. We concluded Amazon Redshift met our needs; a fast, fully managed, petabyte-scale data warehouse solution that uses columnar storage to minimize I/O, provides high data compression rates, and offers fast performance. We quickly spun up a cluster in our development environment, built out the dimensional model, loaded data, and made it available to perform benchmarking and testing of the user data. An extract, transform, load (ETL) tool was used to process and load the data from various sources into Amazon Redshift.

Today, we’re introducing the Amazon EMR Migrations Guide (first published June 2019.) This paper is a comprehensive guide to offer sound technical advice to help customers in planning how to move from on-premises big data deployments to EMR.

Today, we are pleased to announce a set of updates to Amazon QuickSight: Richer dashboards with multiple sheets in your regular and embedded dashboards, multiple axis label orientation options for better readability of dashboards, more calculations such as standard deviation, variance and conditional string functions on SPICE, enhanced URL actions for supporting a broader set of interaction scenarios, and one-click duplication of visuals for faster authoring.

This blog post shows how to use Amazon Kinesis Data Firehose to merge many small messages into larger messages for delivery to Amazon S3, which results in faster processing with Amazon EMR running Spark. This post also shows how to read the compressed files using Apache Spark that are in Amazon S3, which does not have a proper file name extension and store back in Amazon S3 in parquet format.

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 […]