AWS Big Data Blog
Category: Analytics
Collect, parse, transform, and stream Windows events, logs, and metrics using Amazon Kinesis Agent for Microsoft Windows
A complete data pipeline that includes Amazon Kinesis Agent for Microsoft Windows (KA4W) can help you analyze and monitor the performance, security, and availability of Windows-based services. You can build near-real-time dashboards and alarms for your Windows services. You can also use visualization and business intelligence tools such as Amazon Athena, Kibana, Amazon QuickSight, and […]
Read MoreChasing earthquakes: How to prepare an unstructured dataset for visualization via ETL processing with Amazon Redshift
As organizations expand analytics practices and hire data scientists and other specialized roles, big data pipelines are growing increasingly complex. Sophisticated models are being built using the troves of data being collected every second. The bottleneck today is often not the know-how of analytical techniques. Rather, it’s the difficulty of building and maintaining ETL (extract, transform, and load) jobs using tools that might be unsuitable for the cloud. In this post, I demonstrate a solution to this challenge.
Read MoreDynamically scale up storage on Amazon EMR clusters
In a managed Apache Hadoop environment—like an Amazon EMR cluster—when the storage capacity on your cluster fills up, there is no convenient solution to deal with it. This situation occurs because you set up Amazon Elastic Block Store (Amazon EBS) volumes and configure mount points when the cluster is launched, so it’s difficult to modify […]
Read MoreClose the customer journey loop with Amazon Redshift at Equinox Fitness Clubs
Clickstream analysis tools handle their data well, and some even have impressive BI interfaces. However, analyzing clickstream data in isolation comes with many limitations. For example, a customer is interested in a product or service on your website. They go to your physical store to purchase it. The clickstream analyst asks, “What happened after they […]
Read MoreUse CTAS statements with Amazon Athena to reduce cost and improve performance
This blog post shows how to use the CREATE TABLE AS SELECT (CTAS statement) in Athena. It also shows how to automate the creation of unique tables that represent a subset of the AWS CloudTrail data. This helps us audit Amazon Athena usage.
Read MoreAdvanced analytics with table calculations in Amazon QuickSight
Amazon QuickSight recently launched table calculations, which enable you to perform complex calculations on your data to derive meaningful insights. In this blog post, we go through examples of applying these calculations to a sample sales data set so that you can start using these for your own needs. You can find the sample data […]
Read MoreRestrict access to your AWS Glue Data Catalog with resource-level IAM permissions and resource-based policies
Data cataloging is an important part of many analytical systems. The AWS Glue Data Catalog provides integration with a wide number of tools. Using the Data Catalog, you also can specify a policy that grants permissions to objects in the Data Catalog. Data lakes require detailed access control at both the content level and the level of the metadata describing the content. In this post, we show how you can define the access policies for the metadata in the catalog.
Read MoreMigrate to Apache HBase on Amazon S3 on Amazon EMR: Guidelines and Best Practices
This whitepaper walks you through the stages of a migration. It also helps you determine when to choose Apache HBase on Amazon S3 on Amazon EMR, plan for platform security, tune Apache HBase and EMRFS to support your application SLA, identify options to migrate and restore your data, and manage your cluster in production.
Read MoreConnect to Amazon Athena with federated identities using temporary credentials
This post walks through three scenarios to enable trusted users to access Athena using temporary security credentials. First, we use SAML federation where user credentials were stored in Active Directory. Second, we use a custom credentials provider library to enable cross-account access. And third, we use an EC2 Instance Profile role to provide temporary credentials for users in our organization to access Athena.
Read MoreHow Annalect built an event log data analytics solution using Amazon Redshift
By establishing a data warehouse strategy using Amazon S3 for storage and Redshift Spectrum for analytics, we increased the size of the datasets we support by over an order of magnitude. In addition, we improved our ability to ingest large volumes of data quickly, and maintained fast performance without increasing our costs. Our analysts and modelers can now perform deeper analytics to improve ad buying strategies and results.
Read More