AWS Storage Blog
Category: Amazon Athena
Derive insights from AWS DataSync task reports using AWS Glue, Amazon Athena, and Amazon QuickSight
Update (10/30/2024): On October 30, 2024, AWS DataSync launched Enhanced mode tasks, prompting updates to this blog. Updates include a new step in the “Step 2: Populate Glue catalog with task reports data using a Glue crawler” section and detailed information on the new capabilities in “Updated steps for working with task reports of new […]
Access a point in time with Amazon S3 Object Lambda
Point-in-time ‘snapshots’ enable administrators, developers, testers, and end users to quickly access a storage volume or share how it was at an earlier point-in-time. They are a longstanding approach to data protection and recovery, tracking changes within a storage system to reduce both Recovery Point Objective (RTO) and Recovery Time Objective (RTO). However, traditional snapshots […]
Use generative AI to query your Amazon S3 data lake for insights
Businesses store large volumes of data in their data lakes and rely on this data to extract insights and make important business decisions. However, business stakeholders sometimes lack the technical skills required to run complex queries against their data lakes. Instead, they rely on data scientists or analysts to build reports and dashboards or to […]
Streamline and automate compliance monitoring and reporting with AWS Backup Audit Manager
Organizations meet business and regulatory requirements by having visibility and control over backup environments. You want a streamlined solution to continuously monitor, detect, and track policy drifts across your backup deployments at scale. This need is driven by the growing complexity of AWS environments, the proliferation of data across diverse AWS services and regions, and […]
Maintaining object immutability by automatically extending Amazon S3 Object Lock retention periods
Protecting against accidental or malicious deletion is a key element of data protection. Immutability protects data in-place, preventing unintended changes or deletions. However, sometimes it isn’t clear for how long data should be made immutable. Users in this situation are looking for a solution that maintains short-term immutability, indefinitely. They want to make sure their […]
Understand Amazon S3 data transfer costs by classifying requests with Amazon Athena
Cost is top of mind for many enterprises, and building awareness of different cost contributors is the first step toward managing costs and improving efficiency. Costs for transferring data may segregate into common but low cost and less frequent but higher cost groups. Data about these two groups is mixed together, and separating them enables […]
Managing duplicate objects in Amazon S3
When managing a large volume of data in a storage system, it is common for data duplication to happen. Data duplication in data management refers to the presence of multiple copies of the same data within your system, leading to additional storage usage as well as extra overhead when handling multiple copies of the same […]
Automatic monitoring of actions taken on objects in Amazon S3
Administrators may need to monitor and audit actions, like uploads, updates, and deletes, taken on files and other data to comply with regulations or company policies. A scalable and reliable method of tracking and saving actions taken on files can reduce manual work and operational overhead while helping to ensure compliance. An event-based fanout architectures […]
Automatically modify data you are querying with Amazon Athena using Amazon S3 Object Lambda
Enterprises may want to customize their data sets for different requesting applications. For example, if you run an e-commerce website, you may want to mask Personally Identifiable Information (PII) when querying your data for analytics. Although you can create and store multiple customized copies of your data, that can increase your storage cost. You can […]
Simplify querying your archive data in Amazon S3 with Amazon Athena
Today, customers increasingly choose to store data for longer because they recognize its future value potential. Storing data longer, coupled with exponential data growth, has led to customers placing a greater emphasis on storage cost optimization and using cost-effective storage classes. However, a modern data archiving strategy not only calls for optimizing storage costs, but […]