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- Sep 19, 2025
- Parsed from source:Sep 19, 2025
- Detected by Releasebot:Sep 29, 2025
AWS Business Intelligence Knowledge Badge
Announces the AWS Business Intelligence Knowledge Badge Readiness Path for QuickSight. An intermediate 9h45m learning track (8 trainings) plus an assessment to earn a Credly badge, including generative AI with Amazon Q. Enroll via AWS Skill Builder; September 2025 release.
The Community team is pleased to announce to our valued customers a new way to showcase your expertise in AWS Business Intelligence solutions!
Whether you’re just starting your journey with Amazon QuickSight or you’re a seasoned professional, our new AWS Business Intelligence Knowledge Badge Readiness Path is designed for you. This intermediate-level learning path spans 9 hours and 45 minutes, offering a comprehensive exploration of data visualization, analytics, and dashboard creation, with an assessment at the end. Score 80% or more to earn the Credly digital badge!
New to QuickSight? Follow this structured learning path through 8 carefully curated trainings that will build your expertise from the ground up. You’ll master everything from fundamentals to advanced features, including the latest generative AI capabilities with Amazon Q.
Already a long-time QuickSight user? Your hands-on experience may have already prepared you for immediate badge attainment! Skip straight to the assessment: put your expertise to the test with our assessment and earn your Credly digital badge to validate your mastery of AWS Business Intelligence solutions.
This September 2025 release represents our commitment to recognizing and celebrating the expertise of our AWS community members. The badge serves as a testament to your proficiency in:
- Data visualization
- Analytics
- Dashboard creation
- QuickSight best practices
- Generative AI integration
Ready to showcase your QuickSight expertise? Enroll today in AWS Skill Builder and earn your AWS Business Intelligence Knowledge Badge!
#AWSCommunity #BusinessIntelligence #AmazonQuickSight #AWSCertification #DataVisualization
- Sep 11, 2025
- Parsed from source:Sep 11, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight Enhances Chart Performance and Visual Experience
Amazon QuickSight updates 20 native chart types with faster rendering, better axis auto-scaling, improved label fitting and color contrast, and enhanced stacked area visuals. No action required; available across all regions. Visuals and docs updated.
Amazon QuickSight has released improvements to 20 native chart types, enhancing visualization performance and readability. This upgrade includes improvements to Bar charts, Combo charts, Line Charts, Histogram, Scatter Plot, Boxplot, Funnel, Radar, Sankey, Waterfall, Pie, and Donut charts.
Key improvements include faster rendering performance, enhanced axis auto-scaling for optimal chart area utilization, improved data label fitting to display more labels in limited spaces, better color contrast management for improved label readability, and enhanced visualization of stacked areas with improved borders and layer opacity.
These chart improvements are seamlessly integrated and require no action from authors and readers. The upgraded charts are now available in all supported Amazon QuickSight regions.
To learn more about Amazon QuickSight visualizations and features, visit the Visual Types in Amazon QuickSight User Guide.
- September 2025
- No date parsed from source.
- Detected by Releasebot:Sep 29, 2025
Database Migration Service by Amazon
AWS Database Migration Service 3.6.1 release notes
AWS DMS 3.6.1 ships new features: data resync for Oracle/SQL Server to PostgreSQL, IAM database authentication for MariaDB/MySQL/PostgreSQL, PostgreSQL 17 support, and CDC using PostgreSQL read replicas. Also includes numerous stability and compatibility fixes across sources and targets.
New features in AWS DMS 3.6.1
DMS Data Resync AWS DMS automatically fixes data inconsistencies identified through data validation between your source and target databases. The data resync feature is supported for Oracle and SQL Server as a source and Postgre SQL as a target databases.
IAM database authentication for MariaDB, MySQL, and PostgreSQL Introduced support connecting to Amazon RDS and Aurora MariaDB, MySQL, and PostgreSQL endpoints through AWS Identity and Access Management (IAM) database authentication. With this enhancement you can use IAM to centrally manage access to your database resources, instead of managing access individually on each database endpoint.
Support for PostgreSQL 17 Introduced support for PostgreSQL version 17. For more information, see: Using a PostgreSQL database as an AWS DMS source Using a PostgreSQL database as a target for AWS Database Migration Service
PostgreSQL Read Replica Support for Change Data Capture (CDC) Replication AWS DMS supports using PostgreSQL read replicas as source endpoints for Change Data Capture (CDC) replication, available with PostgreSQL version 16.x and later, starting with AWS DMS version 3.6.1. This feature allows you to leverage read replicas for CDC tasks. For more information, see Using a PostgreSQL database as an AWS DMS source.
AWS DMS version 3.6.1 includes the following resolved issues:
Selection rules filtering with data masking issue Table selection rule filters now work correctly with data masking transformation rules. The fix ensures proper filtering when data masking transformations are applied.
PostgreSQL target unbound numeric handling issue PostgreSQL target endpoints can handle unbound numeric data types through optimized memory allocation. This prevents task failures when migrating tables with large numeric values.
Amazon Redshift target LOB handling issue Redshift target endpoints now maintain LOB data integrity during high-volume parallel migrations. The improved LOB handling prevents data corruption when using parallel apply threads.
Transformation rules metadata issue Fixed an issue with expressions in transformation rules that were incorrectly applied.
Metadata table drop and recreate issue Replication tasks now resume successfully when source tables are dropped and recreated during task stoppage. Improved metadata handling and status synchronization for recreated source tables.
SQL Server AlwaysOn primary replica issue Improved primary replica detection for SQL Server sources in AlwaysOn configurations by handling case sensitivity variations.
MySQL source TIME data type handling issue Resolved migration issues with TIME values containing fractions and hours exceeding 24 when loadUsingCSV is disabled.
Data validation NUL character handling issue Data validation now handles NUL (0x00) characters correctly without failing. Improved validation processing for data containing NUL characters.
SQL Server data validation issue Resolved validation comparison issues with UNIQUEIDENTIFIER columns for SQL Server sources.
Table pre-load validation issue AWS DMS tasks now complete validation successfully when tables are in pre-load phase during CDC replication.
Oracle source logging issue Oracle source error logs now display the correct SQL statement during timezone query execution. Improved logging accuracy for better troubleshooting capabilities.
SQL Server driver update SQL Server driver support is updated from ODBC 17 to ODBC 18.
- September 2025
- No date parsed from source.
- Detected by Releasebot:Sep 29, 2025
Database Migration Service by Amazon
AWS Database Migration Service 3.6.0 release notes
AWS DMS 3.6.0 brings measurable product improvements: new dynamic transformation variables for schema and table name changes, and enhanced LOB replication in UPSERT error-handling mode for complete data fidelity. The release also tackles a broad set of reliability and performance fixes across engines including PostgreSQL memory handling, Oracle CLOB/CHAR replication of non-ASCII data, accurate SQL
New features in AWS DMS 3.6.0
- New metadata variables for transformations Introduced two new metadata variables for transformation rules: $AR_M_MODIFIED_SCHEMA and $AR_M_MODIFIED_TABLE_NAME. These variables allow you to create more dynamic and flexible transformations that can adapt to schema or table name changes during your migration process.
- Support for LOB Column Replication in UPSERT Error-Handling Mode Introduced support for replication of Large Object (LOB) columns when using the "No record found for applying an UPDATE: Insert the missing target record" error-handling option. With this enhancement, you can now accurately replicate LOB columns, ensuring complete and accurate data replication.
- PostgreSQL Memory Issue Resolved excessive memory consumption when using PostgreSQL as a source. Fixed an issue where the Write-Ahead Log (WAL) slot would continuously grow, leading to degraded performance. This update enhances the stability and efficiency of PostgreSQL migrations, especially for large databases or long-running tasks.
- Oracle Character Large Object (CLOB) and Character (CHAR) issue Addressed the issue where wide Character Large Object (CLOB) and Character (CHAR) values containing non-ASCII characters (e.g., special symbols or international characters) were not replicated correctly. This fix ensures accurate replication of large text data, reducing errors, and maintaining data consistency.
- Microsoft SQL Server Incorrect Latency Issue Resolved an issue where the Microsoft SQL Server source endpoint would incorrectly report very high latency. This fix provides more accurate performance metrics, allowing you to better monitor and optimize your SQL Server migration tasks.
- Microsoft SQL Server Metadata Issue Fixed an issue with redundant calls to retrieve other tables' metadata, which resulted in degraded performance and latency after a table's metadata had been altered. This optimization improves overall task performance, especially for databases with frequent schema changes.
- Microsoft SQL Server UPDATE Issue Fixed an issue where non-standard UPDATE operations caused tasks to terminate unexpectedly without generating error messages. This fix ensures that such operations are processed correctly, avoiding task failures during complex update scenarios.
- Batch Apply Large Object (LOB) issue Fixed an issue in Batch Optimized Apply mode where Large Object (LOB) lookup would fail to find a record when a DELETE operation and an INSERT operation were combined into a single UPDATE operation. This fix improves data consistency and integrity during migrations involving LOB data and complex Data Manipulation Language (DML) operations.
- Transformations Task Start Issue Addressed an issue where tasks involving numerous transformations would crash during startup. This fix ensures stability and reliability for tasks with complex transformation logic, enabling you to confidently execute data processing tasks.
- MySQL Data Definition Language (DDL) Issue Fixed a failure to capture special format Data Definition Language (DDL) changes during the Change Data Capture (CDC) phase. This fix ensures that all schema changes are properly replicated, maintaining schema consistency between source and target databases throughout the migration process.
- September 2025
- No date parsed from source.
- Detected by Releasebot:Sep 29, 2025
Database Migration Service by Amazon
AWS Database Migration Service 3.5.4 release notes
AWS DMS 3.5.4 brings data masking, faster data validation, and enhanced transformation throughput, plus a long list of bug fixes across PostgreSQL, MySQL, Oracle, S3, MongoDB/DocumentDB, Babelfish, DynamoDB, SQL Server, and more. Overall, a featureful, wide-ranging release.
New features in AWS DMS 3.5.4
Data masking Introduced data masking, allowing transforming sensitive data with options for digit randomization, masking, or hashing at the column level.
Enhanced Data Validation Performance Introduced enhanced data validation performance, enabling faster processing for large datasets during full load and CDC migration tasks across select migration paths.
PostgreSQL source unicode issue Fixed an issues for PostgreSQL source where degraded migration performance was observed while using filtering. Introduced disableUnicodeSourceFilter ECA to control this behavior.
Transformation support for enhanced throughput feature Introduce support for all transformation rules for the enhanced throughput feature.
PostgreSQL, test_decoding issue Fixed an issue for PostgreSQL source where certain events would not be replicated while using the test_decoding plugin.
MySQL to Redshift timestamp issue Fixed an issue for MySQL to Redshift migrations where a timestamp column would not be defined correctly on the target.
Oracle July 2024 PSU issue Fixed an issue for Oracle source with binary reader where DMS task would crash after applying Oracle July 2024 PSU.
MySQL secrets manager issue Fixed an issue for MySQL endpoint where credentials would become corrupted when using secrets manager.
Amazon DocumentDB/MongoDB data record handling issue Fixed an issue for Amazon DocumentDB/MongoDB endpoints where some records would be sent to the target twice causing duplicate key exception and AWS DMS task failure.
Relational to noSQL migration issue Fixed an issue for RDS for SQL Server to noSQL migrations where the document structure was incorrect due to incorrect PK handling.
Data validation issue with Oracle endpoint Fixed an issue for Oracle source where data validation would report false positives for null or empty LOBs.
Uniqueidentifier PK issue with Babelfish target. Fixed an issue for PG - Babelfish target where AWS DMS task would fail while replicating tables with PK defined as uniqueidentifier.
PostgreSQL source issue with MAZ. Fixed an issue for PostgreSQL source where AWS DMS MAZ failover would cause a fatal AWS DMS task failure.
Column order issue Fixed an issue where LOB data was not replicated correctly when the column order differed between the source and target.
Internal AWS DMS database contention issue Fixed an issue for internal DMS database where the AWS DMS task would fail due to internal AWS DMS database concurency issues.
Internal AWS DMS database structure issue Fixed an issues for internal AWS DMS database where the AWS DMS task would fail due to the lack of presence of certain internal database objects.
Oracle source data validaiton issue Fixed an issue for Oracle source where data validation would return false positives for certain rare types of replicated events.
Data validation issue for unicode data types Fixed an issue for the data validation feature where ceratin unicode data types were not compared properly which resulted in false positives.
Parquet target timestamp issue Fixed an issue for parquet target where zero-timestamp was replicated as null.
Babelfish target GeoSpatial data type issue. Fixed an issue for Babelfish target where the GeoSpatial data type was not supported.
Amazon S3 target issue with columns being added during CDC Fixed an issue for Amazon S3 target where new column additions were not handeled properly when the before image setting was enabled.
SQL Server 2022 CU12 issue Fixed an issue for SQL Server source where AWS DMS could not automatically implement MS Replication prerequisites on sources using SQL Server 2022 with CU12 or above.
PostgreSQL boolean issue Fixed an issue for PostgreSQL source where boolean data type would not be migrated correctly while MapBooleanAsBoolean was set to true and pglogical plugin was used.
TaskrecoveryTableEnabled setting issue Fixed an issue for the TaskrecoveryTableEnabled setting, where the AWS DMS task would fail upon task stop when set to true.
Data duplication with TaskrecoveryTableEnabled setting Fixed an issue where some transactions would be replicated twice when the TaskrecoveryTableEnabled setting was enabled.
MySQL 5.5 source issue Fixed an issue for MySQL source where AWS DMS task would fail due to inability to read the BINLOG from MySQL v5.5.
Data validation partition issue with corrupted data type names Data validation now prevents memory corruption during data type processing, eliminating fallback to row-by-row validation for affected partitions.
Amazon S3 source to target migration issue S3 source to target replication now properly handles external table objects during full load and ongoing replication.
Amazon S3 target CDC replication issue S3 target CDC replication processes CSV format data correctly during ongoing replication phase.
S3 replication issue Enhanced S3 directory cleanup process prevents task interruptions during migrations.
Data validation performance issue Data validation operation now optimizes transitions between validation phases, reducing unnecessary delays.
Data validation issue with specific data types Data validation now accurately processes unbound characters and TEXT data types, ensuring correct validation results.
PostgreSQL source issue with MAZ PostgreSQL source replication maintains connectivity during Multi-AZ failover events, preventing task failures.
Babelfish datetime validation issue Data validation now correctly compares datetime values when using Babelfish as a target.
MySQL source column replication issue MySQL source replication now correctly handles mid-table duplicate column additions, preventing task interruptions.
MySQL source column modification issue MySQL source replication maintains column sequence integrity when multiple columns are added during CDC operations.
DynamoDB LOB replication issue DynamoDB target replication now correctly processes LOB data during CDC, ensuring complete data transfer.
PostgreSQL boolean data validation issue PostgreSQL source data validation now correctly interprets boolean data type mappings, producing accurate comparison results.
DocumentDB connection recovery issue DocumentDB replication maintains data consistency during cluster connectivity interruptions and recovery.
Oracle extended VARCHAR2 data truncation issue Oracle source replication preserves trailing spaces in VARCHAR2(4000) columns when extended data type support is enabled.
SQL Server secondary replica DDL handling issue SQL Server source replication maintains connectivity during DDL operations on secondary replicas, preventing task interruptions.
Secret Manager special character handling issue AWS Secrets Manager connection strings now support special characters while preserving security protocols.
MongoDB/Amazon DocumentDB duplicate key issue MongoDB and Amazon DocumentDB replication prevents record duplication that previously triggered key constraint errors.
Oracle timestamp handling issue Oracle source replication accurately processes timestamp values across various session time zone configurations.
Oracle data conversion issue Oracle source replication now handles data type conversions more robustly, preventing ORA-01460 errors.
SQL Server 2022 CDC replication issue SQL Server sources (CU12 and above) can now automatically implement MS Replication prerequisites in AWS DMS.
Test decoding DDL handling AWS DMS ignores DDL statements for tables not configured in table mappings, preventing unnecessary processing of source database schema changes for unmapped tables.
Columns truncation from source SQL Server Views When migrating data from source SQL Server view to target endpoints, the column length is correctly preserved and no columns are truncated.
Metrics Recording for enhanced data validation AWS DMS now accurately reports validated record metrics when using enhanced data validation.
DMS task resume issue after upgrade When resuming tasks after an AWS DMS version upgrade, DMS tasks do not fail to resume due to incompatible internal file formats.
SQL Server Always On primary replica issue Fixed an issue where AWS DMS now correctly identifies the primary replica in Microsoft SQL Server Always On Availability Groups, resolving previous case sensitivity detection errors.
PostgreSQL target numeric data handling issue Fixed an issue where AWS DMS tasks failed when migrating unbound numeric data types to PostgreSQL target endpoints.
Data validation character handling issue AWS DMS now correctly validates CHAR and VARCHAR data during migrations, eliminating false positive reports in validation tasks.
Amazon Redshift LOB parallel apply issue AWS DMS prevents data corruption in Large Object (LOB) data during parellel batch operations when using Amazon Redshift as a target endpoint.
Data validation with column filter issue Validation failures are prevented and queries are successfully executed on Amazon S3 target when source column filters are applied to VARCHAR, CHAR, DATE, and DATETIME data types.
S3 validation data persistence issue When using Amazon S3 targets, consistent data validation states are maintained throughout Change Data Capture (CDC) operations.
String formatting validation issue Fixed an issue where data validation failed due to string formatting errors during record comparison operations.
- Aug 29, 2025
- Parsed from source:Aug 29, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight now supports connectivity to Google Sheets
Amazon QuickSight announces GA of a native Google Sheets connector, enabling login-based access and import of Sheets into SPICE datasets for analysis. Available in multiple regions worldwide. See blog post for details.
Today, Amazon QuickSight is announcing the general availability of a native Google Sheets connector.
Customers can now connect to Google Sheets by logging in with their Google account and importing sheets into a QuickSight SPICE dataset for analysis.
Google Sheets connector for Amazon QuickSight is now available in the following regions: US East (N.Virginia and Ohio), US West (Oregon), Canada (Central), South America (Sao Paulo), Europe (Frankfurt, Stockholm, Ireland, London), Asia Pacific (Singapore, Tokyo, Seoul, Sydney). For more details, read our blog post here.
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/08/amazon-quicksight-google-sheets-connector/
- Aug 29, 2025
- Parsed from source:Aug 29, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight now available in Israel (Tel Aviv) Region and United Arab Emirates (Dubai) Region
Amazon QuickSight is now available in Israel (Tel Aviv) and the United Arab Emirates (Dubai), expanding its global reach to 25 regions. The service remains browser-based with scalable dashboards, embeddable analytics, and no infrastructure management required, now accessible in two new regions.
Amazon QuickSight is a fast, scalable, and fully managed Business Intelligence service that lets you easily create and publish interactive dashboards across your organization is now available in Israel (Tel Aviv) and United Arab Emirates (Dubai) Regions. QuickSight dashboards can be authored on any modern web browser with no clients to install or manage; dashboards can be shared with 10s of 1000s of users without the need to provision or manage any infrastructure. QuickSight dashboards can also be seamlessly embedded into your applications, portals, and websites to provide rich, interactive analytics for end-users.
With this launch, QuickSight expands to 25 regions, including: US East (Ohio and N. Virginia), US West (Oregon), Europe (Spain, Stockholm, Paris, Frankfurt, Ireland, London, Milan and Zurich), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Beijing, Tokyo and Jakarta), Canada (Central), South America (São Paulo), Africa (Cape Town), AWS GovCloud (US-East, US-West), and now Israel (Tel Aviv) and United Arab Emirates (Dubai).
To learn more about Amazon QuickSight, please see our product page, documentation and available regions here.
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/08/amazon-quicksight-israel-uae-region
- Aug 18, 2025
- Parsed from source:Aug 18, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight expands limits on calculated fields
Amazon QuickSight raises calculated fields limits to 2000 per analysis and 500 per dataset, enabling more transformations on large datasets. Natural language calculations via Q are now available in all supported regions, expanding authoring options.
Amazon QuickSight has increased the limits on number of calculated fields allowed in an analysis from 500 to 2000, and from 200 to 500 per dataset. This update enables authors and data curators to create more transformations on their data and draw additional complex insights. This is especially useful for authors and data curators who work with really large datasets and cater to multiple end user personas.
In regions where Amazon Q in QuickSight is available, users can also use natural language to build calculations using Q.
The new calculated fields limits are now available in all supported Amazon QuickSight regions.
To learn more about calculated fields and other QuickSight limits, visit item limits for analysis.
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/08/amazon-quicksight-expands-calculated-fields/
- Jul 2, 2025
- Parsed from source:Jul 2, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight supports 2B row SPICE dataset
Amazon QuickSight Enterprise now supports SPICE datasets up to 2 billion rows, doubling capacity from 1B without slowing ingestion or queries. Available in all QuickSight regions, enabling longer time ranges and more categories for insights.
Amazon QuickSight Enterprise Edition customers can now load up to 2 billion rows of data into Super-fast Parallel In-memory Calculation Engine (SPICE) datasets. This improvement doubles previous capacity of 1 billion rows without slowing ingestion speed or query performance, enabling customers to explore business data over longer time periods or more categories to discover new business insights. Learn more.
The new SPICE dataset size limitation is now available in Amazon QuickSight Enterprise Editions in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, Europe (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and AWS GovCloud (US-West).
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/07/amazon-quicksight-2b-row-spice-dataset
- Jul 1, 2025
- Parsed from source:Jul 1, 2025
- Detected by Releasebot:Sep 29, 2025
Amazon QuickSight launches Trusted Identity Propagation (TIP) for Athena Direct Query
Amazon QuickSight adds Trusted Identity Propagation for Direct Query with Athena, enabling fine-grained, Lake Formation–controlled access and reusable dashboards across users. Available in Standard and Enterprise in multiple regions.
Amazon QuickSight now supports Trusted Identity Propagation (TIP) for Direct Query Datasets connecting to Amazon Athena data sources. With this capability customers can apply fine grained access controls using Lake Formation Rules to govern user access to data in QuickSight. TIP allows Authors to securely control rows and columns of data returned by queries allowing the same dashboard to be used across customers or departments. For further details, visit here.
The new Athena Direct Query Trusted Identity Propagation is now available in Amazon QuickSight Standard and Enterprise Editions in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, Europe (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and AWS GovCloud (US-West).
This is a companion discussion topic for the original entry at https://aws.amazon.com/about-aws/whats-new/2025/07/amazon-quicksight-trusted-identity-propagation/
