Version 26.7.0

Date: 11th July 2026

• Multi-Factor Authentication (MFA): ADOC now supports Time-based One-Time Password (TOTP) as a second authentication factor for users signing in with a username and password. When MFA is enabled for a tenant, users are prompted to enter a one-time code from a TOTP authenticator app after entering their credentials. Tenant administrators can enable or disable MFA for their tenant and reset MFA credentials for individual users. For more information, see Sign In with Multi Factor Authentication.

• Business Glossary: ADOC now includes a Business Glossary, available under Governance, where organizations can create and manage a centralized repository of business term definitions. Terms are organized into glossaries and categories, and each term can include a definition, acronym, and formula. Terms can be associated with Data Products and assets, and linked to related terms using Synonyms, Related, Children, and Parent relationship types. For more information, see Business Glossary.

• acceldata-sdk-python: ADOC now offers acceldata-sdk-python, a new typed Python SDK for catalog, pipeline, policy, and tagging workflows, replacing the legacy acceldata-sdk package. acceldata-sdk is now in maintenance mode and supported for up to three additional releases. For more information, see acceldata-sdk-python Overview.

• Data Products: Published Data Products in the Marketplace are now viewable by any user with tenant-level Data Products view permission, in a read-only view. The Lineage tab now shows PowerBI and Tableau reports along with complete upstream and downstream pipeline paths, with clickable navigation to pipeline details. A dedicated Delete permission has also been added for Data Products, separate from Modify, in both Tenant and Domain roles. For more information, see Data Products.

• Domain Roles for Service Users: Service Users can now be assigned Domain roles directly, giving them the same domain-level access as a regular user without requiring group membership. For more information, see Service Users.

• Uniqueness Check: Configurable NULL Handling: The Uniqueness Check rule in Data Quality policies now includes an Ignore NULL values when validating uniqueness option. When enabled, NULL values are excluded from the uniqueness calculation and multiple NULL values in a column are not counted as duplicates. The option is unchecked by default, preserving existing behavior for all configured policies. For more information, see Data Quality Policy.

• Pipeline Automation: Guided Configuration: Configuring automations within a pipeline is now a guided workflow. Selecting an automation type (Profiling, Data Quality, or Reconciliation) automatically surfaces only the assets and policies relevant to the selected pipeline, and the asset selection field is now a searchable dropdown. For more information, see Create a New Automation.

• Manage Policies: Policy Execution Timeline: The Manage Policies page now includes Started At, Ended At, and Total Execution Time columns, allowing you to track when a policy ran and how long it took to complete directly from the table. For more information, see Manage Policies.

• Asset Profile: Profile Data Export: A Download button is now available on the asset Profile page, allowing you to export profile data as a CSV file. The button is shown only when profile data is available, and any sensitive data masking applied to your view is preserved in the downloaded file. For more information, see Profile Assets.

• Jobs Page: Source Type Filter: The Jobs page now includes a Source Type filter. Selecting a source type automatically narrows the Data Source dropdown to show only data sources of that type, making it easier to find relevant jobs in environments with multiple source types. For more information, see Monitoring and Managing Jobs.

• Alerts: Inline Time Range Filter: The time range filter (Time Slicer) on the Alerts page has been moved from the top-right corner into the main filter toolbar, aligning it with the other filters for better visibility and a more consistent filtering experience. This change has also been applied to Manage Policies, Rule Listing, Audit Logs, and Jobs pages.

• Fixed an issue where pipeline task statuses were not displayed for all connected pipelines in the Lineage view. Previously, only pipelines directly associated with the selected asset showed task status; upstream and downstream pipelines appeared without execution state.

• Fixed an issue where relative threshold evaluation was bypassed indefinitely when "Include in Overall Reliability Score calculation" was turned OFF, causing the system to always return RELIABLE regardless of actual data quality. The historical baseline is now populated independently of the scoring flag.

• Fixed an issue where aborted pipeline task spans were incorrectly displayed with a green checkmark (✅) in the Events List side panel, contradicting the red aborted status shown on the Gantt timeline view.

• Fixed an issue where Export/Import failed for Freshness, Schema Drift, and Anomaly policies with a "No Backing Asset Found" error during rule import processing. DQ policies were unaffected.

• Fixed an issue where MongoDB SQL Views with nested aggregation pipelines containing multiple $group stages returned multiple rows instead of a single consolidated aggregated row. This occurred because the MongoDB Spark Connector's default partitioner executed the aggregation pipeline independently on each partition, causing the final $group (_id: null) to produce one row per partition instead of one merged result.

• Fixed an issue where the Validate Query functionality for BigQuery SQL-Based policies did not apply a record limit, causing queries to execute against the full dataset and leading to performance degradation, timeouts, and unresponsive standalone service.

• Fixed an issue where SQL expression rules failed with a syntax error when a column name was a substring of another column name, causing incorrect backtick placement during Spark execution.

• Fixed an issue where users were unable to save Auto Anomaly policies on S3 parquet assets.

• Fixed an issue where persisted column selections were reset after SQL query revalidation in Data Quality Custom SQL policies using the Spark engine.

• Fixed an issue where Snowflake Pushdown DQ policy persistence did not place parquet files inside the respective RECORD_TYPE directories (success_records/error_records) and incorrectly placed result.json under the success_records path.

• Fixed an issue where ADOC failed to uniquely identify tables across schemas when the same table name existed in multiple schemas, causing data retrieval failures.

• Fixed an issue where Data Plane Application Config values were reset to defaults after performing a Rotate Keys action followed by Validate, Save & Apply on the Deployment Config page. This caused loss of customer-specific configurations including Karpenter autoscaling protection, Spark pod annotations, and custom crawler sizing.

• Fixed a performance issue where the Policy Executions dashboard widget failed to load data and returned 504 timeout errors on tenants with large volumes of policy execution data.

• Fixed an issue where users were unexpectedly logged out while actively working on ADOC, primarily when navigating the Pipelines page.

• Fixed an issue where SQL view creation failed on Azure MSSQL tables when using CTE queries (WITH clause).