Table Of Contents
Table Of Contents

Release Time Machine

This page documents updates to AgileData.

AgileData contains features that are designed to make collecting, combining and consuming data simple.

The AgileData team are constantly adding more features which result in reducing the friction to manage data in a simply magical way.

As we release each new feature we list it briefly in this section. They are ordered by the date we released them.

7 February 2023

  • Capture source_partition in the data_quality table in spanner so we can rollback if necessary to do a full table validation when required

  • Daily Health Check - check_trust_rules_passed included in daily_sla_checks

  • Daily Health Check - check_anomaly_summary included in daily_sla_checks

  • Remove dataplex data quality pattern and redirect to updated validate_table endpoint to run trust rules

  • Tenancy Features - only update catalog for shared tiles when the tile hasn’t already been inserted - preserve user topics and description

  • Use ‘Show Details’ pattern on notifications screen to open existing preview modal with the results of data quality exceptions (stub feature)

  • Include BQ slot time in job statistics modal screen

  • Exclude reserved columns from trust rules screen so users can’t set trust rules against system columns - they are already validated automatically.

15 January 2023

  • New error handling pattern in all cloud functions to send errors to a) cloud logging for the app to display and b) websocket notifications for the app to display

  • Updated pattern for identifying event (vs change) source data based on a known list of event columns - eg event_timestamp, event_date, event_type etc

  • Updated event table template to autocreate the event key based on all the ‘output event key’ rules the user creates

  • Updated notifications and cross navigation in the app as a proof of concept for notifications

  • Small updated to daily SLA and Anomaly checks to harden the patterns

14 December 2022

  • New json to jsonl file converter for dropped files

  • Daily SLA check pattern - auto scheduled and updated daily

  • Tag BQ event jobs with the config version to allow displaying in the application

  • Draft of anomoly checking and display into event notifcations

  • Table level trust rules (anomaly and sla)

  • Extend tenancy attributes to include deployment versions and tenancy created attributed

10 November 2022

  • Persist BQ profiles into Spanner for re-use and increased performance in the app

  • First draft of auto generating C, D and E rules using the persisted profile data

  • Inclusion of topics on the config (rule) endpoints

  • Include data preview on the column list endpoints (for output fields rule step)

  • Push ARRAY/STRUCT metadata into the data preview results so the app can customise display for nested/repeated data

  • Update logic for calculating a watermark for running previews - try 14 days, then full back to max date in last 6 months

  • Augment the unnest_fields() and unnest_data() functions to traverse VERY wide tables to create usable preview/column data

  • New file_header_parser function to more accurately work out header rows and delimiters being used

  • New create_sample_table function which uses the new file header parser

  • Update upsert templates - reverted to INSERT() VALUES() pattern

  • Combine trust scores and persist against consume tiles (ie aggregate up the score from ensembles)

  • Updated rule type endpoint with better sorting for readability

  • Implement logrocket logging into the app layer

  • Implement dopt user registration into the app layer

04 September 2022

  • Updated cloud build pattern for all code repositories. We now use a tag based deployment pattern for all tenancies.

  • Update the ‘view change rules’ and ‘view consume rules’ links on tiles to be context aware

  • Include ‘advanced options’ show and hide for consume config

  • Include the catalog_key in the ensemble_config payload to enable cross screen browsing in the app

  • Use coalesce() for user defined keys in config. Otherwise concat() of null keys (especially in events) produces a null key value.

18 August 2022

  • ALL NEW jinja templates deployed to all projects. Major re-write and re-factor of all change rule and config generation.

  • Includes the new patterns to compare existing templates with new templates when new chnage rules are introducef.

12 August 2022

  • New cloud function export_history_tables which exports all history tables from one project as avro files to be ingested into another project

  • Alias driving tables in consume pattern to avoid issues with reserved words

  • Updated check_job_status which augments the event_logging table in spanner for load_jobs. Updates the rows_loaded attribute after load completes

  • small bug fixes for ensemble_check and check_load_position.

  • Mark consume tiles that have a report_key against them (initial plumbing for reports screen)

  • Export all css and js assets into storage bucket for LogRocket to use when rendering activity reports.

01 August 2022

  • Update the parse status for filedrop rules so we can set them to Active in the app

  • New compare_template endpoint to compare existing config against config generated from new templates

  • Update the sqlparse formatting for generated sql so when it displays for magicians in the app its more readable and standardised

  • Add policy tags (group membership) to the members screen in frontend

  • Update preview view logic to first find the latest effective data in a view then set the preview window (instead of trailing 14 days)

17 July 2022

  • Updated Search endpoint to rank and return most relevant results in order

  • New cloud function excel_to_csv which parses a dropped spreadsheet and creates a csv file for each worksheet

  • Updated filedrop to retry a failed file load using a string version of schema (bypass autodetect)

03 July 2022

  • Move invite_user email html into a jinja template

  • Draft of new jinja rule templates - break up large logic blocks into smaller components for reusability

  • Update the Given Filedrop rule file names to exclude schema and type as this pattern is just to create a filedrop to landing wildcard mapping rule

  • Secure all POST endpoints in API layer to either Admin or Editor roles

14 June 2022

  • Profile all history tables and persist into a new _profiles table for analysis and auto rule creation

  • New endpoint to auto generate a set of C and D tables and rules based on _profiles data

  • Union usage from the -c project into -d results and display in the app monitoring report

  • New manage_gsuite functions to grant|revoke users to user groups

  • New union pattern to create the required sql to union two or more tables/views together safely

30 May 2022

  • New concept and event matrix endpoints

  • Addition of catalog_key into config responses and config_key into catalog responses for cross navigation in app

  • New lookahead manifest pattern for loads that start without a manifest but it exists by the time they finish

  • Caching pattern for app engine - always cache app pages and cache select api responses

  • BQ sample function when previewing event_* datasets to reduce data scanned

24 May 2022

  • Cleanup bq_table and bq_column metadata when logical tables are deleted in app

  • New jinja template to use BQ pivot() function

18 May 2022

  • Generate file transfer keyfile for users to automate bucket transfers

  • Import and Export endpoints to create and read yaml rule files

  • Function to archive BQ tables to GCS bucket

3 May 2022

  • Spanner - persist ensemble_config into a table (previously calculated using a view)

  • Switch data map and gui outputs to use the new ensemble_config table

  • Execution - update the job_completed function to maintain the ensemble_config whenever concepts,details or events are changed.

29 April 2022

  • Tracking - track last_executed for all config rules

  • Load Position - Deploy the check_load_position() function which returns dynamic watermarking based on table and config metadata

14 April 2022

  • Data Search - deploy new BigQuery search function to allow users to search within tiles

12 April 2022

  • Data Map - updated to include shared datasets and the ability to execute rules against them as if they were local, ie run all steps from here

  • Tasks - new task endpoints deployed, ability to create and update tasks (trello style screen in app)

11 April 2022

  • Shared Datasets - tenancy feature to share an external dataset and have the tiles appear within the local project

  • Templates - new create and load templates for external shared datasets

31 March 2022

  • Messaging - deploy websockets server to enable realtime chat and messages within and between orchestration layers

9 March 2022

  • Data Quality - Run data quality (data trust) rules after BigqQuery loads complete, and update summaries used by gui to show a trust score for each tile

18 January 2022

  • Preview - Delete Items

    App, Catalog, Topic Canvas, Rules, Manage

    The ability to delete a Catalog Tile, Topic Canvas or Rule. When an item is deleted it is a ‘soft’ delete. Deleted items are available in a new Manage > Deleted Items screen and can be undeleted if required.

17 January 2022

  • Create Concept button in Topic Canvas

    App, Topic Canvas

    Fixed unplanned trick in Topic Canvas where the Create button for a new Concept was hiding.

13 January 2022

  • Default topic for events created via topic canvas

    App, Topic Canvas, Catalog

    When a event is defined in the topic canvas the Default topic tag is automagically assigned. Previously the topics were automagically created based on the cocenpts that werre added to the event, but this created to much noise and made it more complex than it needed to be.

  • Streamlined deployment process

    Platform, DataOps

    Streamlined the automation of code deployed across tenancies. This included the deployment of all code components. Reduced the effort to deploy across multiple tenancies.

12 January 2022

  • Removed Tenancy Dependency for deployment

    Platform, DataOps

    Removed the need to inject the tenancy name in the deployment process, reduced time to deploy.

From the begining of time

  • Data Validation across areas

    Automagical reconciliation of data between areas and alerting of any anomaly’s.

  • Rule execution moved to pub/sub

    Refactored rules hand offs to decouple them from direct hand off’s to using pub/sub.

  • Dependency Manifest

    Dynamically determine dependencies across rules at time of rule execution to ensure immediate consistency of concept, detail and event data when refreshing Consume views.

  • Consume API

    Ability to automagically push Consume views to a csv file to enable them to be consumed via an API.

  • Collection effective dated

    Ability to add a effective date to Landing rules to define a date key for determining change data when loading History.

  • Google Secret Manager for Third Party Access

    Leverage Google Secret Manager to provide a central place and single source of truth to manage, access, and audit secrets for third party app integration.

  • Levenshtein Distance Rule Pattern

    Added Levenshtein rule pattern to allow Single Magic Record (Master Data Management) matching.

  • DDL Conversion

    Extract table DDL from Oracle and SQL Server systems of records and convert it to BigQuery DDL to automatically create the tables in AgileData.

  • Shopify Change Rules

    Define default change rules for Shopify, including Customers, Products, Orders and Transactions.

  • Unest Change Rule

    Ability to define an unest rule step in a change rule.

  • Slack Logging Notifications Channel

    Integrate Slack as a notification channel to view runtime logs and errors

  • Schedule based invocation of rules

    Rules can be triggered/innovated based on a fixed schedule, for example at 2am each working day.

  • Shopify API Collection Rule

    Change rule to allow you to automatically collect data from the Shopify API.

  • Rule and catalog API

    API to allow rules and catalog entries to be called via the GUI or any other mechanism.

  • Rule execution code visibility

    You can now see the code that will be executed for a rule.

  • Rule Natural Language Parsing

    First version of natural language parsing of rules to:

    identify key change rules words define key words for rule pattern execution

  • Natural Language Rule Framework

    Allows the parsing of a rule and storage of the rule pattern mapping in a dedicated high performance data repository to allow multiple concurrent requests from the GUI.

  • Concept and Detail Storage

    Concepts and Detail catalog entries are now stored in a dedicated high performance data repository to allow multiple concurrent requests from the GUI.

  • Rule Storage

    Rules are now stored in a dedicated high performance data repository to allow multiple concurrent requests from the GUI.

  • Docs.AgileData.io

    Automated deployment framework for documentation and documentation site setup.

  • Rule Validation

    Rules SQL is validated before rule is submitted to pub/sub for execution.

  • Automated User provisioning

    Users are automatically provisioned when tenancy is created.

  • Soundex Rule Pattern

    Added soundex rule pattern to allow Master Data Management matching.

  • Automatic provisioning of security groups

    When automatically provisioning a tenancy standard security groups are also automatically deployed.

  • Filedrop bucket naming

    Improved security of filedrop area by anonymising the filedrop bucket names to ensure they are not discoverable.

  • Separation of the filedrop area

    The filedrop area is separated from other data areas to increase security in depth.

  • Consume rules

    You can create a rule that uses a consume table as an input and outputs another consume table. This is useful when you want to create custom consume views with “pretty” field names (aka a semantic layer) for your visualisation or analytics tool to use.

  • Automatic creation of consume views in the consume area

    Consume views are automatically created in the consume area when the consume tables are created in the event/consume layer.

  • Separation of the consume area

    The consume area is separated from other data areas to increase security in depth.

  • Data PII profiling

    Profile data to identify any personally identifiable data that is being stored.

  • DDL files to create history tables

    Allows files containing DDL to be droped into filedrop and they generate the table structure for the history tables.

  • Version Change Rules

    When a change rule is updated and the rule executed the rules is versioned in config.

  • Data profiling stored in catalog

    Results of the data profiling is stored against the object in the data catalog.

  • Data Lineage

    Initial cut of tracing lineage of data in filedrop all the way through history and event processing to the consume tables.

  • Updated Detail Fields

    When you change the field list for a Detail change rule, the Detail table is dropped and rebuilt on next load to accommodate the field changes.

  • Rollback of loads

    Option to reset load watermarks to force reload of data into history, events or consume.

  • Load statistics

    Persist load statistics for data movement in filedrop, history, events and consume.

  • Rule execution state

    Manage rule execution state to ensure two rules cannot simultaneously update the same concept, detail or event table

  • Callbacks

    Rules issue a callback to dependent rules to remove the risk of time out issues with multiple dependent rule execution.

  • Filedrop based invocation of rules

    When a file is dropped the relevant rules tat are dependent on that file will automatically execute.

  • Pub/Sub

    Rule are executed via a publish and subscribe pattern rather than a data flow pattern to allow rules to be authored and executed in isolation of other rules, while also allowing them to be combined into an end-to-end data pipeline.

  • Autodetect preloaded csv file in filedrop

    When dropping a new csv file into the filedrop area the file is compared against the previous file loaded and if it is the same the file is not reloaded.

  • Autodetect csv file metadata

    For new files the ingestion process automatically samples the csv files and determines the file structure. This create a change rule to load the data into a history table. The metadata description and change rule is persisted is retained to ensure the same change rule is used on subsequent files.

  • Auto Generate Consume Tables

    After a change rule has executed consume tables are created. Concepts and any related details are denormalised into a single table. Events, the relevant Concepts that are part of the event definition and the details for those concepts are denormalised into consume tables. All tables are as at the current point in time.

  • Rule Master Pattern - Output Concat Key

    Allows the selection of multiple fields to use as the business key for a History table, Concept, Detail or Event.

  • Rule Master Pattern - Output Key

    Allows the selection of the field to use as the business key for a Concept, Detail or Event.

  • Calculation change rule pattern

    Allow the use of a formula to calculate a value, for example a / b

  • Aggregated change rule pattern

    Allow the use of a formula to calculate a value, for example sum (a)

  • Parse change rule pattern

    Allow the use of a formula to parse a field, for example split(trim(a),’ ‘) : a1

  • Single table relationship change rule pattern

    Join the fields in a single table.

  • Multiple table relationship change rule pattern

    Join fields across two tables.

  • Field filter change rule pattern

    Filter on a field for a given value.

  • New event change rule pattern

    Config support the creation of event records via a change rule.

  • New detail change rule pattern

    Config support the creation of a detail records for a concept via a simple change rule.

  • New concept change rule pattern

    Config support the creation of a concept records via a simple change rule.

  • Change data recognition and history point in time updates

    When new data is ingested into the history tables, and similar data has previously been ingested into those tables, the ingestion processes identifies new records versus updated records. For records that have changed rather than being new, the previous version of that record is end dated.

  • File drop area

    Users are able to drop a file into a filedrop bucket to enable it to be consumed into the history tables.

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