March Homeruns 🌸⚾

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Omni

What is it: Omni Analytics has added write back capabilities with Data Input. This feature will allow the end users to enrich data models by integrating ad-hoc data via CSV, Excel or copy-pasting. New data can then either be consumed in the workbook for a single user, or promoted to a shared data model for more widespread consumption. Additionally, such data can also be written to data warehouses which could allow circumventing data teams altogether, thereby reducing time to realize value from data.

Documentation regarding enterprise use cases such as Sharepoint ingestion to ensure scalability, and specifics around data warehousing write back is still limited. However, you can still read all about the feature here.

Why is it relevant: Write back capabilities are table stakes for any BI software with the push towards self service analytics. Omni (and other new age BI platforms) have been listening to its users and bringing in features that legacy BI players are still catching up to. This is great for the larger BI industry as it moves towards democratizing analytics.

However, as with any self service tool, care has to be taken to ensure governance is in place to avoid an unmanageable data sprawl. Additionally, while the BI industry is moving rapidly towards self service, key considerations like compute costs, performance and scalability for inputs still need to be addressed. Until those considerations are addressed, adoption of features like write-back may see a spike and then an eventual plateau.

dbt

What is it: dbt copilot is now generally available. While “Copilot” in a data platform is nothing newsworthy, what makes this one interesting is the ability to 1) prompt Copilot to provide contextually aware code suggestions as you are building the code, 2) automate tests in dbt and 3) build semantic models and metrics automatically.

Additional updates include a beta release for Bring your OpenAI key and integration with Azure Open AI service.

Check out this quick demo below for details.

Read the entire release here.

Databricks

What is it: If you use Databricks and Power BI, this one is huge. Databricks has announced **wait for it** Power BI Workflows. This will allow Data teams to build a unified pipeline that can trigger refreshes downstream on Power BI semantic models without having to step foot into Power BI service. Data teams will also be able to realize useful features such as task dependencies, schedules/triggers, retries, and notifications for such pipelines.

Power BI tasks will support:

• Unity Catalog data objects including tables, views, materialized views, and streaming tables

• Publishing, updating, and refreshing semantic models

• Import, Direct Query, and Dual Storage modes

Read all about it here.

Why is it relevant: Setting up data refreshes for Power BI datasets can be tricky to achieve when multiple data objects are at play, with their own orchestration schedules. Power BI workflow in Databricks can be a game changer, ensuring semantic model refreshes are triggered at the right time and only when needed. Databricks workflows could potentially also reduce costs as you would not need to run Power BI refreshes unless there is fresh data in the system.

BigQuery

What is it: BigQuery Studio has introduced native git integration with BigQuery repositories. With this pre-GA release, users will be able to take advantage of git based version control directly in BigQuery GUI. Third party git provider integration has also been provided for platforms like Github, Gitlab, Bitbucket and Azure Devops Services.

Read all about the announcement here. You can also check out the documentation here.

Why is it relevant: A typical SDLC cycle has CI/CD practices at its core. Analytics development life cycle have also adopted these software engineering best practices. Without Git integration, users are forced to copy paste code or rely on manual workarounds. This feature should make life a little bit easier for the hardworking BigQuery DEs out there.

AWS

What is it: AWS Redshift has announced single sign-on (SSO) through its IAM Identity centre for its Data API. This ensures role based access control (RBAC) through Row Level Security and Column level security is propagated consistently in an application querying Redshift. It also eliminates the need for manually configuring drivers like ODBC/JDBC when connecting to Redshift, making life much easier.

Read all about it here.

Data events action calendar 📅

• Mongodb local is happening in Toronto on April 15th. Details here.

• Google Cloud Next is happening in Las Vegas from April 9-11th, 2025. Details here.

• PostgreSQL Development Conference is Montreal from May 13-16th. Details here.

• Snowflake Data Summit will be in San Francisco from June 2-5th. Details here.

• Databricks Data + AI Summit will be in San Francisco from June 9-12th. Details here.

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