More productivity. More efficiency. Scalability. There are many enterprise benefits to the cloud. It’s no wonder nearly all enterprises use cloud services.
However, challenges abound. Complex, hybrid ecosystems and siloed data slow decision-making and is a drag on innovation. It’s too often the case that business users have limited information about data, data analysts can’t access or verify data quality, and engineers lack visibility into technical lineage.
We’re excited to announce the 2023.02 release of Collibra Data Intelligence Cloud to help address these challenges and maximize the value of today’s data. This latest release includes new integrations, Collibra Protect support for BigQuery, and new Data Quality & Observability features that enable deeper visibility for better insight into the data that matters most. These new capabilities will provide complete visibility into cloud data assets from source to destination, and deliver trusted data to all users across the organization.
Collibra Data Intelligence Cloud connects data sources across Snowflake and Google Cloud Storage, extends visibility across data sets, enables more robust data governance, and leverages the true value of metadata.
These newest partner integrations provide complete visibility into cloud data assets from source to destination, delivering trusted data to all users across the organization.
Get visibility across your Snowflake data
Snowflake has become a popular cloud data platform.
With Snowflake Lineage, now Collibra Data Intelligence Cloud delivers enhanced end-to-end visibility of all data stored in Snowflake, offering a clear view of data flows from system to system, including transformations coming from queries, views, stored procedures, tasks, bulk data loads, snowpipes, and streams.
The functionality is available by tapping into Snowflake Access History, which allows for the automated extraction of lineage from any transformations that run on the Snowflake platform. Lineage extraction is available on any orchestration tool, including SQL scripts, stored procedures, ETL tools, or Python scripts.
Also, a new Snowflake tag ingestion capability enables Snowflake tags to be incorporated into the Collibra Data Catalog. By leveraging Snowflake tags that categorize data users can develop more compliant business or policy processes and workflows.
Protect your data with Collibra Protect for Google Big Query
With Collibra Protect, enterprises get intelligent data controls from a unified platform to discover, define, and protect data across the cloud.
The Google Cloud Platform is an integral part of the data ecosystem of many organizations. The introduction of Collibra Protect for Big Query provides intelligent data controls to discover, define, and protect data across your enterprise cloud. With Collibra, now data professionals can use Big Query to enable enterprise policy decision-making based on who, what, and why data should be accessed.
If you’re running Google BigQuery, you’ll want to make sure sensitive data is protected. Now, sensitive data can be selected by the user and a policy can be invoked.
This integration of Google and Collibra makes it easier for enterprises to take control of data, scale access, and accelerate analytics, all while maintaining compliance with privacy and policy practices.
Collibra Protect offers:
- Policy overview page: Maintain oversight of all places and owners
- Policy builder: No-code, drop-down rules creation so you can create and execute policies in minutes
- New data protection features: Masking, hashing, and redacting
- Policy audit: See product policies, protected data, and user access
- New asset page integration: New Data Protection tab displays summary of Data protection standards and data access rules
Plus, you can filter by group and search for the name of relevant policies.
Collibra Protect admins can now create custom prescriptive paths for the asset types through the API. The customization includes creating, modifying, or deleting prescriptive paths.
Our latest Google Cloud Storage (GCS) integration enables organizations to ingest, catalog, and govern metadata within Collibra Data Intelligence Cloud.
Enhance your Tableau integration
Our latest Tableau integration improves the ability to interpret Tableau technical lineage and track the transformations between objects with customer SQL and customization rules. Now, you’ll be able to enable users to easily identify Tableau columns, tables, and data sources with the same name and rename it in Tableau for clarity. A more flexible BI operating model supports the ability to change the names of attribute types in Tableau.
According to our analysis, this enhanced integration improves harvesting performance by up to 10X.
New Data Quality & Observability features
We’ve additional improvements to enhance data quality and observability. The new operational reports and self-serve views provide real-time insights (e.g., missing jobs, oversized jobs, rule performance etc.) to understand your usage, optimize performance, and drive adoption of your data quality efforts.
Fresh data is also important because it has a huge impact on your bottom line. Unfortunately, that impact often goes undetected until it’s too late. With the introduction of data freshness rules and alerts help you see inside data pipelines to reveal staleness in your data operations.
And there’s even more good news
This release also includes a new Homepage Editor and a public beta for Lineage on Edge to help deliver an even more frictionless user experience. By streamlining the configuration and access to data your organization can focus on delivering insights and driving better business decisions.
The new Collibra Data Intelligence Homepage Editor is more intuitive and allows for much greater configurability. You can now customize your card placement to meet the specific needs of your business.
You can now enable technical lineage via Edge for an expanding set of supported JDBC, BI and ETL data sources . This feature is in public beta and includes:
- Seamless integration with Data Catalog
- The Edge User Interface (UI), instead of Command Line Interface (CLI)
- Connections via Edge, instead of lineage harvester drivers
- Job scheduling via Data Catalog
Supporting today’s most demanding data landscapes
As the ecosystem of data becomes ever more complex organizations need a unified data intelligence platform that can connect to any data source in order to discover, understand, trust and access their data at scale.