Collibra Lineage Reviews

I have been working with Collibra Lineage for more than five years now, overall almost five years. I am using the product myself for molecular consultants and resellers at a consulting firm.

The best features of Collibra Lineage are quite user-friendly, and business users can use it much better than other catalog tools such as Talend or challenges according to my team. The traceability diagrams are very complicated and not user-friendly at all.

The automatic data flow mapping is effective; some of the integrations pose issues in terms of the configuration of those data sources, but it works fine. Even transformation platforms such as DVD work really well.

The integration with other Collibra Lineage products is valuable in our data governance initiatives. I have worked on many migration projects where organizations are moving away from other catalogs such as Talend or Informatica Axon and Informatica EDC to Collibra Lineage. I have worked on projects where we are creating the catalog from scratch on both fronts.

The main use case for Collibra Lineage is focused on the data product integration. They want the data lineage, data product lineage, and data products. They have some AWS platform in their state, and they have implemented external layers on top of that, including iceberg tables. The data lineage and delta are used to write a model with data products in Snowflake. In the Snowflake layer, they have their reporting in Tableau.

They have implemented a model with data products in Snowflake, which helps them in reporting in Tableau.

The features of Collibra Lineage that I have found most valuable include its non-integrated, non-native nature, which is one of the unique features for customization. In my case, data engineers have created their approach with Snowflake. By using a customized approach, they develop simple solutions and integrate with Collibra. A custom lineage, technical lineage helps me to design or join all these multiple layers. For example, connecting three Oracle instances to AWS is not available out-of-the-box, so there is a function to customize.

The main benefits that Collibra Lineage provides include measurable advantages. Once I have Lineage implemented, I can implement any automation on top of that. When I classify the D's on the data product, I can transform that data word to all the related columns using automation and workflow. This functionality avoids needing to do everything manually, and business only has to handle it at one layer, which is the data product. The lineage connects backward, allowing me to push back all these D's across all connected columns and registers. It's useful for the technical team to understand how all the data businesses seem different.

My use case for Collibra Lineage is for data governance; the purpose is to manage and govern our data effectively.

The best features of Collibra Lineage include its ability to map data flows and provide clear visualizations. I appreciate the interface, the reporting capabilities, and the overall user experience about this product. I use the automatic data flow mapping and visualization feature, and it helps my organization by providing clarity in understanding data lineage.

I have been using this solution for three years, and the improvements I have seen include better data quality and compliance, which benefits my business mainly by reducing risks.

We created custom data models in Collibra Lineage for domains and communities. Under each domain, we created databases and linked data dictionaries. We set up workflows by linking controls, which were attested by control owners quarterly. All of this was automated.

The solution allowed us to quickly and efficiently implement our data governance operating model, including accountabilities, regulatory lineage, and data dictionaries. This was much faster and more efficient than manual methods or other tools like Informatica. I prefer Collibra Lineage for its self-service capabilities.

I created a use case and gave users access to data stores, allowing them to implement their data sets easily. In contrast, Informatica requires a dedicated team of IT experts to handle these tasks.

The solution's APIs can be seamlessly connected to anything. 

I use the solution to link the technical and business terms and see the lineage between different technical terms. To track data flow, we start on the report level if there is a compliance requirement. We can see which data set a particular resource is using. We can see how the data table for the data set is created. We go back and trace the source. We try to define it from the source to the target end to end.

The product increases trust in the data. We know what is affected and where we need to update things if we change something.

We used Collibra Lineage mainly for end-to-end lineage. Additionally, we wanted to use it for business velocity data cataloging and data quality.

The most valuable features of Collibra Lineage are the multiple options for automation. Additionally, if you have a scenario where automation does not work, you have the option to manually create the lineage. The solution does not force you to always go through an automated way where you have broken lineage and you are stuck without a lineage.

We use it for compliance and data quality.

It shows how the data was transformed on the way and how the solutions were derived. This is the essence of the tool and why it is so powerful.

Any stakeholder in the company can see a very detailed visualization of the path of the data from the row to the report or the dataset to which machine learning was applied, for example.

We have a full-time user interface in-house.

The solution makes data more discoverable and transparent.