Governance workflows have clarified data ownership and improve lineage-driven decision making
What is our primary use case?
I have used Collibra Platform for metadata management, which is a data intelligence platform. I have also used Collibra DQ platform for checking data quality purposes as part of data governance.
I built metadata management by identifying data owners and data stewardship, including producers and consumers, and created workflows for approvals. I also established data lineage to understand the source, target, and how producers and consumers are linked.
Using Collibra Platform for data lineage and workflow approvals has impacted my daily work by allowing me to understand where data comes from and what systems are involved, how data is persisted until it reaches the target, and who is the right person to make any changes using workflow approvals to identify producers and consumers and their linkage.
Additional use cases with Collibra Platform would include monitoring data quality rules and scorecards, and assigning remediation tasks whenever there is a failure or the score decreases.
What is most valuable?
The best features of Collibra Platform, in my opinion, are that it is very user-friendly and integrated with basic SQL. Collibra Platform also has Collibra AI within the platform to help resolve issues very easily.
Collibra AI has helped me by identifying approved datasets and models. It also helps track data models with Collibra Platform.
Collibra Platform has positively impacted my organization through additional features including Critical Data Elements governance, automatic workflow management, and stewardship. Collibra Platform also helps with business glossary and audit management.
After using Collibra Platform, my organization was able to identify which datasets are approved. Business definitions became very clear, and it also helped establish clear data ownership.
What needs improvement?
Collibra Platform can be improved in simpler relationship management because some people feel Collibra Platform is complex for non-business users.
The platform could also improve easy navigation with Collibra Platform. Asset management and workflows in Collibra Platform could also be simplified.
I chose a rating of eight out of ten for Collibra Platform because there are some areas for improvement such as performance and user-friendly navigation.
For how long have I used the solution?
I have used Collibra Platform for around two years.
What do I think about the stability of the solution?
Collibra Platform is very stable and has delivered better results.
What do I think about the scalability of the solution?
Due to better data lineage, troubleshooting time has reduced, so Collibra Platform is definitely scalable. When used with the cloud like AWS, it provides more features and benefits for analytics.
How are customer service and support?
Customer support for Collibra Platform is very strong. Whenever there was an issue with the application, it was very easy to log a ticket and the issue was resolved on time.
Which solution did I use previously and why did I switch?
I have not used a different solution before Collibra Platform. The only different solution was an in-house platform of the organization. The reason for migrating to Collibra Platform was for the main features I explained.
How was the initial setup?
My experience with pricing, setup cost, and licensing for Collibra Platform is that since it is on-premises, pricing, setup, and everything is straightforward. I think that once it is moved to AWS, licensing and cost will be better.
What was our ROI?
I have seen a return on investment from using Collibra Platform on the data governance and metadata perspective as it has saved considerable time, especially when creating reports and it is easy to manage by just the known data stewards. It has saved money, time, and resources.
Which other solutions did I evaluate?
I am not sure about other solutions. Collibra Platform was chosen as the only option.
What other advice do I have?
The advice I would give to others looking into using Collibra Platform is that they first have to understand data governance concepts very well, including metadata management and how data intelligence and data cataloging work. Then exploring the platform will be really helpful.
Collibra Platform is a wonderful platform that has helped with metadata ingestion in real projects. It also helps with integration with fantastic tools like Snowflake and Tableau. Collibra Platform has many business glossaries, workflow management, asset management, relationships, and improved data lineage have also helped reduce troubleshooting. There have been many improvements after we started using Collibra Platform when compared to the in-house tool. I would rate this platform an eight out of ten.
Which deployment model are you using for this solution?
On-premises
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Unified data governance has reduced manual effort and accelerates trusted AI model oversight
What is our primary use case?
In my current field, I have been there for nearly five or six years, mostly related to data governance, data quality, master data management, and all the associated things.
I have been using Collibra Platform since the last six years and have been an avid user of Collibra Platform for different projects and use cases to implement for different organizations.
There have been many use cases for Collibra Platform, and during the initial days, four or five years back, the primary use case used to be business glossary and data catalog and physical data dictionary. Right now the focus is shifting more into AI governance and governance, such as doing data governance through agents, then connecting Collibra Platform to different various platforms to make a unified data governance or AI governance solutions.
For AI governance, Collibra Platform is being used to do governance for all the data models, including their explainability, the transparency, the biasness, and all these checks and how we are avoiding that. Governing the entire AI model and the AI frameworks is what Collibra Platform is currently doing in AI governance and what I am currently associated with working in Collibra Platform with AI governance. There has been another major shift with agentic, so you have to also govern your agents. Additionally, you can deploy agents into Collibra Platform to reduce your work time, so this has been the major shift. Apart from this, on the main use cases, there has been more usage of technical metadata, and linkage of technical metadata to business metadata has been a dire need of the present.
What is most valuable?
The best features right now that Collibra Platform offers is obviously the business glossary, which is very extensive, and there are different types of assets that can be created with different types of relations that can be added. It is a very good metadata management tool along with clubbed in concepts of data modeling. I would say business glossary, physical data dictionary, and metadata extraction from various sources are the best three features in Collibra Platform, and then also creating lineage out of it. It is a very business user-friendly tool as well.
Definitely, the user-friendliness is one of the key standpoints which makes Collibra Platform different from other metadata management tools which are more focused on technical metadata management. But along with that, Collibra Platform's catalog or the glossary is very extensive, which again makes Collibra Platform stand out from different other tools in the market.
There have been several impacts from Collibra Platform. Through the business glossary, the data discovery time, such as the data search time gets reduced by almost 50%. Then there are efforts of business stakeholders or domain leads which get reduced, so that is a kind of dollar saved. One data steward or one business steward can use Collibra Platform and reduce the manual data management work by 50%. So you can save every 50% of work saved per domain translating into 50% of dollars earned. Search time gets reduced significantly, I would say 50 to 75%. The stewardship activities or the domain ownership activities get reduced significantly, multiplying into saving dollars. The best thing is the volume it is able to handle, so manual effort gets reduced by almost 90 to 95%.
I tracked the reduction in manual effort or search time for different projects. It is not just one specific project; I have worked in multiple projects where I have seen this. The manual search time reduces a lot because ownerships are very clearly defined, so you know whom to reach out to, where to reach out to, and which team to reach out to. All the data in your landscape has a context added to it and has a business description added to it. You get to see which database schema table or column it belongs to, so you get to know an entire idea of the data which you are using. If you have a lineage already developed, then you can backtrack to see the source layer's data as well, which actually reduces a lot of time for you.
What needs improvement?
Improvement with respect to adding more connectors is one thing I feel which needs to be looked at. Right now, Collibra Platform provides many connectors and native connections, out-of-the-box connectors, but the technology landscape is overgrowing, and several new enterprise tools are coming in the market. The number of connectors can be increased. Secondly, to use Collibra Platform APIs, you need to always have a JSON Web Token or admin access, so that process can be improvised. Third, Collibra Platform can try and test how to make the work faster with more and more agents. Capturing the lineage becomes a little cumbersome in Collibra Platform when the technology landscape is a combination of multiple tools, so that is one thing which can be simplified.
I have already added the integration with other tools, so that is one area which needs to be improvised and there is scope for improvement. Another thing is bringing in more agents to agentify things and making work faster.
For how long have I used the solution?
I have been using Collibra Platform since the last six years and have been an avid user of Collibra Platform for different projects and use cases to implement for different organizations.
What do I think about the stability of the solution?
Collibra Platform is very stable. It does not lag, and it can handle large volumes of data in less time.
What do I think about the scalability of the solution?
Collibra Platform is heavily scalable with a completely robust architecture. The connection of data sources becomes easy with out-of-the-box connectors, although if not, then it is a challenge. Still, there are various out-of-the-box connectors available, so it is highly scalable and can handle large volumes of data within a shorter period of time, making its scalability really good.
How are customer service and support?
Customer support is very appreciable; anything you reach out to them for, they definitely try to help you out and they are in continuous touch with you. I have also experienced developing several features together, so it is really good.
Which solution did I use previously and why did I switch?
I have used many solutions throughout, including Informatica, Alation, BigID, and several others, some homegrown solutions. There is no particular reason to switch; it depends on the project-to-project needs, nothing else.
What was our ROI?
There has been a return on investment with Collibra Platform as a tool because you save a lot of money and a lot of headcounts that you would have had to spend on data management professionals if Collibra Platform was not there. More than money saving, the time saving is significant, as whoever is there, Collibra Platform eases their usage of data. A lot of time gets saved in data search, data discovery, and data analysis, which translates into a good return on investment.
Which other solutions did I evaluate?
I evaluated other options before choosing Collibra Platform as I do this for any project. Generally, I evaluated it with market-leading tools such as Alation, Informatica, Atlan, and a few others, sometimes Ataccama, sometimes BigID, depending on the need.
What other advice do I have?
Collibra Platform is a very good business metadata management tool, and if you want a unified portal wherein you can place everything at one place and look at every data in a one-stop shop, just as Amazon for products, Collibra Platform can be your Amazon if you use it correctly for all your data. I would rate this product 9 out of 10.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Data governance has transformed reporting and now delivers faster lineage-driven root cause analysis
What is our primary use case?
My main use case for Collibra Platform is reporting governance and building the data lineage by connecting to Unity Catalog and documenting KPIs, dimensions, and business reports. Once those reports are implemented by a developer using this data lineage, we could do end-to-end traceability if some KPIs are shown wrong in the report, then we leverage this data lineage to check the actual data source, the underlying field, table, etc., to do the root cause analysis.
For example, we have multiple data sources for building the reports using Collibra Platform, and we plugged in Tableau metadata and SAP Analytical Cloud, which are two of the main data sources for visualization, with our back end being SAP BW and sometimes SAP HANA. When a director from the business sends or documents the report in Collibra Platform, highlighting the requirements and KPIs, this is the first phase of the lifecycle of the report as a candidate or draft. Once it goes to the formal review process with business stakeholders and the data governance council, it is approved and goes for actual implementation to the developers, who implement these reports in BW and visualize them in Tableau or SAP Analytical Cloud platform. If one of the KPIs in a report is shown wrong, then using the data lineage in Collibra Platform, we could see which particular KPI is sourced from which SAP BW or SAP HANA table. Then the developer quickly finds out the root cause, fixes it, and showcases it to the end user using this data lineage capability in Collibra Platform. This is one of the practical use cases we implemented via Collibra Platform.
We have some other use cases, such as building the data quality report on certain data assets where we leverage Collibra Platform. For example, we work with the business to document their data assets in the form of data attributes, which are consumed by other businesses, and they set up business rules against those data attributes. Our data quality team creates data quality checks that are documented in Collibra Platform, and using the data lineage, we could see the quality of a specific attribute. We have traffic light indicators, such as green for good and red for an obvious problem, and in cases with certain errors, it is easy for the end user to consume this data attribute for reporting or quality purposes by seeing the data quality scorecard, which helps in deciding whether it is worth using or not. If not, they could trigger a workflow to the end data owner to fix those data quality issues, allowing them to leverage those data assets in their reports or use cases.
What is most valuable?
The best features of Collibra Platform include workflows primarily for governance perspective, where you can define your asset lifecycle, and use these workflows to govern those and collaborate with other stakeholders. We gather feedback collectively and notify when certain attributes or assets are changed. Another important feature is the data lineage I have described earlier, which helps in impact assessment before making any changes, showing where a particular field is being used in a report, data quality report, or normal report. It also assists in root cause analysis if something breaks down in your data pipeline. Recently, Collibra Platform also implemented certain AI features, such as generating descriptions for technical metadata that often lacks descriptions in data sources, which helps to define out-of-the-box or standard definitions of data assets such as tables and columns. These are the main features, and Collibra Platform also offers AI governance, which we do not use currently but is a powerful feature in Collibra Platform.
Collibra Platform helps to understand underlying policies and compliance classifications, including PII or non-PII classifications, crucial for accessing confidential data. This significantly eases the data finding and shopping process, allowing for quick access to necessary data.
The governance implemented provides clear ownership, so you already know who the actual owner is without chasing around. You find the real owner in Collibra Platform, which is always up to date, helping to identify the concerned party, and using a workflow, you define the lifecycle of collaboration, such as who should participate, who should be the reviewer and approver, and who should take action on the data, involving data stewards, business data stewards, technical data stewards, and the actual data owners. This makes life easier, improving data findability or searchability by approximately thirty to forty percent through these workflows.
What needs improvement?
Collibra Platform's platform needs improvement in certain areas such as workflows designed for administration that send excessive notifications, and sometimes it is unclear how many times a workflow instance was triggered. There are intelligence gaps that need addressing, along with user experience, especially with searchability when similar data assets have redundancy in SAP systems. Although certain improvements were made, such as defining weightages for certain assets to prioritize search results, more fine-tuning is still beneficial.
For migrating assets from one environment to another, we use import-export functionality, which can be cumbersome and manual. Leveraging AI could simplify the process by automatically listing assets for movement, requiring only a couple of clicks, providing a win for administration purposes.
For how long have I used the solution?
I have been using Collibra Platform for the last ten years.
What do I think about the stability of the solution?
Collibra Platform is stable.
What do I think about the scalability of the solution?
We scaled from a few hundred to over a thousand users, highlighting effective scalability for us.
How are customer service and support?
Customer support was great.
Which solution did I use previously and why did I switch?
We did not previously use a different solution.
How was the initial setup?
Getting started with Collibra Platform was quite tough initially, as it involved change management to lift and shift to new technology. We set up as per governance policy, starting small, onboarding business data users for reporting governance, documenting reports, KPIs, and dimensions, leveraging workflows to collaborate efficiently. We identified data owners from each business domain and began with critical data elements, around one hundred to three hundred elements and their associated KPIs. Regular biweekly touchpoints helped to understand their journey, the value gained, and areas for improvement. Over roughly two years, we saw significant adoption growth from a few hundred to over a thousand users, and this journey continues.
What was our ROI?
We have seen a return on investment, as previously it took weeks or even months to find the actual data owner, while now it takes just seconds or a few minutes, indicating a significant increase. The reduction in time needed to find and search for data is acknowledged by our senior management as they actively use Collibra Platform.
Which other solutions did I evaluate?
Before choosing Collibra Platform, we evaluated other options, including Informatica.
What other advice do I have?
My advice for others considering Collibra Platform is to start with a small vanilla platform and your use case rather than attempting a big bang theory. Starting small can provide a significant impact, such as reporting, which also draws senior management attention. I would rate this product an eight overall.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Excellent Software Services with No Drawbacks
What do you like best about the product?
Good software services deliver reliable, efficient, and user-friendly solutions tailored to client needs. They ensure seamless integration, robust security, timely support, and continuous innovation, enhancing productivity and customer satisfaction across industries and platforms.
What do you dislike about the product?
Nothing at the moment implies no current tasks, updates, or concerns requiring attention, indicating a temporary pause or state of readiness.
What problems is the product solving and how is that benefiting you?
Collibra solves key data governance challenges by providing a centralized platform for managing data quality, lineage, and compliance. It helps ensure trusted data across systems, enabling better decision-making, reducing risk, and improving operational efficiency.
