Collibra Platform Reviews

My main use case for Collibra Platform is for a banking client in the Netherlands, who wanted to create a centralized system to organize data assets, define ownership, ensure data quality, and enforce governance policies.

This was for a banking client in the Netherlands, and Collibra Platform is used to govern the customer balance. Without Collibra Platform, we faced issues because retail and risk and finance teams all calculated the balance differently, resulting in inconsistent reports. With Collibra Platform, we defined the correct customer balance in a business glossary and assigned a data owner such as the head of retail or head of finance. It helped us show the lineage from core banking to data warehouse reports and apply access rules, authorizing teams to see sensitive data related to the customer. Basically, it was for reporting, risk analysis, and regulatory compliance.

I think Collibra Platform is a really great tool that is user-friendly, and the person using it does not need much technical background. The user should be smart enough to know data governance rules, but a technical background is not mandatory. For banks, which are heavily regulated with regulations such as Basel IV and GDPR, Collibra Platform proves to be useful for regulators in controlling data. It provides end-to-end traceability and allows us to define exact definitions of certain rules across departments, which brings out the actual value in banking.

The best features Collibra Platform offers include traceability, audit readiness, and making data defensible. It is great for regulatory compliance, clearly showing data lineage, applying access rules, defining a business glossary, and having a data catalog. It also includes workflow automation, which differentiates it from other data lineage tools, and provides data quality monitoring. For me, the top features would be data cataloging and glossary, lineage and workflows, and compliance.

With Collibra Platform, workflow automation allows us to request analysts to access customer transaction data. It can auto-trigger workflows, starting a predefined approval process with step-by-step approvals from the data owner to compliance and IT security. It includes automated checks verifying if data is sensitive or if the user has the required role or training. Access is granted or rejected, and everything is logged, making workflow automation a way to turn governance policy into executable processes.

After implementing Collibra Platform, we maintained a consistent definition for customer balance across all banking departments such as finance, retail, and risk. Earlier, teams had different calculations that led to inconsistent reports. Collibra Platform helps us achieve faster decision-making, improve data trust and accuracy, and reduce conflicting reports. It also provides full transparency of data lineage, where everyone can see the entire lifecycle of the data. After introducing Collibra Platform, our operational efficiency increased, reducing manual processes and cutting data access approval times significantly.

I think Collibra Platform could be improved with a simpler UI for business users, faster search capabilities, and better performance for large metadata volumes. The setup can be complex and time-consuming, so more plug-and-play connectors would be helpful for faster onboarding with cloud systems such as Snowflake or Databricks.

I believe integration with tools such as Power BI, Tableau, or notebooks would be great for handling large data processing.

I have been using Collibra Platform for more than three years.

Collibra Platform is stable.

Collibra Platform is scalable but requires a lot of technical expertise.

Customer support for Collibra Platform has been great whenever we needed assistance.

I would rate customer support a solid eight out of ten based on feedback I hear from my team.

We did not use any other solution before Collibra Platform.

For metrics reflecting improvements, we experienced a twenty-five percent reduction in data preparation time for the analytics team and about a thirty percent reduction in planning time. Tasks related to data governance went from weeks to days or even minutes. This operational efficiency has reduced labor costs and increased productivity, directly impacting our ROI.

I have seen a return on investment with significant reductions in compliance risk and costs associated with duplicate data.

My experience with pricing, setup cost, and licensing has been good, especially when using it alongside Azure.

Before choosing Collibra Platform, we evaluated different options such as Azure Purview.

I chose seven out of ten because Collibra Platform addresses all our use cases, simplifies our processes, and provides good ROI, but it needs improvement in integration and some other areas.

My advice for others looking into using Collibra Platform is to go ahead with the tool, as it greatly simplifies processes and saves costs and time. I would rate this review a seven out of ten overall.

Implementing Collibra Governance is definitely something that all organizations having data need. It's the kind of tool especially for large enterprises where data is distributed across multiple data stacks, bringing rigor for both data management and data engineering.

We use Collibra Governance for metadata management and access restrictions, as well as lineage.

We use Collibra's Data Stewardship features. In terms of role assignment and accountability, there are three levels of users: people who are data users, then there are data stewards, who are users of data enforcing compliance and rigor around data, and finally, the data governor who sets up policies and principles.

We have utilized Collibra's Business Glossary. It is good for reference of the data, understanding what the data is about, which helps maintain data accuracy.

Collibra's integration capabilities benefit our organization, although compared to the rest of the market, it is a bit cumbersome, but it's acceptable.

My experience with Collibra's collaboration tools in improving data literacy has been quite good. I think it is one of the best for helping people understand and discuss certain data sets and manage workflows.

In future updates, I would like to see more AI-based capability in Collibra Governance, wherein the data definitions can be auto-generated and lineage can be tracked down easier.

I've been working with it for probably 12 years.

The installation process is quite straightforward, but for it to be adapted by the organization presents challenges based on the organization, so it's not a technical challenge.

For a basic installation, I spend just a few weeks, probably about two weeks on setup and configuration.

Three to four people from my side usually take part in the implementation.

There are some benefits in the long run in terms of return on investment. While there are no direct cost reductions, there is significant indirect cost reduction. If I consider putting data governance in place without a tool like this, it's difficult, resulting in a significant cost improvement. If something else can be used instead and it's more expensive, that is a consideration.

Regarding licensing, I find it is one of the more expensive options, so it is not particularly affordable.

The interface is very good, with no complaints.

I do work with other vendors as well. Some other vendors I work with include Informatica, Atlan, and Suchi.

On a scale of 1-10, I rate Collibra Governance a 9.

My main use case for Collibra Platform is data cataloging as well as AI governance.

In my day-to-day work, I connect with data sources such as Snowflake and a variety of data sources like Hive, and then use the metadata to define the data dictionary, while also using Collibra Platform to define the business glossary and tie it up with the metadata so that any user logged in can understand what the data describes. For AI governance, I have a lifecycle where the user submits a workflow to get approved for their AI use case, and then I use that workflow to analyze the use case and the associated data, completing a data quality check using Great Expectations before approving the use case if there is no risk associated with the data. I use Collibra Platform for both AI governance and data catalog.

Unique to my organization is the data cataloging part and Edge; I use Edge of Collibra Platform to connect to different inbuilt data sources.

The best features Collibra Platform offers include data cataloging and a variety of APIs, allowing me to use Python and REST API to export or import data within Collibra Platform, and there is a lot of documentation available, along with fantastic support from Collibra Platform which helps whenever I encounter issues.

The documentation is clear and helpful, and it is easy to integrate with other tools using Collibra Platform's APIs. For example, I did an integration with Databricks to Collibra Platform to get all the assets from Collibra Platform, and it was very easy.

It is easy to define the business glossary in bulk with Collibra Platform, as I use Excel export to bulk create business glossaries, making it easy to tag, and the workflow capabilities are excellent, getting assigned to users when the workflow starts and making it easy to manage and track workflows from end to end.

Collibra Platform has positively impacted my organization by removing silos in AI governance, as prior to introducing Collibra Platform's workflow, processes were messy and done in silos; after introducing Collibra Platform, the process is thorough and significantly reduces my organization's risk.

Collibra Platform could be improved regarding data quality, as the rules cannot be defined as easily as in other tools.

The user interface is very good and convenient, with no additional improvements needed.

I have been using Collibra Platform for three years.

Collibra Platform is stable in my experience.

The scalability of Collibra Platform is good.

Customer support is excellent from Collibra Platform.

Onboarding new users to Collibra Platform is easy; even non-technical users can navigate it effectively, as the documentation is sufficient, and users can also attend training sessions through the university for additional support.

Data lineage is easy to track and understand with Collibra Platform because it establishes complex relationships between each hop using an automated tool called Lineage Harvester, which connects with the database and establishes lineage between hops.

Collibra Platform uses SSO for login and manages access control, providing full access to admins while restricting access for data stewards, data quality analysts, data analysts, and technical stewards, ensuring that everyone has only the required access and there are granular permissions available.

Collibra Platform manages metadata effectively, making it easy to update, search, and maintain metadata across my data sources.

Collibra Platform supports collaboration between different teams or departments through workflows that assign tasks to specific teams or individuals, with automatic reminders sent from Collibra Platform until tasks are completed.

My advice for others looking into using Collibra Platform is that it is excellent for those needing AI governance, data cataloging, and automated data lineage—definitely consider it. I rate this product a ten out of ten.

I used Collibra Catalog primarily for cataloging all the assets. We created data dictionaries by ingesting data from multiple databases into Collibra Catalog and setting up workflows for review and approval processes.

The most valuable features of Collibra Catalog are its customizability and ease of use. We created data dictionaries both by ingesting our database structures and for non-database sources. We also set up different communities, defining ownership and stewardship with customizable workflows.

There is an issue with Collibra Catalog's pricing model, especially for organizations with many databases, as the initial package comes with a limited number of connectors. This can lead to manual efforts to connect more databases, increasing costs. It would be beneficial if they offered more connectors as part of the initial package.

We used Collibra Catalog as long as we had Collibra, starting from when we began cataloging all our assets.

I did not have any issues with the stability of Collibra Catalog.

Collibra Catalog is quite scalable. We were a big bank and had thousands of assets without any issues.

When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved. Without the program, the support was decent, with response times of 24-48 hours. Sometimes the support was useful, and sometimes it was not.

Neutral

My company initially used Collibra, but after being acquired by BMO, which had a contract with Informatica, we had to switch. BMO had recently renewed their contract with Informatica, which led to letting go of Collibra.

The initial setup was straightforward with the involvement of our IT team. It is important to have a Collibra Resident Architect for a successful implementation, which we found more effective than hiring external contractors.

We used the Collibra Resident Architect program instead of hiring contractors. This was a cost-effective approach, and it was extremely beneficial to have a knowledgeable Collibra employee assist with setup and configuration.

The pricing for Collibra was good since we did not have many add-ons. However, adding modules like Privacy could become expensive. The value is still greater when considering the cost of customizing other tools.

I have experience comparing Microsoft Purview and Data Hub alongside Collibra. Collibra is favored for governance, while Purview, integrated with Azure, is a better fit for engineers than business users.

I would definitely recommend Collibra Catalog to others. Of all the catalogs I've used, Collibra stands out as being more of a full tool for governance. As long as Collibra can connect to your databases, it cannot be easily beaten. I rate the overall solution an 8 out of 10.

I work as a data consultant for IBM Bluetab company, and my role involves data analysis, data engineering, and conveying messages in terms of research and reports.

I have been using Collibra Platform for over two years, and I find the platform to be very unique in terms of data governance, as it is very aligned to most of my needs.

I use Collibra Platform primarily for searching domains and all information from my data catalog. Currently, we are in the process of migrating databases from Oracle to Azure. I type mostly definitions, check who has ownership of a field or domain, and search for categories when I need to find similarities between one data warehouse and another type of database. I use the artificial intelligence tool set to receive hints on words and make traceability of where certain data could be located. I use most of those cases.

A specific example of how I used Collibra Platform recently involves traceability needs. The platform allows me to input information regarding where a certain field within a table begins, and then I need to understand what the equivalent is in another database. I typically search for the name I already have in mind, from which I can see details about ownership, the tables it is linking in that position, and check definitions. I get everything summarized in tables and can also see more details about the parent table and relative tables, so I could benefit from the diagrams they offer.

I have additional insights about how I use Collibra Platform in my work. For example, when I know the term but specifically need to get more insights about what could be the next definition deriving from this term, it would be great if I could get suggestions from the formation of two terms so I would not need to search in other places.

The best features Collibra Platform offers, in my opinion, include the ability to search deeply. If I have a term and I select it, I can see all the data governance utilities in terms of ownership, definition, and whether this data is considered to be private or public within my organization, as well as all the key information. For reports, if I have the domain for certain data and think it may be incomplete, I can upload a spreadsheet and update it within the platform. This information is very useful to my work.

Out of those features, I find myself using the feature of converting my domains into smaller views and getting more insights about the origin of a certain field within a table the most. It is having a broad view but also having a connection with a specific view at the same time, which helps me have a smoother traceability process.

Collibra Platform has impacted my organization positively. The main benefit is that we now have our best catalog organizer. Since we moved from one type of database that was mostly relational, we are now able to see other types of structures, and we can actually use spreadsheets, tables, and other types of information that could be generated from them.

The AI hints could be something that would be very useful. If I have to think about something else, I see potential in working with other external platforms like Databricks. Inside of any platform, I could actually get to the definition, for example, inside of Databricks, or if I am inside of Collibra Platform, I could get snippets of the code, something related to this interdisciplinary work. I could also get a plugin version with other types of platforms.

Collibra Platform could be improved, particularly the AI platform, which at the end of the day needs to be very tailored and very specific to my cases.

User integrations could be very useful to see how the work could also be linked to other platforms, so I would really like to see that.

I would rate Collibra Platform a nine out of ten so far, as it has been really useful for my case.

I chose a nine out of ten because it is not fully integrated with other platforms at the moment. I think that is what needs to be improved.

My advice to others looking into using Collibra Platform is that they can start ahead with the platform. It is very intuitive and has everything that you need regarding data governance, especially if you want to aim for traceability purposes. I give Collibra Platform an overall rating of nine out of ten.

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 configuration issues I face include troubleshooting that is not very helpful. I keep struggling with that and usually have to go to the Citizen data platform and the marketplace to get the answers I am looking for.

The controlled logs and documentation need improvement, particularly regarding how to access class features that they do not control, and documentation in terms of customization and UI customization. Dashboarding needs significant improvement as the widgets are not very clear or usable, and there is not much documentation around it.

To make Collibra Lineage better, additional features should be added to help technical users. They have improved significantly in terms of university courses in the last five years, but aspects such as AI governance and data notebook are not being promoted adequately. Data notebook is a very good feature, but there is a mismatch in the courses' speed and how quickly they are giving people the ability to learn about it.

I have been working with Collibra Lineage for more than five years now.

The implementation becomes more complicated, especially in terms of integration if there is no Collibra Lineage native connector. If you have to build gateways using the APIs or communicate with the APIs, it becomes significantly more complicated.

I would rate their technical support a seven or eight, as it depends on the payment tier. If you have paid for support, they respond to every email, and you have a personal account manager who takes care of all issues. If you just purchased a license without a support system, it is hard to get a decent reply on tickets, but this is true for most other catalog tools as well.

Positive

I usually recommend products such as Purview instead of Collibra Lineage, which is a significant downgrade from Collibra Lineage in terms of experience and key features. I have seen people moving to in-house catalog tools as well.

The product is definitely expensive. I have seen many customers moving away from Collibra Lineage after using it for a couple of years because the cost-benefit analysis does not give them a favorable report. They are paying too much for features they are not able to utilize.

The pricing presents both advantages and challenges. Many clients do not anticipate the effort required to develop a catalog and fully utilize it for data consumption. When considering the time and effort required to build a catalog and utilize it effectively, combined with the prices, it often does not make financial sense.

I usually recommend products such as Purview instead of Collibra Lineage, which is a significant downgrade from Collibra Lineage in terms of experience and key features. I have seen people moving to in-house catalog tools as well.

I would still recommend Collibra Lineage to others, as I am a champion. I am a two-time Ranger certified person, and I speak about Collibra Lineage in a positive light when I get the chance. I rate this solution 8 out of 10.

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.

When discussing potential areas of improvement for Collibra Lineage, there are several cases to consider. If we discuss Lineage, which is the major part I work with, solutions are implemented in PySpark, and Collibra does not have out-of-the-box features for that. If a developer implements ETL in Glue or PySpark, Collibra cannot capture lineage out of that. This is an area for improvement, alongside integration with Starburst, which is another area where lineage capability is lacking.

I have been working with Collibra Lineage for five years.

I rate the stability of Collibra Lineage as seven. This is a fair assessment compared to alternative tools such as IBM Cloud Pak for Data, which I've also worked with.

In terms of scalability, Collibra Lineage's performance is reliable, as the lineage harvest runs on the lineage server which operates on Collibra cloud. I have not faced any issues concerning scalability. Despite earlier concerns when it took eight hours for one data job, recent improvements have reduced this time to three to four hours, though it still depends on metadata volume.

For technical support, I would rate it as eight because with premium support, the service is excellent.

The initial setup of Collibra Lineage is very simple nowadays. You can drag lineage from the UI by selecting and dropping whatever configuration you want. For configuring Lineage capability for Snowflake, there are multiple options available. It's particularly efficient since last year when they moved lineage to UI.

I have not used data flow mapping with Collibra Lineage. I question the helpfulness of visualization features for Collibra, particularly lineage visualization.

I agree with the assessment that lineage visualization in Collibra is valuable.

Overall rating: 7 out of 10.

We are a customer of Collibra. Collibra Governance is applied in our data management workflows by creating all the business functions separately, maintaining the data sources of those KPIs and everything separately on those businesses.

Collibra Governance provides ease of use. The portal is self-explanatory with lots of documentation on its usage, making implementation and understanding simple for our team.

The most important feature is the ease of use. The portal is very self-explanatory and robust. The tool also provides integration with a lot of sources.

There should be more detailed documentation on the selectors and certain information, and a reduction in cost as compared to other tools. The data marketplace solution could be more flexible in filtering capabilities. Additionally, their responsive time in technical support can be quicker.

I have been working with Collibra Governance for almost two years.

The solution is stable, and I would rate it as a seven out fo ten.

On a scale of one to ten, the scalability of the solution is around seven or eight out of ten.

Technical support is effective in providing solutions. That said, their response time can be improved. I would rate it around five or six out of ten.

Neutral

We have not used another solution till now but are considering others, especially due to cost.

It is mostly straightforward, especially if you have the infrastructure ready.

I wish the tool could be less expensive compared to other tools.

We are looking into Purview due to costs and features differences.

The tool is intuitive, easy to learn, and would be better if the costs were reduced.

I'd rate the solution seven out of ten.

Collibra Platform is used for data governance, bridging business and technical data. I used Collibra Platform to import metadata from GCP projects by utilizing Collibra import APIs.

Importing metadata from GCP projects helps to make data accessible for everyone at the company so that they can use this data because they have information about metadata.

Collibra Platform offers features such as Collibra lineage, Collibra sampling, and bridging business objects and technical data, which really stand out to me.

Collibra lineage helps us to understand where the data comes from and is used to understand the lineage of the data. Sampling also helps to get an idea of the data.

Collibra Platform has positively impacted my organization by increasing data usage and helping teams build data products. Faster access and easy accessibility contributed to how data usage increased.

The UI of Collibra Platform can be improved, as can some APIs such as the import API.

Improving the UI and documentation would bring it closer to a perfect score for me, making it more accessible.

I have been using Collibra Platform for two years.

Collibra Platform is adequate in terms of stability.

Collibra Platform's scalability is adequate.

Customer support for Collibra Platform is adequate overall.

We did not previously use a different solution.

I do not have metrics regarding a return on investment.

I have no experience with pricing, setup cost, and licensing because I was not in charge of that.

I do not know if we evaluated other options before choosing Collibra Platform.

I would advise others looking into using Collibra Platform to get some training and develop a culture around data governance.

I have no idea about Collibra Platform's AI capabilities regarding governance and security because I have not used it yet. I have no experience with Collibra Platform's AI capabilities related to the accuracy and reliability of output.

I gave this review a rating of 7.

We have a data platform and we use Collibra Catalog as enterprise governance tools. We are using Collibra Catalog for basic functionality.

It has various features such as cataloging data products and data sets, and it also has a marketplace and edge connectors to scan metadata. All these are various features, and the data quality aspects are there as well.

Discoverability is one of the key things we are always looking into.

Lineage is also available, including both technical and metadata lineage.

One of the very key drawbacks is that automation for access provisioning is not available. If I discover a data set or data product in the marketplace and want to access the data, this feature doesn't exist at all.

This is the biggest problem because without access automation enabled, users cannot get access to the underlying data.

We have been using it for 4 and 1/2 years now.

Deployment issues exist; every time we do a deployment, it erases the data in its previous versions. We have highlighted this to Collibra Catalog and have raised a ticket. They are working on it.

We are not satisfied as it is not yet completed. We raised this issue a year ago, but there have not been any results yet.

Response time is the main issue.

The solution is scalable.

We have multiple cataloging systems similar to Collibra Catalog.

Pricing is not under my purview as I am an architect. The platform team handles the licensing aspects.

The comparison shows that each tool has its own pros and cons.

Gartner identifies Collibra Catalog as the leader, which aligns with our observations.

I have read reports about Collibra Governance and Microsoft Purview on the website. We are currently using Collibra Catalog. We also use Tableau. I work as a Collibra Catalog architect. The tech support rating is six out of ten. Overall, I rate this solution 8 out of 10.