Collibra Platform Reviews

The main use case has been drafting business glossaries, data dictionaries, assigning ownerships, and prioritizing data elements.

Once a data element is prioritized, we assign ownership on the basis of seniority or the basis of expertise in a particular field. Then we assign the ownership and wait for the owner to confirm or approve their ownership from their end.

I have also created some data quality rules on Collibra Platform to monitor the accuracy, timeliness, and completeness of the data. Apart from that, I have also tried to create some workflows and some policy measures, tried to create some data products, and data contracts as well.

Collibra Platform has been used by my organization for various clients for internal company data cataloging. When we have governed the data, when we have cataloged the data, and given it a business glossary name, after that, we have been able to build many use cases on AI, and that has been really helpful.

Right now, we are also working with an AI use case or making an AI chatbot to answer quickly and to have the metrics quickly. To build that, we need to catalog some amount of data related to around 45 to 46 reports. First of all, we don't have to do it manually. We can enter the data element in Collibra Platform, and then we can define the data type or the data definitions.

I think the best feature of Collibra Platform is its easy-to-use UI. It's an integrated platform where we can have an enterprise level of elements catalog assigned to different owners and track the lineage. We also have a business lineage and technical lineage for different types of users, which is really helpful in understanding different use cases in different scenarios. The UI is really easy to use.

Business lineage is important when we are showing this to someone who is at a very senior level and we want them to understand what kind of data we are using and what kind of insights we are deriving, but they are not very versed with the schema or the technical terms related to that dataset. They can understand and clearly see what the dataset is really about and how it is being connected from top to bottom. That's been really helpful. Technical lineage is mostly used by the engineering teams to track the source of the data and to understand if there are any breakages in the data pipelines. That's helpful. The easy to use UI means that if any business user is using it and is not very technical in nature, they are able to quickly pick up at least the glossary part of Collibra Platform and the navigation is also not much. Everything is just right there. It doesn't take much time to get well-versed with it. You just know what to do when you see it.

I have seen return on investment. Basically, earlier the team was cataloging using Excel and there was no automated process. The Excel had to be shared with everyone else and multiple users had to be deployed on that. Now with Collibra Platform, we can use it very quickly. We can share it with multiple users and the users are able to see everything in one space at one time without any glitches and without any changes. It has been really streamlined. The return on investment has been great. I think the employees have become more productive. They are able to take on a lot more work, which is really required. There's a lot of work. Collibra Platform has made the employees 20 to 30 percent more productive. Collibra Platform has increased the discoverability and productivity of employees by at least 30 percent, which is great.

I think it's a great platform. Searching can be made a little better. The data marketplace which it provides is also great, but sometimes when we are searching an element and we know we are not sure if we can find it or if we have missed it. Listing data domains in one place for quick visibility will be an add-on.

I am not a hardcore coder. For a coder to create workflows and automate the process, I needed to learn Groovy script and create some workflows. In the automation part, I think it can also introduce a low-code, no-code platform where we can connect different connectors and we can quickly create some automated workflows, if at basic level only, because the next big thing is automation and AI. Low-code, no-code platforms are being used by everyone. I think that will be useful.

When I look for a data domain, I'm not able to find it very quickly. For a business owner to know data domains and search data domains, it could be made a little easier. Also, the automation part needs improvement. We are only able to enter the data manually or connect to a data source, but now we want to create some workflows as well. That's why I've chosen a rating of eight. Otherwise, it's really great.

I have been using Collibra for about four and a half years.

Collibra Platform is pretty stable and very easy to open and easy to share a link with and provide access to the employees.

Collibra Platform has been scaled across the organization. Our organization has more than 10,000 employees without any glitch, without any hang, and without any slowness. It's scalable. We can provide access to different users very quickly. The users just need to go through training and they're ready to use it.

Customer support is great. We have been assisted by them in no time and there's been very little follow-up, and we are able to resolve any issue which we require. I think customer support is a nine. They're always available and very easy to talk to, very generous, and they're able to help at any time of the day.

I've used Enterprise Data Catalog from Informatica. I switched because a lot of business users were also coming in and using the catalog. Enterprise Data Catalog is more of a technical usage platform. A lot of business users were struggling to use it. That's why we have switched to Collibra Platform.

I haven't done the pricing and license cost, but setup is easy. I've done the setup, but I think a higher level of approval comes for pricing.

We have evaluated Atacama, Atlan, Informatica Enterprise Data Catalog, and Axon before choosing Collibra Platform. All the options, features, pros and cons of using different platforms were considered, but Collibra Platform stood out in terms of the features and in terms of ready availability, and we were in a hurry to deploy it. Collibra Platform really stepped up and we were able to get the licensing at our desired prices. That's why we have used Collibra Platform.

I would advise others that it's really easy to use. You can have a small training provided by Collibra Platform and you are good to go. Your basic use cases are covered. Your team can use it in a very efficient way and you can have visibility of all the datasets and all the data catalogs available in your database. Collibra Platform has been a great help for any development which we are looking to do and in tracing the lineage and detecting if any datasets is broken or giving any null values or anything. It has been very important to use it. I would advise to go ahead and use it. It will not take much time. If you don't even know how to use it, you will learn it really quickly. It's a good to go product. I give this product a rating of eight out of ten.

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.

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.

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.

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.

Collibra Platform is very stable. It does not lag, and it can handle large volumes of data in less time.

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.

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.

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.

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.

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.

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.

My main use case for Collibra Platform, previously from 2023, is supporting data governance and data cataloging. I use it to help structure and maintain business terms, data standards, business rules, data dictionary, and ownership or stewardship information. This mainly supports my work from a domain experience perspective. More recently, I use Collibra Platform from a managed services perspective, primarily for operational support, monitoring, connector health, release follow-up, monthly service reporting, and related activities.

From a managed services perspective, my focus with Collibra Platform is on keeping the platform stable and ensuring that the client has clear visibility into how the service is performing. This includes monitoring platform availability, checking connector health, following up on Collibra Platform releases and updates, supporting incidents or service requests, and preparing monthly service reporting. The reporting typically includes uptime, connector status, known issues, incidents, changes, upcoming releases, or relevant platform updates. My work is less about creating governance content day to day and more about operational support, service quality, and ensuring that Collibra Platform setup continues to run smoothly. I maintain the platform in the managed services phase, so recently I made a minor tweak in a workflow by changing some logic based on the client's request.

One aspect of my use cases with Collibra Platform is that I work with it as a bridge between business and IT. I focus not only on the technical setup but also on how the content, roles, responsibilities, and reporting support business users. I work with business terms, standards, rules, data ownership, workflows, and data quality visibility, as well as more operational topics such as environments, release monitoring, and service reporting. This combination helps me understand both how business users utilize Collibra Platform and how it needs to be supported from a service perspective.

Collibra Platform offers numerous features, and recently I have been looking into the AI agent feature. The strongest features for me are the Data Catalog, Business Glossary, workflows, and the operational model behind roles and responsibilities. The Data Catalog is valuable because it gives users a central place to find and understand data assets instead of relying on scattered documentation or asking different people where something is stored or used. I actively use the DataBricks Unity Catalog integration, which works very well for our organization. The Business Glossary is important because it helps align business and IT around the same definitions, which is especially useful when different teams use the same term in slightly different ways. Workflows stand out because they help standardize governance processes, such as approvals, issue handling, and creation of new terms and assets, making the process more controlled and less dependent on individuals. The operating model is a key strength because Collibra Platform allows you to connect data assets with owners, stewards, responsibilities, policies, different standards, and rules, which gives better visibility to who is accountable for what and how data should be governed, ultimately giving maturity to the company and easing the work.

Collibra Platform has had a positive impact on structure, transparency, and alignment around data in my organization. One clear improvement is that business definitions, standards, business rules, and ownership information can be kept in one central place. This makes it easier for business and IT teams to use the same language and understand who is responsible for which data. It also improves visibility since users can better understand what data exists, what it means, where it is used, and which governance rules apply. From a support perspective, it helps because I can monitor the platform, follow up on connectors and releases, and provide clear monthly reporting. Overall, the biggest benefit is that Collibra Platform helps move data governance from scattered documents and informal knowledge into a more structured and controlled platform.

I am exploring the AI agent and AI governance features in more depth, as I believe there is considerable room for improvement in those areas, and they will generally enhance all features.

A few areas where I think Collibra Platform can improve include user experience. Collibra Platform is very powerful, but for new or occasional users, it can feel complex. It takes time to understand the structure, roles, asset types, relationships, and where to find the right information. A simpler and more guided user experience would help adoption, possibly supported by AI agent introduction. Another area is reporting; Collibra Platform contains a lot of useful information, but creating clear operational or management-level reporting is not always straightforward. It would be helpful to have easier out-of-the-box dashboards for things such as adoption, data ownership, and workflow progress. For integrations, they bring a lot of value, but they require careful setup, monitoring, and troubleshooting. Overall, Collibra Platform is strong.

I have been using Collibra Platform for around two years. Most of my hands-on experience was between 2023 and 2025, and I have been using it again over the last two months.

The performance and reliability of Collibra Platform is excellent since we use the SaaS cloud offering. I communicate with Collibra Platform's support team, which provides the platform, and the experience is outstanding with approximately 100 percent availability. Any small drops are usually maintenance hours that occur outside of work hours. Collibra Platform is stable based on my experience.

The scalability of Collibra Platform, from my experience, is good, especially because it is a cloud-based SaaS platform that supports separate environments such as development and production. It can handle growth in users, assets, metadata, and integrations, but it requires good governance and administration. For example, as usage grows, you need to manage roles, permissions, ownerships, assets, workflows, and integrations carefully. If the operational model is not well maintained, the platform can become difficult to navigate, even if the technical platform can scale.

My experience with customer support for Collibra Platform is generally very positive. Collibra Platform's support team can help with platform-related questions, and I use their services frequently regarding uptime reports. They provide quick and high-quality responses.

I would rate customer support for Collibra Platform at ten out of ten based on my experience. I have not had any complex tasks; my interactions were mainly about reporting and uptime, so I did not have an opportunity to communicate with them on more complex issues. However, from what I hear from my colleagues, they also have a very positive experience.

I have not personally led a formal migration from another dedicated data governance platform to Collibra Platform. Before Collibra Platform, governance information was typically managed in a more manual or scattered way. Collibra Platform provides a more structured and centralized platform for the purposes it serves. I have not used any dedicated governance tool before; the experience was more about partial governance inside other tools. I used different MDM tools that have some data governance capabilities, but it is nothing close to Collibra Platform.

I do see a return on investment with Collibra Platform, but I would describe it more in terms of efficiency, transparency, and risk reduction rather than exact financial numbers. Collibra Platform saves time because users can find business definitions, ownership information, and related assets in one place instead of searching through different documents, emails, or asking multiple people. It reduces rework and misunderstandings between business and IT. From a managed service perspective, the return on investment is also in better operational control. I cannot provide an exact figure such as money saved or employees reduced, but the value is visible in better data understanding, faster communication, fewer misunderstandings, and stronger governance control.

My advice for others looking into using Collibra Platform would be to start with a clear governance model before configuring too much into Collibra Platform. Collibra Platform is a very flexible platform, which means you need to define your business model, how it should work, and carefully define your communities, domains, asset types, ownership model, roles, responsibilities, and workflows from the beginning. If the structure is not clear, the platform can become very difficult for users to understand. I also recommend starting with some practical use cases and not trying to implement everything at once, such as a business glossary, key data assets ownership, and a few important workflows, then expanding gradually. Training is also important because business users, data stewards, and administrators need different levels of training as they use the platform in different ways. I would rate this review at eight out of ten overall.

My main use case for Collibra Platform is that we use it on a day-to-day basis. We configure workflows for clients, and we have multiple clients for which we work. Our task is to manage the metadata of their company or design workflows. These two are the major components that we work with.

One specific example of how I use Collibra Platform for managing metadata or designing workflows is that some people have access to certain information only within the company. We help them configure workflows where only a few people have access to that particular data. Apart from that, whenever they have different definitions across different departments, we help them create a data dictionary and business dictionary within Collibra Platform so their data could be unified.

This is just one of the use cases, as it depends upon the client what they ask for. We have previously worked with data lineage as well, creating policies and AI governance. We have shown them how it could benefit their AI infrastructure. Those are the other core areas we have worked upon.

Collibra Platform offers best features including a velocity pack where some of the workflows are already provided when you enter into the platform. These are very specific to Collibra Platform, which no other vendors such as Alation or Purview provide. Collibra Platform provides a great user experience for the first time someone is entering Collibra Platform, as they have a few things that are already packaged for you, so you don't have to start from scratch.

Within Collibra Platform, if you go to the documentation section within the workflows, you can find several workflows which you can utilize. These are already present there, which helps you to start from ten to twenty percent rather than starting from zero. These are workflows that help get you ahead.

In terms of features, the UI experience is great, whether it is lineage, governance section, or navigating from one domain to another. It is very useful in terms of the features. The settings sections have multiple options where you can add user groups. Everything is very well configured, and you can change the number of attributes a definition has. It is very configurable in that sense. The UI is also very configurable in terms of what you intend to have, and you can get your logo up on the website.

Improvements in efficiency is one of the outcomes thanks to Collibra Platform because previously users used to search for data and had to wait for a certain amount of time to get a reply from another user. Now with Collibra Platform in place, the user can automatically search for the data and determine whether he or she has access to it. It has become very user-friendly, saving time and energy for the different departments. It has increased cross-departmental support, as people are less reliant on each other because there are certain checks already in place.

When we talk about the impact of Collibra Platform, our company does consulting for other companies. We have some out-of-the-box solutions that we offer, and apart from that, if a client has some requirement, we try to fulfill that in terms of our function as an organization. We are more focused towards providing workflows which require certain skills, and those companies that don't possess those skills reach out to us to get these features onto their platform.

Talking about the improvements needed for Collibra Platform, the first is learning. The platform is very large, so it requires a certain amount of information before you can work upon Collibra Platform. That is one thing that Collibra Platform should work upon in terms of how it can make a user understand what the functionalities intend to show. That is one core area I see. Apart from that, there are certain templates that it provides for AI governance, and these are very basic initially, but I think over time they could enhance these governance templates.

I chose eight because I am a firm believer that there is always room for improvement and Collibra Platform is no exception. There are two segments I have mentioned: since the platform is huge, users get confused at times. I think a better training program or a better way to explain the functionalities could be enhanced. Apart from that, AI governance is still being worked on and many features could be enhanced as we look forward to see its development.

I have been using Collibra Platform for almost two years.

Collibra Platform is definitely very stable. They release new versions at times, but they formally inform users, which is good. It is very stable in terms of stability.

Collibra Platform is highly scalable. As user data grows, you can enhance your licensing and everything works out for you. It is a very scalable platform when it comes to scalability.

I would highly suggest that Collibra Platform's customer support is outstanding. They are very keen on helping you as a customer. Previously, I had a situation where I got stuck and reached out to them, and within days they reached out back and we set up a call where we discussed everything. Collibra Platform is highly supportive when it comes to providing customer services.

Previously, we have worked with Alation, but as the client's requirement changes for us, currently we are using Collibra Platform. The reason for changing is not up to us; it is about the client. Whoever we work with, it is usually about them, not ourselves. Previously I worked with Alation.

I have seen a return on investment with Collibra Platform. Previously we had ten people working on a project and now there are six people currently working. Collibra Platform has certainly improved our working capability when it comes to platform usage. Collibra Platform does add value to your time.

When it comes to pricing, I think Collibra Platform is very high on the high-end side. The pricing is too much, but I would say that the price they are offering and the services they are offering are comparable. However, as per market standards, when comparing other data governance tools, Collibra Platform stands out in terms of higher pricing.

Before choosing Collibra Platform, we had evaluated Microsoft Purview and Alation for data governance. I would say Collibra Platform stands out above all the tools.

I would rate Collibra Platform around eight. I would give others looking into using Collibra Platform the advice to start with the university before entering into the main platform. This would give you a base on how to navigate in the platform and how to utilize the capabilities that Collibra Platform offers. I have given Collibra Platform an overall rating of eight out of ten.

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.

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.

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.

I have been using Collibra Platform for the last ten years.

Collibra Platform is stable.

We scaled from a few hundred to over a thousand users, highlighting effective scalability for us.

Customer support was great.

We did not previously use a different solution.

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.

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.

Before choosing Collibra Platform, we evaluated other options, including Informatica.

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.

My main use case for Collibra Platform is the Collibra Catalog for metadata management. Data classification and metadata management, both technical and business metadata management, are my primary use cases. I use Collibra Catalog for metadata management to import technical metadata from our schemas, and we ensure that the tags are applied for sensitive data and financial data. We also leverage automated workflows.

The best features that Collibra Platform offers are data classification and automated data tagging, specifically the data classification of financial and sensitive data, and the automated workflows that can connect to any platform, such as Teradata or Hadoop, to extract the technical metadata, which is very useful for our use cases for the business users.

The automated workflows help my business users specifically because we are migrating from our legacy system over to the cloud, Google Cloud Platform, and by leveraging these automated workflows, we can bring in a lot of technical metadata over to Collibra and at the same time onboard our business users. Collibra Platform offers a very customized user interface, making onboarding easy for us. Report generation was leveraged and was easy for the business users, and the end-to-end lineage was a significant differentiation that Collibra Platform offered, which was beneficial for our end users.

Collibra Platform has positively impacted my organization in all the ways I mentioned, as the benefits and user adoption for different data stewards and data custodians were easier because it has a very nice GUI. In real time, we can import a lot of metadata from different databases and even the cloud platform, which made migration to Google Cloud from the legacy platform easy and completed on time, while also offering benefits from a cost perspective through our market research.

Collibra Platform can be improved by adopting customized AI tools, similar to what other platforms like Databricks and Unity Catalog offer.

I have been using Collibra Platform for over two years.

Collibra Platform is stable, and that stability is why we chose it for our migration initiative to Google Cloud.

Collibra Platform is pretty scalable, although we have not explored a lot in that area because our requirement was pretty limited, mainly focusing on our cloud migration and the slow onboarding of the data stewards.

Customer support was very good, indeed excellent. Every time we had a person on the ground available to touch base with, plus there were weekly sessions with them that covered the loads and highlighted when it exceeded a threshold, so customer support was awesome. I would rate the customer support ten out of ten.

I previously used Informatica but switched to Collibra Platform for several reasons, including Informatica being very expensive, lacking smooth customer support, and the frequent charges for license renewal and software upgrades, which complicated the entire migration to the cloud.

The automated workflows help my business users specifically because we are migrating from our legacy system over to the cloud, Google Cloud Platform, and by leveraging these automated workflows, we can bring in a lot of technical metadata over to Collibra Platform and at the same time onboard our business users. Collibra Platform offers a very customized user interface, making onboarding easy for us.

We are just a customer of this vendor.

I have seen a return on investment as there were fewer employees needed, and the migration to the cloud from the legacy platform on the Hadoop side was much easier using Collibra Platform. The migration or onboarding process thanks to Collibra Platform was completed within a time frame of four months, representing a pretty huge gain for the company.

My experience with pricing, setup cost, and licensing shows that the pricing was reasonable and stood out much better than others, as per a Gartner survey.

Before choosing Collibra Platform, we evaluated Reltio, Informatica, and a few other vendors available in the market.

My advice to others looking into using Collibra Platform is to have a short-term and long-term strategy and roadmap, do research on your organization to identify which use cases would be a good start to explore, thereby better allocating funding to align with those strategic initiatives, while also ensuring that your business has visibility on your planning from the beginning so that the users of the tool remain engaged, along with alignment from their leadership on how and when to engage. I would rate this solution an eight out of ten.

My main use case for Collibra Platform is data lineage and data traceability, as it has extensive functionalities around those tasks.

Collibra Platform is particularly powerful for enterprise data governance. Currently, my company is undergoing a migration process between one database and another, so we use Collibra Platform mostly for data governance tracking.

When we need to find equivalences between one data platform and another, we can search among data sets and metadata. We can also assign ownership or stewardship.

Collibra Platform offers an intuitive user interface that allows you to navigate easily even without prior experience. The API functionality for ingesting metadata is also part of the core features.

When I need to register data sets manually, I can input API credentials and create BigQuery tables, modify schemas, and manage the records of every table through the API. Collibra Platform's APIs are very well documented, which makes the process smooth and motivates me to collaborate more.

Collibra Platform has impacted my organization positively because it provides comprehensive data governance functionalities for enterprises. It centralizes policies, ownership, business definitions, and rules, resulting in fewer inconsistencies and standardized terminology across the organization.

Collibra Platform could be improved by enhancing the user interface with artificial intelligence implementation that could suggest words as I type. Most platforms from other domains already offer this feature, and I think it would be valuable.

Overall artificial intelligence capabilities make a significant difference because they can reduce the time invested in typing.

Regarding the accuracy and reliability of output for Collibra Platform's AI capabilities, there is room for improvement by expanding the number of use cases. The platform is functioning adequately now but could perform better.

I have been working in my current field for over two years.

Collibra Platform is stable, and I have not encountered any errors so far.

In terms of scalability, I would rate it a solid eight, though I am not certain about all the implications since my role is focused on analysis.

I have not personally used customer support, but based on the written documentation, it appears to have gone successfully, though it could still be improved.

Before Collibra Platform, we used Google Spreadsheets or Excel files to track data lineage. It is beneficial now that we are using this automated platform instead.

Even though I cannot estimate the cost, the time saved is significant because we no longer spend time tracking where the data originated. We can go directly to the portal and see the specific source from which the data came.

I did not have to worry about pricing, setup cost, or licensing because my organization provides Collibra Platform as a tool.

I did not evaluate other options before choosing Collibra Platform because I wanted to start with it from the beginning, as it is very convenient.

I recommend that others use Collibra Platform, as it is a platform that combines many functionalities and handles the security aspect thoroughly.

Artificial intelligence is one of the main reasons I continue to use Collibra Platform, and while it could certainly be improved, I encourage the team to maintain this direction for customer satisfaction. I give this platform a rating of nine out of ten.

Collibra Platform is used for data cataloging, business glossary, data lineage, DQ integration, workflow automation, custom workflow automation, policy and governance management, role-based access, and stewardship workflows.

My day-to-day use of Collibra Platform involves working on the glossary, working on the lineage, developing custom workflows according to requirements, and aligning the whole process according to business needs.

My day-to-day use cases include asset approval workflows, triggering workflows for business users for bulk approval of their assets, change management, and the associated approval processes. Connectivity and metadata ingestion are also part of my day-to-day work.

Collibra Platform's best features are data cataloging, the glossary view, and the lineage part from both the data asset side as well as the business asset side. Collibra Platform's data quality integration is now bug-free, and I am currently using it to bring in DQ scores from the data quality side to the DIC, which is fully integrated and working well.

Automated workflows are an interesting part of Collibra Platform, providing flexibility, a very good user experience, and a nice dashboard to present. Collibra Platform's automated workflows have helped my team with a wide variety of integrations available out-of-the-box, including Snowflake, Power BI, Informatica, and other JDBC databases.

As a result of using Collibra Platform, I have access to many metrics regarding company internal policies, including the golden rules, their expiry, and everything which provides a better view of which assets are policy compliant. This is measurable and helps me understand which policies govern which data assets, their expected expiry dates, and reapproval needs. The quality of data, critical data elements, and personal identifiable information are also classified for improving the accuracy of data.

Collibra Platform has achieved improved data discoverability and governance standardization with reduced manual efforts and better compliance visibility. Collibra Platform delivers value that is more operational and strategic rather than immediate cost savings, with faster data discovery and reduced analyst effort, as well as better audit and compliance readiness.

Some improvements needed for Collibra Platform are minor fixes, as the major ones have already been addressed. I encounter some hidden out-of-the-box domains that are not easily configurable. Giving access to users would be helpful, and introducing more customization options for integration and other selections would also be beneficial. Collibra Platform is currently working on technical lineage, but I have not seen the latest updates.

I have been working in my current field for around three years and nine months.

Collibra Platform is pretty much stable in my experience.

Collibra Platform is highly scalable, with people using it day by day and different business units creating their own views to utilize the platform. The permission structure that has been introduced allows setting up domain permissions for the various business units in my organization.

Customer support for Collibra Platform is slightly different. For premium support, if I pay extra, they provide a very good and quick response. For normal users, the turnaround time is around 24 hours, which is also good.

I started with Collibra Platform from the initial implementation and did not previously use a different solution.

I believe the pricing, setup cost, and licensing were discussed by my CEO with Collibra support, and we did not openly discuss it among ourselves.

I did not evaluate other options before choosing Collibra Platform as I directly joined the company with experience in Collibra and began working with this platform for data governance.

Automated workflows are beneficial because when metadata ingestion takes place, I need approvals to be triggered automatically. If there is a refresh in a particular schema, it should go through the approval process for the candidate one. If any asset goes missing from the source, those should be obsoleted. This is how automated workflows have helped my team manage a large amount of data and metadata.

My advice for others looking into using Collibra Platform is to adopt the cloud setup for both the DQ and DIC instead of just the DIC. Using both on your own premises keeps everything under your organization's control, including the database and security.

I have covered everything I wanted to say regarding Collibra Platform, and I would rate this review as a 9 out of 10.

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.

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.

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.

I have used Collibra Platform for around two years.

Collibra Platform is very stable and has delivered better results.

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.

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.

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.

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.

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.

I am not sure about other solutions. Collibra Platform was chosen as the only option.

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.

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.