Collibra Governance Reviews

We use the solution's Data Stewardship part. We tried to explore the policy management piece, but we were unable to get through it. We haven't worked excessively on that. It was just some POCs or MVPs, but this is something that we would like to explore in the future. This is something that will be our future requirement in six to seven months down the line.

We use the solution's Data Stewardship part.

We are not able to ingest all the data in Collibra, and that's why we cannot do element-to-element level data tracking.

I have been using Collibra Governance for two years.

I rate the solution's initial setup as medium because it's not very difficult. We have to look at a few nuances from the infrastructure and performance perspectives. We have to consider whether we would have the leverage capabilities for that. So, all these things need to be considered from the engineering side.

Collibra Governance is an expensive solution.

Our current focus is more on the solution's stewardship, cataloging, and reference data features. The one feature of Collibra Governance we would like to explore is the automated tagging of PII data. We do deal with such kinds of data within our organization. It would be helpful if there were any videos available for us to go through because this is something that will help us in the near future.

We are not extensively using the solution's data lineage functionality because we are simply building over it. The only challenge for us is from the connective side. We are not able to ingest all the data in Collibra, and that's why we cannot do element-to-element level data tracking.

The major Broadlock would be the integration piece. If that is done, we'll be able to have all our data in the Collibra. The data lineage functionality is a really good feature, and we would really love to leverage it. The challenge is that the connectors are not available in the pipeline.

Collibra Governance is deployed on the cloud in our organization.

Overall, I rate the solution a seven out of ten.

The solution that I had worked on was related to the technical implementation of metadata for capturing analytics. That said, that particular implementation missed the bus with using it for business use and getting a proper buy-in from the users.

We learned some lessons on a past implementation, and with the new implementation, we're going beyond the data catalog and looking at the OwlIQ, data quality, as well as data lineage. We're really selecting some of the best modules within Collibra's toolset.

Right now, we're just implementing it. We're still in the purchasing process, however, having experience with it, I would say a great feature is its usability on the engagement with enterprise functionality. The crowdsourcing and just making it very accessible is foundational. At the end of the day, it always comes down to terms. For example, we might be saying the same exact term, however, have completely different meanings. It brings to light just the nuances, especially within a larger enterprise organization, a global organization. In organizations of this size, we've realized just how different our terminology views are. It sheds a good light on this and helps clarify. 

The data lineage piece is very useful for us. The ability to understand data flows, where systems and changes originate, is great. A lot of time you might have something on paper that isn't necessarily working in real life. This product brings about the right visibility to have the right conversations between business and IT.

There is a good community setup around the solution that can provide insights. 

It's not necessarily a tool specific, however, with any sort of application, there's an investment as far as the way in which you need to use it. There is a lot of upfront work that has to be considered. That's just a common reality with any software implementation. There's a lot of pre-work. You just don't turn on the lights assume it's going to work exactly as you envisioned. There is input and planning required.

If anything, I would say that the licensing is one area that could get improved. We have basically three roles: an admin, an editor, and a view-only role. It is limiting. For example, we want view-only, however, if we want users to be able to approve workflows, they need editor rights. That makes sense, except it doesn't necessarily meet all the business cases we have. In some instances, you might just need proper approvals, and you are not necessarily asking anyone to edit things. Yet in order for them to approve, they must have edit rights.

The last implementation was very much focused more on IT and capturing more of the IT view of data and even data definitions really focused on data standards, such as how we're going to name the technical fields or how we're going to name the entities. This new deployment is really much more focused on not just the IT side but on the business side and the operational side. It's based more so around analytics and operational governance. I'm hoping to use more of the modules and have a better, more favorable opinion of the solution's capabilities. While overall I have the sense it's good, the last company I was with didn't have the right business partners and it really just became another IT tool, which wasn't helpful to the company as a whole.

The initial setup requires more of a trial and error approach and there isn't too much documentation available to help you figure things out. There needs to be more online support around the sharing of best practices. There are a lot of use cases and people like the tool. That said, you hear a lot of pain points around large amounts of data being ingested and creating backlogs of data that need to be cataloged and there's really no way to prioritize it. 

Ultimately, it's a tool that should help to coordinate a lot of efforts and it would be nice to be able to look at something and understand how another experience could be similar or you can get a lesson learned before you actually make it your own lesson to learn.

This is more of a data governance tool, not necessarily a centralized tool for data cleansing. However, with the data quality module, that's the next evolution that's possible. Looking at data quality issues and then ultimately not necessarily being able to correct them, there's a lost opportunity. Data changes all the time. We're measuring it all the time. It would be advantageous to build this into more of a data quality tool in which users could cleanse data that could go back to source systems. That said, that's encroaching on more of the MDM solution.

I've been using the solution for about two years or so at this point. 

It's largely a good, stable solution. This is not an MDM solution. From a governance standpoint, there are some things that Collibra does better than some of its competitors, however, there's always something about having multiple tools and getting users to accept the multiple tools. It would be great if they could partner with an MDM solution provider to give more of a seamless look and feel.

In the last implementation, I do not recall dealing with bugs or glitches. In this new implementation, it's still too early to tell. 

The scalability potential is all around the framework that's specific to the company. It'd be good to have some general best practices from Collibra's standpoint. That said, is scalable, however, first and foremost, you need to implement it and really look at how the tool is functioning out of the box before you put your own strategy on it. 

Many times though, projects as they go, you're really not afforded that freedom. You might have a specific use case and you're trying to get that implemented so you'll get a quick win from a governance standpoint and so you can continue to incrementally add value. It's a balance due to the fact that, as we're trying to provide a solution, governance is an investment for sure. While there's certainly scalability potential there are structures that need to be in place from a foundational standpoint for it to scale as you need it to.

In the last implementation, there were about 20 users on the product. In that case, it was not that extensively used. Doing a data warehouse migration from Cloudera to Azure, things were collected, however, what was missing was the business definitions and the scenario-based understanding. Due to the implementation the last time, it offered a very flat view of the data. You didn't understand how everything was related or how things were scenario-based, et cetera. You couldn't get a sense of how fields are ultimately connected, and the KPIs that they ultimately built didn't help with understanding. The intention was that it was going to be an enterprise data catalog and it missed that chance. 

I haven't been in touch with technical support. I can't speak to how helpful or responsive they are. 

The implementation is not that easy. All the sell sheets and everything makes it seem as though it's more structured. Here you have this catalog, however, in reality, you have to define the structure including the data that you're going to be collecting, how you're going to define it, what those workflows are, what the user groups are, et cetera. There's a whole change management initiative even beyond just turning it on. 

With any application, whether it's cloud-based, but especially if it's on-prem, there is a level of pre-work that needs to be done. It's not just a turn-it-on type of event. Overall, that's sometimes lost in the process.

Getting it installed and all that is pretty straightforward if you can get a system integrator, or maybe if you have the in-house knowledge, however, it's really the strategy that's behind it that makes for an easy or difficult rollout.

The community is pretty good, however, I haven't necessarily found anything that's like user groups that can help guide implementation. A lot of it is you make a mistake and you have to go back and try to remedy it. There is a lot of trial and error involved.

We handled the entire implementation ourselves, in-house. 

While I do not have a sense of the version number, I would say that we are not on the latest version of the solution at this time. 

I would advise new users looking at getting it implemented to really use the out-of-box features before you overlay your specific strategy on it. Upfront investigations and creating a repeatable framework of how this will ultimately operate are important to the success of the solution. One of the crucial early factors is to get this as part of an operating fabric within your company. There's a lot of pre-work and pre-thought that needs to be in place in that sense. Having well-engaged business folks as part of it will help with the level of success as well. This is not necessarily a big bang type of development and release. It's very incremental. You've got to think backward as far as the user experience - of how things are going to be searched and located - and bring that back to your IT process.

I'd rate the solution at a seven out of ten.

We use the product for classification based on the different regulations and compliance requirements.

The platform is customizable. In comparison, Informatica Axon has predefined facets. Meanwhile, Collibra lets us create custom assets. It helps us build a powerful workflow mechanism where there can be any stewardship, including issue management governing assets using policies, regulations, or business rules. They are integrated very well. It has a lot of connectors with different source systems and efficient cataloging features.

There could be more integration similar to Snowflake, for instance. They do support integration, but complete lineage is not possible. Certain implementations, including lineage maps, could be user-friendly. At the moment, there needs to be more lineage between data sources. It needs improvements in terms of attribute connectivity during data transformation.

We have been using Collibra Governance for seven or eight years.

It is a stable platform.

Collibra Governance is suitable for enterprise businesses. It is a SaaS product. Thus, the end users don’t have to maintain scalability or maintenance.

The technical support team is responsive.

Positive

I have worked with Informatica Axon and Data Catalog. In comparison, Collibra has better workflow management features. I recommend it for technical usage as well. However, Axon is more user-friendly for creating lineage diagrams. It has ready-to-use templates for deployment.

The initial setup process is complicated. However, once you get good training and understanding of the system, it is very straightforward. Some of the configurations require support. It takes around a week or two to complete all the configuration for the existing ecosystem.

For Informatica, we have to buy cataloging and governance separately. Meanwhile, Collibra offers one structure for both. We purchase its annual license. There is an extra cost for additional users.

I rate Collibra Governance an eight out of ten.

Our major use case for Collibra Governance involves maintaining lineage, as well as linking business terms and technical terms together. Then, our use revolves around linking policies with actual data, such that we can create data sharing policies within the tool, storing data and quality results.

I am currently working on about 10-12 projects with Collibra Governance using the latest cloud version. It is available on both cloud and on-premises, but currently all our solutions are moving to the cloud.

Workflows is the most valuable feature of Collibra because we will typically use an interface for it and we can customize it as per our needs.

It is also a very user-friendly tool which is easy to navigate and understand right from the start.

Many other tools like Collibra Governance give you the option to actually see the data in the tool, which is not an option in Collibra. If you compare it with Alation, which has the compose data option, you can see the data right there.

Perhaps this is a feature they could include in the future, although I'm not sure if it is in their roadmap or not, because it is just a governance tool for storing metadata, and not for connecting actual data. If they could include some type of data viewing functionality, however, I would appreciate it.

I've been using Collibra Governance for around six years.

It has been a stable tool since I started using it, which was around 2015. We have used their cloud version since about 2019 or so, making that two years of stable cloud use, while the on-premises version has also been stable. I believe it has been in the market from about 2008 and they have made many enhancements over time with regard to stability.

Since our version of Collibra is on the cloud and we essentially only use it as a metadata tool, the best way it can be extended is to increase the cloud database. This is all done by the Collibra team, however.

At the moment, I am working on between 10 and 12 projects with it, so in this sense I can call it scalable.

The tech support is good because they have a dedicated team who will be mobilized to help support you on the aspect that you are struggling with. Usually, you will get a response from a team member who has knowledge of the sort of routine you are asking about, and you will be talking with someone who has good knowledge of the tool. Of course, it may happen that the support team member is new to the job, but they will at least help guide you in the right direction.

There is also a support portal where you can browse and search for articles that explain what you need to know. If you can't find the information you're looking for, then you can just raise a ticket with their support. It is very easy.

Positive

It's a very user-friendly tool and easy to navigate right from the beginning.

We didn't actually need to install anything with the cloud version because the Collibra team maintains the installation and everything related to it. They simply give us a direct URL to access it and the admin team then manages all the other considerations. Usually, the customers buy one, two, or three instances at a time, including instances for QA and development, but the deployment process really depends on the size of the company.

Deployment in general is very easy because they have a built-in migration feature with which we can easily migrate data from one system to another in a direct manner. We can also simply make a complete backup of the environment and then just upload it to another system using the backup option.

Collibra provides you with a license based on the subscription model that you purchase.

I highly recommend this tool to users who want to see the lineage of their data, including technical lineage and business lineage. It is very easy to create lineage views with it, and it supports many technical lineages out of the box.

I would rate Collibra Governance an eight out of ten.

The primary use case for the solution is the governance of data dictionaries. It is useful for managing and classifying data on a large scale.

The product has significantly improved data governance by providing a centralized platform for managing data assets and ensuring consistent definitions. It has led to better data quality and more efficient compliance with regulatory requirements.

The product's most valuable features are cataloging and classification. 

They could simplify the platform's setup and design process. It requires significant IT involvement and expertise, which can be a barrier for smaller organizations.

We have been using Collibra Governance for approximately five years.

The product is stable and reliable. I rate the stability an eight.

The product is scalable, but the extent to which it scales effectively depends on how well it is designed and implemented. 

I rate the scalability an eight. 

The product's pricing is high, which its comprehensive features and capabilities may justify. However, the cost can be a consideration for smaller organizations or those with limited budgets.

As a data governance advisor, I evaluate various solutions based on their fit for the client's requirements. While I recommend this solution when it meets the organization's needs, there are more than one-size-fits-all solutions.

Integration with it can vary based on the client's IT landscape. For some organizations, integration is straightforward, while for others, it can be quite complex.

Its user interface is generally user-friendly, but it could benefit from some enhancements to improve ease of navigation and customization. While functional, a more intuitive design could help users operate the platform more efficiently.

Its performance can vary depending on how well it is configured and the scale at which it is deployed.

It has strong data privacy and security features, including robust encryption and access controls. It is designed to comply with various data protection regulations, crucial for maintaining data security.

It offers extensive customization, allowing tailored configurations to meet specific organizational needs. However, achieving this level of customization often requires considerable time and technical expertise.

It has strong user adoption and satisfaction due to its comprehensive features and capabilities. However, user experiences can vary based on the organization's specific needs and the solution's implementation.

I rate it a seven out of ten. 

Collibra is generally used as a data governance tool, maintaining all metadata repositories. For each and every data that has been cataloged in Collibra, there'll be an owner assigned to it, whether it's a subject matter expert, a data streamer, data owner, etc. All the data is catalogued into Collibra. It has a single source of truth for data. I'm a senior Collibra consultant and we are customers of the company. 

We have data that people want to access and that's where Collibra fits in. They provide the SSO authentication so that anyone in the organization using the login can find what they want. 

Collibra is evolving their connectivity towards all programs across the IT landscape. The solution has good workflows and they now offer nine dimensions of data quality and provide a lot of features. The solution is based on AIML, Artificial Intelligence Machine Learning so that even if you don't know SQL, you can operate Collibra Data Quality. Collibra Workflows, Collibra Data Quality, are two good aspects that I would highlight from Collibra. Governance provides a user access mechanism, where you have all the data assets cataloged in Collibra. Not everyone can access all the data which is where the governance process comes in. They are constantly coming up with new features, and provide a monthly release.

The Collibra interface is not very user-friendly because it has a lot of features that business users find difficult to navigate. Anyone using the device needs some knowledge about how to use the tool and it takes a while to access and get used to the interface. I'd like to see them build a simple interface with only four dropdowns in order to get access to the request. If you're using it for the first time, it's difficult.

There are widgets in the dashboard and if they could make it more like a webpage instead of a Word document, that would be helpful. They have alternatives, but it takes a lot of work and even Collibra developers don't necessarily know how it works. Some changes are needed. 

I've been using this solution for three years. 

The stability is good, I've never felt any performance issues. 

It is highly scalable, we have around 4,500 users.

When you buy a Collibra license, they offer some training. If we have any issues, we can have a coaching call with them. In addition, they have a support portal. If you raise a ticket with them, they'll respond. 

Collibra provides support to anyone deploying the cloud version and implementation generally only takes a couple of hours. They are also responsible for maintenance.

There is a standard license for Collibra Governance and an additional cost for Collibra Lineage and for Collibra Data Quality. Author licenses have a set maximum limit; if you want extra there's an additional cost. That's their marketing strategy. 

I recommend going to the Collibra University web portal where you can register and log in. They provide a lot of basic information and the functionalities they provide. For anyone wanting to get into governance you can easily get certified as a Collibra consultant. Collibra has its own product roadmap. They have an ideation platform, where you can suggest ideas and if they get a sufficient number of responses in a particular area, they will add it to their roadmap and work on it. Collibra provides a lot to their customers as well as continually improving the product.

Anyone wanting data analytics uses Collibra. I rate this solution seven out of 10. 

We use it for metadata management, data lineage, and automated governance processes. I am working on the SaaS deployment, but I have also worked on the on-premise deployment. I am currently using its latest version.

We get to see the end-to-end data life cycle or the data flow in our organization. In my previous project, I implemented the Collibra Governance solution. We got the metadata right from the landing layer, and then throughout the intermediate layer, that is, the staging layer, the application layer, and the data warehouse layer. We then connected all the metadata together. So, in one single go, you can see how your data is landing, how it is getting transformed while it is moving throughout, and who is consuming this data through the reports, and in which report it is getting used. You can see the entire snapshot in one single click, which is a great feature for an organization.

The end-to-end solution itself is great. The most valuable is the workload feature that Collibra offers. There is a vast amount of flexibility in terms of how much we can customize. It gives us a lot of options to implement for a lot of purposes.

One problem is the data lineage, especially extracting the ETL transformation from different ETL tools and identifying how the data is getting changed from one layer to different layers and how the transformation is applied. It doesn't support all the ETL tools for extracting the transformation logic. It supports some of the tools, but there are still some tools that need to be supported. 

There is also a small pain point in terms of integration. There is a little bit of change in their strategy from Collibra's end. Earlier, they used to offer two solutions. One was out of the box, and one was a custom-built solution for which they used to provide a dual connector. Now the focus from the Collibra side is more on using the out of the box connector. They are discouraging doing the custom integration. That leaves us with two problems. The first problem is that the out-of-the-box connecter is not yet enabled for a lot of systems, and the second problem is that the out-of-the-box connecter has certain limitations. If we want to tweak those as per our needs, it is not possible. However, the custom-built is still supported, and you can still build a custom integration by using the API, but it is not very encouraged by Collibra.

Its dashboard also needs to be improved. There are options to use the HTML code to customize your dashboard, but it has a lot of limitations.

I have been using it for two and a half years.

It is a stable product. In the past, whenever a new version was introduced, there were a few issues, and a few things didn't work, but Collibra has improved the quality now. In the last couple of upgrades, I have not seen such an issue.

It supports the entire enterprise's data governance, which means that you can have a vast amount of metadata and bring metadata from any system. That could mean millions of tables and columns. I haven't seen its performance deteriorate too much. It is just that when you are trying to integrate with a new system and you are also trying to profile the data, it can give some challenges with a huge data set.

It is used very heavily in my latest project. The customer has a lot of expectations. They are trying to replace the existing system and want to completely move to Collibra Governance. So, it is being used pretty extensively, and they will add more and more to it.

I would rate their technical support as medium. I have had several interactions with Collibra. The response is usually within eight hours. You may or may not get a good answer in the first go. You may have to do a follow-up, again explain the question, and then they get back.

I have some experience with Informatica EDC and Axon, which together provide a data governance solution. The main difference is that Informatica has separated the business and technical aspects of data governance. EDC or Enterprise Data Catalog handles the data catalogs, integration, and harvesting the metadata, and Axon focuses on the business aspect of data governance, such as data lineage, data quality, and workflows. Collibra has everything in one solution. As far as integrations are concerned, Informatica has the edge over Collibra. It provides more connectors and more flexibility for building custom solutions.

If you are using the SaaS version, it is very straightforward. Otherwise, it could have complications. You won't realize those complications in the beginning because the product really starts running. However, when you start bringing the metadata from different sources, you will realize that there are some configuration changes that you need to make. Maybe the connectivity is not happening, and some firewalls need to be opened. Collibra is no longer providing the on-premise option for new customers. They are asking everyone to go for the cloud version.

In terms of deployment duration, if you are using a SaaS version, it hardly takes a day to get your product up and running. Implementing the use cases is an ongoing process. It typically takes six months to a year for implementing the high priority use cases.

It does not generally require a lot of people for deployment, but it also depends on the use cases. Generally, two to four people are enough. In terms of the team, we have a Collibra workflow developer, metamodel developer, Collibra architect, and integration developer. They all handle different aspects of the work.

In terms of maintenance, it does require maintenance, and you have to keep updating it. Most of the stuff is done automatically for you, but you still need to verify your custom code to check if anything is broken.

I have worked with two or three implementations. Even though my current client has a lot of expectations from Collibra, they have not realized the full ROI. They are still exploring it and have not yet reached that stage where they can make a decision. One of my earlier customers was pretty happy and satisfied with this solution, and they did realize the ROI.

I think it is on a yearly basis, but I'm not involved with the pricing session, so I have no idea. There are several licenses for different models. You get one license per product, but a lot of features are controlled separately through different licenses. So, as and when you want to use a feature, you have to procure the license for that feature.

I would definitely recommend this solution, but I would say that before starting the implementation, just understand what the product is, what it can do, and what it cannot do. Don't focus too much on the technical aspects of the product. Data governance should be used from the business point of view.

Data governance was a new concept for me. By using this product, I got to know a lot of different aspects of data governance, and how should you go about implementing it. One main lesson that I have learned from using this solution is that don't just focus on bringing the metadata from the whole system and dumping it into the tool. It will become unreadable for other users. You will end up with too much data that no one is using. It is better to start small.

I would rate Collibra Governance an eight out of ten. There are two main bottlenecks for my use cases that can cause trouble for me. It needs better data lineage functionality for extracting the transformations. It also needs better integration. I would like to see more connectors and more flexibility in terms of integrating it with different systems. 

Our clients are typically using it for metadata management. From a broader perspective, Collibra establishes an excellent foundation on which to build an enterprise data governance program. 

The most valuable aspect of the solution is its collaboration platform, which includes the workflows, the data lineage, and some of the communities. The ability to collaborate and approve business terms for the business glossary data dictionary is excellent.

The breadth of available connectors for metadata ingestion need to grow quickly to support customers as they expand their data governance programs to include a diverse list of source systems from which they want to derive business value. The connectors are needed  to bring metadata into Collibra and enable lineage, workflows, definitions, etc.  That said, this is not just a Collibra problem - this is an everybody problem. The central challenge is the availability of APIs to ingest text structural metadata, which is a common problem across any data governance platform or even any integration platform, honestly.

To be fair, I would say that Collibra's purpose and primary value is as a collaboration platform, which is the core value of business-centric data governance, and not as an integration platform.  For this purpose, they are clearly the leading solution.

We've been using the solution for six or seven years. We've used it longer than almost anybody.

The stability is very good. It's not buggy and it doesn't have glitches. It doesn't crash or freeze. It's reliable.

It's really scalable, it's really solid. If an organization needs to expand their solution, they should be able to do so easily.

We've reached out to technical support rather frequently. That said, it depends on the topic. I would say that their tech support is excellent, but it is not necessarily an overly large team because they are still a growing company.

They have some really good, smart people, however, they don't have a team of experts for each target subject area.  They don't have a team of 20 people for each application component that can just go, "Oh, yeah. We set an appointment tomorrow!" You might have to wait a few days for the right person.  Having said that, their focus on making detailed self-driven education and training available online enables clients easily to investigate application areas.

The way we view data governance is this: it has to be led by the business. It has to be business-facing. Although there's a number of applications that might have a data catalog, for instance, like Alation, Informatica or Talend, we're vendor-neutral. If we find something better, we'll switch. We're open about that.

With Collibra, their strength is that they were the only data governance platform built specifically to address data governance as it was being formed as a discipline. Virtually every other solution in the marketplace is built as some sort of data management application aimed at IT, and has either morphed from an ETL or something else into that. Alation morphed from a code scanning application into data governance solution (data catalog) for instance. 

Collibra also took a business-centric approach. Their application is the only one that you could throw a business person in front of, and they would understand it intuitively, they'd say, "Oh, okay. So this is where I approve items. This is where I request them. This is where I see things. This is a dashboard that I can look at our progress." You're not going to get a sales VP going into Collibra, but if a sales VP went into Collibra, they would understand it. That's another reason why this has been the data governance solution we have recommended to clients, and still do.

The setup is not complex. It is straightforward. Collibra's very good at doing setups very quickly, so we typically leave this to them. They sell a cloud installation. Essentially, they formerly were both on-prem and cloud, however, now they're focused only on a cloud delivery model based on customer demand.  Thankfully, it is extremely straightforward, as this is the box we need to check prior to helping clients move forward on their data governance program.

The costs vary. I don't have details on the exact pricing of the solution as we do not resell it even though we recommend it.  This enables us to maintain our neutrality as a client advisor.

Their licensing model focuses primarily on the advanced technical users to help to establish the data governance foundation and manage and maintain it as more and more business groups are brought on board.  What I like about their licensing model is that they try to remove barriers to adoption by making it very inexpensive to add "data citizens" across the organization, i.e.  normal, "lite" users who are using, but not developing, connectors, workflows, communities, etc.

In that sense, the marketplace perhaps is not aware of the beneficial TCO of Collibra's license structure, because it causes them to focus on the initial cost of the heavy advanced users, while not realizing that they will be able to bring the overall corporate community onboard at a relatively minimal cost. Therefore, their pricing can appear high per user, however, in fact, for a community or population of data governance users, it's, not actually that high, it's just front-end loaded to establish the technical foundation and basis for the data governance program.

We are experts on implementing business-centric data governance programs, as that is the only model for success.  As such, we are implementation partners with Collibra, and in fact are one of, if not the, longest-standing Collibra partners globally.

The advice I'd give to other potential users would be the same I'd give to people implementing any sort of governance. I would first advise clients to have your data governance business cases ready in advance, or at least start by identifying potential business outcomes that can be delivered through clear and documented access to data. From there, they can target the relevant source systems needed to delivere on these business cases.

From a technical perspective, there are different approaches to ingest structural metadata, i.e.  tools and connectors that are available to assist with this.  While Collibra is hands-down the best data governance collaboration platform, clients should review the different options to ingest metadata based on the targeted source systems.  Of course, Collibra's catalog is the first option that should be considered, but available connectors need to be reviewed.

Overall, on a scale from one to ten, I'd give it a nine. based on its excellence as a data governance business collaboration platform.  From the perspective of metadata ingestion,  I'd probably give it a seven - I like their current roadmap and designated approach, but connectors are a work in progress, as they are for everyone.