Collibra Governance Reviews

We are focused primarily on the Data Governance Catalog (DGC) for our data dictionary use. We are not using it for information governance in terms of regulatory compliance, etc. We are focused on business glossary, data catalog, data dictionary, and some workflow processes to help with metadata management and other things.

We are fully updated, and we are using its latest version.

One of the workflows that we're just finishing and rolling out is a certification process. Collibra DGC has an attribute in there called "certified," and it is basically a yes/no choice. We wanted a lot more information about the certification of data sets, so I wrote this workflow, which is probably 30 or 40 steps long. We have a series of criteria that we have to meet in order for a data set to be considered certified. I was able to create attributes for all those and create a workflow that goes hand in hand with data set development so that when somebody competes their work, he or she can pop into Collibra and say, "I have finished this." It logs it and it becomes part of a trust score. It is really nice, and it is making our certification process more robust and the documentation easier to collect and maintain.

I like Collibra's flexibility. I like to be able to modify things for our own use. For example, we've chosen to use Collibra also as a knowledge management tool, even though it is not designed to be a knowledge management tool. That's the beauty of it. It can serve as a knowledge management tool by creating some custom assets specifically for knowledge management. I have a knowledge base domain and a knowledge base article asset type- along with a few other things. I really like the flexibility to be able to extend it in those non-traditional ways.

On the flexibility side, I've created some really nice and very useful custom workflows that have really helped with work processes and productivity. They've really helped us do things easier, faster, and better.

The UI is good if you happen to be an administrator and are familiar with the technical side of the administration. If you're a business user, the UI is not good. It is hard to learn. It is hard for those who are administering it to teach to end-users and it can take hours of training to do it. Because it is difficult and non-intuitive, business users resist using it. It is a battle to get them on board and to keep them engaged because of the UI. On the other hand, Collibra just hired a person specifically to revamp the UI. So, they're dealing with it, but it isn't there yet.

They're working on the lineage harvesting for technical lineages. I don't know this for a fact, but my feeling is that this is new to them. So, they're still developing it and it feels awkward.

I have been using this solution for eight months.

Its stability is very good. Out of 10, I'd probably give it a nine. We've had a couple of little glitches where something happened, but they were minor and we were able to create tickets and get issues resolved within a week and usually within just a day or so.

So far, we haven't had any major problems. We're ingesting metadata from AWS Redshift. We've also got connectors built for S3 but we haven't used them yet. We're importing from Oracle and working on lineage harvesting from DBT, Data Services, and few other places. So far, everything has been really good. We're importing metadata from Tableau, and there are no problems there, either.

In terms of the roles of its users, we've got product managers and solution managers. (A solution manager is the IT coordinator who works with the product manager.) We've also got analysts, engineers, reviewers, editors, data stewards, and data coordinators or custodians. We also have technical stewards, admins, and a group of people we call "normal" who are business users that have read-only access.

In terms of Collibra's usage, I would love to have it used 10 times more than it is, but because of the difficult UI, I am getting resistance from the users. It is hard for them to navigate and learn the interface. Once you know it, it is easy to get around and find what you need. It is just about learning the interface and dealing with some poor choices of how to use the screen real estate. So, right now, the user engagement is lower than I would like it to be. 

Their technical support is very good. On a scale of one to 10, I would give them a seven. We've probably had four or five tickets open and were able to get them resolved quickly. 

It feels like they may be sensitive--possibly they've had some bad reviews regarding their customer service--so it seems like they may be going overboard there. For example, they have scheduled a meeting every month for our team to meet with what they call a customer success manager.  I feel like this is too often.  They're responsive about stuff, but it feels like they're trying too hard.

Prior to this and strictly for our data dictionary, I used Dataedo. They are very good at what they do, but have a much more focused solution.

For knowledge management, I used Confluence and really liked it, but we came up against the issue of access levels for for non-registered users; we didn't want to pay license fees for a large number of "read-only" users. Basically, it is either full (paid) access or free access to "the world" and like everyone else, we have information that we don't want to expose to the world.

Setup was really straightforward. Collibra was very good with holding meetings and being responsive to requests. I was pleased with the setup and configuration process. They were really good at the initial stages of learning and understanding what we were doing.

Those of us who are working on this project also have "day jobs" so we were not focused solely on this. The focused time on it among members of the team was probably less than a hundred hours extended over a period of several weeks.

In terms of maintenance, we have a small, three-person team of people who are actually working on the technical maintenance side. All told, the actual time that we spend in administration at this point is very low--perhaps 20 hours a month spread between three people.

We did it in-house with direct interactions with the Collibra team. Our experience with their team was very good. They have an onboarding process and a roadmap they like to follow. We were just one department with a small team working on the actual setup and use case. Several of their steps didn't apply to our use case so we skipped these and even took some of the other steps out of order simply because it made sense for us. The onboarding team at Collibra was 100% supportive of making those changes and doing things the way we needed instead of the way they ordinarily would have done.

It is substantial, and we pay yearly. 

The thing that made our onboarding really simple was that we understood beforehand our use case and our needs. We understood what our roles were and who needed to be involved. We also understood our communities and our setup structure. We had all of that from the beginning. They mentioned several times that we were extremely well-prepared. So we learned that the more users know about the needs of the department or the company, and the more advance prep work they can do, the easier the onboarding process is.

When we started, the Collibra team sent us two huge Excel files that were basically questionnaires that they wanted us to go through to prepare for onboarding. We already had all of that done. It was finished but wasn't in the same format.  We wrote back and asked, "Do you really want us to fill out these Excel sheets? We've already gathered this information." They said, "Oh, great. We will skip the first two steps of onboarding because you've already got it." That really accelerated the process.

I'd give Collibra a nine out of 10. I am really happy with it though there are few things that I wish were different, especially in the UI.

Collibra Governance is used as a data governance tool to manage your business metadata and technical metadata from various systems. Customers also use the tool to provide a data cataloging option, create a data lineage, and automate some of the business processes.

The solution's most valuable feature is data cataloging. The solution's data cataloging feature is mainly used for data discovery. Nowadays, data cataloging enables the data marketplace to share data within enterprises. That's another enablement that Collibra Governance does.

When you have a huge amount of hierarchical data to manage, the solution's performance tends to decrease.

I have been using Collibra Governance for six to seven years.

Sometimes, when we face an issue, we resolve it by ourselves. On other occasions, we contact the solution's technical support team. I wouldn't say that the technical support is excellent. The support team struggles to resolve the issues 60% of the time. However, they are able to resolve issues the remaining 40% of the time.

Neutral

Many of our customers I spoke to felt that the solution is a bit highly-priced.

I sometimes recommend Collibra Governance to our customers based on their requirements and environment. Most customers look forward to having a data lineage function, but I haven't seen any tool that satisfies the customer requirements, including Collibra Governance.

The solution has primarily enabled some of the compliance reporting through data lineage reporting. When you have data cataloging with complete metadata enrichment and identification of PII and non-PII, it helps customers control and manage them properly.

If a customer does not have the appetite to procure Collibra Governance because of the pricing models, we may recommend a different product with cheaper prices. Collibra is working on building a new product for AI governance. I want to see how Collibra's data governance and AI governance will relate to each other.

Most of the customers we deal with are looking for a tool to resolve the data lineage challenge. However, none of the products in the market seem to be resolving the customers' data lineage issues. Vendors like Collibra, Alation, and Informatica could work on it and provide a more comprehensible solution to the customer.

Overall, I rate the solution an eight out of ten.

There are different use cases, including integration with other applications, setting up operating models for specific business domains, such as finance or manufacturing, defining domain structures, and implementing data quality rules and scorecards. The specific use cases can vary from client to client, but they generally involve leveraging Collibra's capabilities to establish a strong governance framework and improve data management across the organization.

I appreciate its user-friendly interface. It facilitates explaining and handing over the data between the teams. It enables a linear view of the data assets across different levels, providing a comprehensive understanding. While other tools may offer similar features, Collibra Governance stands out for its integration capabilities, particularly with platforms like Google Cloud. It is also well-regarded for its modern and cloud-based approach, which aligns with the needs of clients that utilize multiple cloud solutions.

There are certain limitations and difficulties regarding the migration of complex data quality rules, as the tool may struggle with lengthy calculations and longer loading times. Our clients reported that they have experienced runtime errors in those scenarios, Also, setting up the tool and seeing real results can take a significant amount of time and manual effort. Many clients struggle to find experienced consultants due to the tool's extensive features, and this shortage impacts the deployment process and overall value realization. The pricing structure is significantly expensive and not affordable for all the clients. I would suggest that Collibra consider offering a lighter version of the tool for small companies. Currently, the main focus of their strategy lies in targeting medium and large enterprises.

I have been using this solution for a year now.

It provides good stability. We didn't have many complaints about it. There have been some challenges with complex rules, particularly about data quality.

It offers good scalability that is suitable for medium to large companies.

They provide excellent support, and there is positive feedback in the market regarding their support services. The collaboration between Collibra Governance and their clients fosters mutual learning and improvement. 

Positive

I previously used other solutions, like Azure and Informatica, but Collibra Governance offers the best experience regarding the user-friendly nature of the interface. While the other tools have their strengths, Collibra stands out for its compatibility features. It is a competitive solution that offers a variety of comprehensive capabilities.

Configuring is relatively easy with the right training and materials, which is essential for users to understand and utilize the tool effectively. The complexity of the configuration itself depends on the scope of the project, with smaller use cases typically taking one to two months. For larger projects, a team of three to four people, including a developer, engineer, and governance specialist, may be required for deployment. The maintenance is straightforward. Overall, it is a user-friendly tool for administrators.

Generally, it is a rather expensive solution compared to some other tools in the market, but I found it to be fair-priced for its capabilities. The cost barrier often causes potential clients, especially small companies, to opt for other choices. I saw many clients coming back to Collibra after realizing that other tools have significant limitations. The cost factor also varies depending on the size of the company, as larger organizations have a bigger capital to invest in multiple tools.

I recommend considering it, as it provides valuable features. It may be advisable to evaluate and assess the requirements and preferences of the client before making a final decision. I would rate the solution eight out of ten.

I've been working with multiple companies, but with two of the companies we have been using Collibra mostly for data governance. With these companies, our use case is all about metadata governance, lineage, and data-related policy management. We're doing policy management directly inside Collibra and we're also using it for issue management on the analytics side.

If someone has a data concern, they just call me in and then put that concern into Collibra as a front-end UI for the data stewards and data scientists, and we start processing them.

We have benefited greatly from Collibra's data governance reporting. If we want to know more about a specific data element, we can use Collibra to get a picture of the whole history of it.

For example, who is the business owner for it? Where is the data coming from (especially when you have different sources which come through) and who was all touching it? And if I wanted to add a rule, like a business rule or a data quality rule for that particular data element, how or where do I keep it? It's like one central place, but for all these items.

I like the lineage feature the most because I don't think there's any other tool that actually depicts the data flow from multiple sources and the connectivities between every data element inside those sources.

I don't think there's any other solution where you can view multiple systems and multiple sources and data places and you can just write it down. It's a lot of work to initially organize but there's no other tools to do lineage like Collibra does it.

The connectors are not very sophisticated. They can do, for example, Informatica and Tableau, but the connectors themselves could be improved.

I recently got a subscription for another 600K for Collibra for one more year, so the author licenses are not used much. And they keep changing the UI platform; that can also be improved.

From an administration perspective, I like the white-glove onboarding part of Collibra. That was actually nice and I really liked that. For administration in general, I like that you can use Collibra however you want. It's more raw and easily adaptable.

So you can cook it or you can steam it or you can make changes to it in a lot of different ways, but it would also be nice if there were an already available analytics tools like Tableau at hand. Though it is easily adaptable and you'll have a completed end product which you can really leverage.

I've been using Collibra Governance for five or six years.

In terms of scalability, it's more like adopting; it's more like a shark. You have to keep feeding it and then it will grow. It depends on how many systems you're using. I worked for a union bank earlier when we set up Collibra and we were able to push in 3000, 30,000, 30,000 data elements. It's great when all the data is available because the team had been doing data analysis for more than a year prior to getting onto Collibra.

At my current company, the data analysis started at the same time along with the data governance and I think I hardly have 300 data elements. So it works on however much you feed it.

And if you have a huge data dictionary and business glossary already available, well and good. Instead of putting it in an Excel sheet, you can put it on Collibra and then you can actually walk through it. But if not, then you have to start feeding it, and it might take at least two years until you get proper food for the tool.

The technical support is okay, definitely not bad. I think they have a 24 hour SLA, but again, it's a data governance tool, so if it breaks and it's not available for a day or so, it's not going to create any business loss. It's more of an understanding kind of tool, and if the SLA is a bit delayed it won't be much of a problem.

The only comment I have is that some of the technical support teams in privacy, security, infrastructure, etc., could be more available during US timezones. That would have made our onboarding process easier.

We went through setup with the white-glove onboarding program. I actually gave feedback to Collibra as well, because the process is a little unusual, but I appreciate it.

The one thing I found a bit difficult when properly onboarding with Collibra and setting it up is that some of the Collibra teams we're working with, like in the security, privacy, and infrastructure teams, are in the European timezone and not the US timezone. Because of this, it becomes a little uncomfortable. It would be great if they could change things around so that there's also somebody available in the US.

It's not just one single technical support team when you are setting up Collibra; you have a lot of different puzzle pieces to work with. That's what the white-glove onboarding is all about. So it actually takes five to six weeks to completely set up, from starting with the solution to getting the software installed and all the nodes set up.

Whether it's on-premises or online, in both cases the whole setup takes five to six weeks and in this time frame I also need to have the company-related IT support people available. And it's just hard for me because most of Collibra's support teams are on Europe time. It could even take up to eight weeks.

Regarding implementation, we need to have the role-setting, we need to have the workspace in the UI in the front end, we need to build the communities, the groups, etc. So it's more like a whole structure that you have to build, and it's a lot of work.

It's more raw, so you can change it however you want. But the thing is, there's not much of a guideline and it depends on your company and organization as well. So you have to ask, how do you want to do the structure? Then you first have to find the communities, and you'll have to set up the groups and the UI, and what comes back, and it's just more about adopting the software to your needs.

Our data officer was very interested in doing it. So she's fully on. And we had an administrator, a developer and the business. We had around three or four business owners to set up the first part before we adopted the rest of the businesses. Of course I was there, too, and there was one more project manager. All in all, we implemented Collibra with only about eight people. As for ongoing maintenance, we only require one administrator.

We have not seen ROI yet. Again, it's more like a dictionary. You buy a dictionary at home, so whenever you want it, you use it. What is the value of getting the dictionary? I don't know. It depends on your talent. If your team does not have good talent, then the dictionaries are more useful. It gets easier to navigate. And if you don't have the dictionary, it's going to be hard.

I think they have a trust issue.  I did not like the way they recently went through the process. They were like, "Finish this SOW first, only then will we sign the other SOW." Or, "Finish this code." I didn't like that much.

And they're also very hard. They don't negotiate much: The first price is the first price. We tried our vendor management team contracts that our negotiation people use, but they did not negotiate at all, nothing at all. The very first price they quoted, they almost always stuck to the same price, within 95-98%. Always the same price; hardly anything went down. So that's one thing. They shouldn't do that.

Generally, when all the vendors quote, first they quote and then we start negotiating it. They might then reduce the quote or just provide a different way of getting around. Collibra were very rigid cost-wise, so they should improve that or maybe come up with some plan on how to negotiate.

I think we considered Informatica and one or two others that I can't remember off the top of my head. Informatica was the actual challenger to Collibra before we finalized the cost and everything.

It was cheaper, and it was another good one from an analytics perspective. But we know that, industry-wise, Collibra is number one from a data governance perspective. That's one of the reasons why we went with Collibra, even though the rest of the tools' setup cost and maintenance were cheaper.

It's a very niche product. It's nice to use and easy to promote. You don't have to have all the user licenses - you can also get the author licenses. If you have 10 author licenses, you can get up to 50,000 consumer licenses. It's nice to know you have a mobile component in that regard.

If you're doing a lot of training as well, you need to do proper training with your data team, and with your business team, try to use it as a business tool instead of a technical tool. Employ it as much as you feed it, because then it's that much more useful.

And then having the business rules, the data governance and data quality rules, everything in one place, is nice to have. If you try to utilize it, the data lineage is number one, because there's awesome capability in it. So just try to use it and you'll start loving it.

I would rate Collibra a seven out of ten.

We primarily use the solution for when the customer needs data governance to establish cases. We're choosing the product in order to meet the requirements of the customer. That includes requirements such as establishing a governance council if the customer does not have one. It's for data management and the solution handles data quality and metadata management, et cetera. 

Before implementing data governance, the customer had a pain point of identifying the data and providing data useful to their business. That was the biggest challenge. There were also many data quality jobs where the customer wanted to find and identify the data in terms of where the data is sitting and who was responsible for it, et cetera. We were able to identify data sources, which applications were available within the organization, the domain level, and more to clarify exactly what was happening, where reports were sitting, who was connected to what, where data was coming from, and more. It also helps clarify job roles and showed access to identify where pain points were to get an overall picture of the data of the entire organization. 

The ability to pull together data lineage is one of the most valuable aspects of the product. 

The transparency was great. the business was able to come in and see the data and what exactly was happening in a way they couldn't before. The company could see job roles, data sources, and policies. 

The quality and visibility of the data links are great.

They used to rely on third parties, however, now, for example, they've brought in their own data quality tool. 

The beauty of the solution is that you can customize it quite a bit.

The technical support could be better.

Previously, it was a challenge to integrate tools like MuleSoft into the product. However, they've gotten better. 

There needs to be more security and compliance embedded in the product in the future. 

I've used the solution for close to seven years. 

The stability is great. I'd rate it at around a nine out of ten in terms of reliability. There are no bugs or glitches, and it doesn't crash or freeze. 

The scalability is quite good. I'd rate the ease of expansion at an 8.5 out of ten. 

We weren't overly pleased with the technical support. They need to provide a better quality of service to the customer. 

Neutral

I'm also familiar with Informatica Axon. I find that it is a little stronger in the data quality department. However, it is not as easy to deploy. 

It's not too complex to set up initially. It's pretty easy if you are doing a basic setup. However, it does depend on the client's requirements. You can customize a lot of things, which is great. 

We handled the setup ourselves in-house. I mostly did the implementation myself. I have seven years of experience and am quite comfortable with it. 

We have witnessed an ROI while using this product. The customer typically sees huge returns. 

The solution isn't overly expensive for bigger customers. Typically, the cost is handled by the customer, not me, and therefore iI can't speak of the exact pricing. 

I'm not sure which version of the solution we are on right now. We're on the cloud deployment, meaning we are likely using the latest iteration.

I'd recommend the solution to others. It's a straightforward product. 

I would rate it nine out of ten overall.  

Collibra Governance is used to maintain and govern our company's data and evaluate the data quality. 

Collibra Governance allows users to scan the data in the Schema and check its quality. Our organization's business customers add their company data to Collibra Governance and use data visibility to evaluate how the data can be increased or utilized for some business decisions.

For example, if you have ten columns in one table and assume one column has a couple of null values, Collibra Governance will identify and show you the number of null values present. The identified columns can be further manually checked and altered to enhance the total data quality. 

The solution's search functionality can be improved. For instance, if I search with one piece of data, the tool provides a granular level of data and sometimes billions of data results, among which it's extremely difficult to find a relation. Instead of the aforementioned type of results, the solution can provide a hierarchy based on levels that reveal data upon click. 

I have been using Collibra Governance for three months. 

I would rate the stability a nine out of ten. The product is highly stable. 

I would rate the scalability an eight out of ten. It's a satisfying data quality evaluation tool. 

I would rate the tech support an eight out of ten. The response time from the support team can be further improved. But an immediate response cannot be expected for Collibra Governance because it's not a critical product with urgent use cases.

Whenever, our company has faced issues or bugs while implementing an update of Collibra Governance, an extensive wait time has been encountered. The response time from the support team can be improved based on the issues faced or in an ad hoc format. 

Positive

For the initial setup of Collibra Governance, the vendor's product team assists our company. At our company, we deploy Collibra Governance on the cloud. 

Collibra Governance is extremely expensive. The solution is provided as a whole package, and users cannot avail of only a particular set of features; the whole package must be purchased even if it's not required. 

Collibra Governance will face competition once a data governance tool hits the market that provides basic features at the ideal cost. The pricing model of Collibra Governance should be more flexible for clients.  

At our company, we have used the data catalog feature. Collibra Governance is the top data governance tool in the market. AI capabilities are already being introduced in Collibra Governance. The data lineage feature is also used in our company for data harvesting.

Based on the business requirements, we customize the solution if needed. I would rate the solution an eight out of ten. I would recommend Collibra Governance to others. 

We've used it for cataloging or defining our business data entities and their associated attributes or data elements. Where appropriate, we are defining their sources and their modes of derivation. Rising above that, we are also using Collibra for the definition of our business metrics that are calculated from those data elements and the derivation definitions associated with them.

We have folks in the field doing our clinical research operations, and they have the opportunity to refer to Collibra when they are examining a particular report. When they have a question about how something in that report is derived, they can pull a metric that is defined fully in Collibra. They have the opportunity to drill back into Collibra to see that.

It is a big library. It has a long list of data assets and their descriptions and lineage. It's fairly two-dimensional. For my use, it just has lists of things. There might be others in my organization who are tying the data elements, metrics, and other things together, but I don't rely on that, and I don't leverage that. For me, it is a fairly flat library for information.

What I use it for is fairly rudimentary, and I don't have any complaints about it. I haven't tried to stretch the boundaries at all, but it would be nice if there were capabilities built within the system to somehow help enforce the quality and consistency across related elements that are built in the catalog. It could have intelligent capabilities built in to help maintain the quality of the data and information, such as natural language processing, machine learning, and so on. 

I've been exposed to it for about seven years, but I have been using it more heavily over the past couple of years.

I've not seen or heard of any problems with its stability.

I haven't seen any impediments there. So, I have no concerns about scalability. It could be because I haven't been this involved in pushing the boundaries, but I've seen it accommodate new layers without hearing of any issues.

It is open to everybody in our organization. We have more than a thousand users. So, there are more than a thousand people out there who have lately used Collibra, but most of them have used it in the reference mode or read-only mode. In terms of their roles, we've got everybody from data engineers, data analysts, and systems developers to business analysts and business end-users. 

I've never called them, and I don't hear anybody complaining about it.

As far as I know, this was our first venture about seven years ago into data cataloging and data governance.

I wasn't involved in the setup, but I can see that the maintenance of information within the system is quite straightforward.

My guess would be that we took care of most of the things in-house.

I'm only involved in the use of it. My advice would be to make sure that the content is of quality because it tends to mushroom into lots and lots of information that can easily get out of sync. It should only be entered into by an organization that has the discipline behind it to maintain the information at a high level of quality. Otherwise, you end up with a lot of information that seems useful, but in effect, it could be more harmful than it's worth if things get out of sync. It takes an organization to maintain this kind of solution. The content is dependent on the quality of the maintenance of the content.

I see a small chunk of it, and I would rate it an eight out of ten.

I worked with this solution a few months ago and the main use case of Collibra was as the central metadata tool for the enterprise. The plan was to have all of our data dictionaries, our business glossary, to expose data lineage through Collibra and show all of the relationships and connections between our various tables and databases and the actual semantic business layer, in Collibra. It was a way to unify our technical metadata with our business metadata and with our actual applications.

Recently, a lot of work has been done around sensitive data elements. Collibra is really a good tool for centralizing a list of elements that could either be first or second order PII and connecting the top policies around those specific PII elements to the systems they're found in, and how they are implemented. If they're used as different names in different systems, that's valuable because it's helping the company meet its goals in terms of new legal regulations for the EU as well as for California. Those two are our GDPR and CCPA which are the two most recent policies from that domain. It's also very good for data quality issue management. Collibra is essentially the main tool for that. It's a valuable tool in many different companies.

The interface itself is very useful. I think what I find most useful about the tool, if I'm looking at it from the perspective of a data user, would be the search capability. The fact that I can search for any data elements that are in the table and there will be a pretty comprehensive list that are either identical or very similar to one another in the tables where they are found. I think in terms of sourcing, it's really valuable. I also think that the ability to connect your business metadata with your technical metadata, is something that's very valuable from the perspective of the business. People on the business side need to understand where data is coming from, how it's connected. Doing that through one centralized repository, or document, is useful.

The issue may be the way it's been implemented in my company but, for Collibra to be really useful, what's missing is an easy way to connect to different data sources and different types of data sources and actually ingest and profile some of that data. That's the trouble we've always had in getting wider adoption of the tool. Unless there's a mandate from the enterprise data office or the like, regular users are not going to use the tool for really robust business use cases without having some actual data in there. I know there is some out of the box capability for this, but I think it needs to be easier for Collibra to actually ingest and run some basic profiling on the data itself. That's currently missing from the tool. 

I think that today this is a stable solution which wasn't the case in the past. For a couple of years, there were certain outstanding issues and bugs that took a really long time to fully address. Those have been taken care of at this point.

It's a very scalable tool. There is a ton of metadata in there. If they were to roll this out to other lines of business and start getting more adoption, I don't think they would have a problem with scalability. I think the problem is really with getting that adoption in the first place.

The company is very hands-on providing support and solutions but I think the problem is that they might be stretched a little thin. It's a fairly small company, I believe, and there have been cases where we had to wait months to get support to fully patch something that was wrong in the tool. It's even more of an issue if you are connecting Collibra with another third party tool because you have to get everybody on the call. You have to make sure that they're corresponding, following up in a timely manner. It's just not easy.

I have previously used the Sandbox versions of Alation, and Informatica. I remember Alation being overall very similar to Collibra. I think Collibra's UI may be a little better. I think it's very user-friendly. I would say definitely superior to Informatica. I haven't really heard many good things about the Informatica business glossary metadata solution although it has been a while since I have seen or used that and it may have changed. I definitely think Collibra is the gold standard in terms of combining user experience with the actual capabilities. Again, at the end of the day, it's really a matter of implementation as to how good it actually is and how positively it will be adopted.

There have been some issues with the implementation and the adoption rate has not been high. It's not being used extremely extensively. It's being used for those use cases already mentioned, meaning at the enterprise level for identifying PII and complying with regulations. It is being used for data quality issue management in finance but as far as I'm aware it's not being used for data quality issue management for other lines of business.

I don't exactly remember the pricing but my impressions from everybody that I've talked to is that it's an expensive tool. It's more expensive than its competitors. It may well be worth it in terms of how it's being used. I think it's a superior tool, but it's also a premium tool. 

Before purchasing a license or licenses for Collibra, you need to have a data strategy or data governance and a management strategy defined beforehand. You need to have at least some semblance of an idea of how you want the various spaces and communities in Collibra to be organized. Obviously, certain things will change as you get familiar with the tool, but you can't just wing it. You need to have a strategy that also takes into account other tools and other solutions that you want Collibra to be connected to because there could be an issue where maybe you have a data lineage tool that is getting upgraded in three months from now, and your current version of Collibra will be better suited to connect with that tool once it's been upgraded. You're never going to be able to know 100% beforehand when those types of events will happen, but you need to have some kind of strategy in mind. This is where you really need the investment in data governance and management before you define the tool that you're going to use. That has to come before any implementation of Collibra. 

It's a big tool, so it can potentially be difficult to implement if you don't have the right investment in place before deployment. It's also user-friendly with a lot of great out-of-the-box capabilities. There is some room for improvement in certain areas, but overall it's a good solution. 

I would rate this solution a seven out of 10.