Collibra Platform Reviews

Our use case is to manage master data inside of Governance.

The solution is deployed on cloud. We have around 10 data analysts using the solution.

The most valuable feature is the discovery process for the data catalog because we get it in a visual format as a way to understand and classify it. It's good to generate insights and get the context of the data.

When we are doing discovery for unstructured data sources, I would suggest a quality report of the data that would indicate what was unable to process.

The main issue is the data quality and that we can't control dealing with the real-world data. It's good to measure this and compare it between different data sources.

The Collibra products are very consolidated in the market. I think it's harder to analyze different domains of the data. Through Data Lineage, I think Collibra could add a relationship graphic analysis. They could add a feature that is a new way to explore the data.

I have used this solution for six months.

It's pretty stable. It hasn't suffered any outages so far.

I'm not sure if you can improve or optimize the performance to streamline it, but in terms of stability, I haven't had any issues.

We haven't scaled up, so I don't know if we will have any issues with this.

I would rate this solution 8 out of 10. 

The entirety of Data Intelligence is good, but I can't talk about all the products inside. I can't give it a 10, at least for the pieces of Collibra that I know.

There are many pieces of the platform, and I think everyone should at least test the Data Catalog and Data Privacy or deploy it and combine it. If we mix with other vendors that can deliver these things, it will be complex to get things done.

It's very tight with the Data Catalog and Data Lineage. It's more than just an integration and an API for your services.

We are using the product mainly for metadata management as well as some data governance practices such as roles and responsibilities set up. We're also using different workflows - mainly approval workflows or request access workflows where people can actually request access to data. We have use cases based on different teams, based on what they need. It's mainly the glossaries, such as business glossaries, data dictionaries, and report catalogs.

The product is becoming the source of truth for the different business terms, acronyms, measures, etc. At least, this is the goal. Also, I would say the report catalog where the people can go and see what reports there are and can request access to the data if they need to is great. 

The data lineage from the source up to the reporting tools has been very helpful. It's also been very beneficial to be able to run some impact analysis. The visualization property can visualize the overall picture to see how the different assets are connected. This is also very beneficial to our organization. Of course, then there's the social aspect. You can command or you can use different workflows. 

Basically, it's helped our organization in a myriad of ways.

You can tailor the solution to your needs. You can really create different office drives and different attributes or relations that you can customize for your needs, which is a great thing. 

The diagrams are really great due to the fact that there are validations. The search capabilities and the different filters are all great aspects.

It's a user-friendly tool, even for non-technical people. That was one of the reasons why we chose it. It has very good social adoption. There isn't much training needed.

The solution needs to be controlled. It can go sometimes out of hand.

The speed sometimes, especially now, since we have moved to the Collibra Cloud, has not been the best. The management of the speed of the tool is not that great. It's also partially impacted by the fact that we need to use a VPN and we have got a lot of security measures. Sometimes it's not working well together with everything else. That is the main pain point that we are having.

Occasionally we get little bugs that occur, however, this is typical.

We would like to have a data lineage feature. It's just like on a different module. That's already available, as well as some advanced connectors. 

From my perspective, I would like to see improvement in the dashboard creation, to make it easier to create a really nice dashboard, and to also be able to play with the user interface when it comes to those dashboards. 

We haven't used the solution much, however, we have used it within the last 18 months or so.

We do occasionally have bugs in the system.

Now, after we have moved to the Collibra Cloud, we have to do some re-indexing and some restarting. We are at the stage where we are getting to something of a normal state. Sometimes there are some issues, however, we hope that it's just temporary.

We need to scale it more and more, however, that's why also be moved to the cloud. We believe that it will be better in terms of scalability.

There are two types of users and two types of licensing. One group is able to alter the information. Then there are users that can see the content. We have about 500-600 people who have accessed the solution in the past three months.

I am not the one who actually deals with the support, however, I know that some people are dealing with them quite a lot. My understanding is that the quality of technical support depends on if you really emphasize the importance of the issue. Then they react quite well. You really have to make sure that you've set up the importance, the criticality, of that issue properly.

Previously, we had a tool called Samantha, which is quite a local product. It was purchased by Alteryx.

If I compare Samantha and Collibra, they are actually two different worlds. We are quite independent with Collibra and therefore, we can basically really create any kind of item by ourselves rather than using the other tool, Samantha. We were relying too heavily on developers previously. It wasn't ideal.

The initial setup was quite straightforward. I wasn't the one who was taking care of it from a technical point of view, however, if I remember correctly, my colleagues didn't have any problems with it. When it comes to the user interface and how to work everything, it was really straightforward. 

A great advantage is that Collibra has got Collibra University where you have a lot of materials and videos, and tutorials as to how to use Collibra. We also have the Collibra community and documentation where you can search for information. This is really great asset for us.

Now that we are on the cloud, maintenance in terms of updates, etc. will be handled by Collibra. We are developing our own connectors as well, and we'll need occasional maintenance for that.

We haven't specifically tried to measure any ROI. It's not something that I can accurately answer.

You pay for a one year license for the whole Collibra. Then, you have some modules which are paid separately, such as the data lineage or the privacy and security module and others or insights, so that you can access some metrics. Licensing is also based on what you pay for each alter-license. It means that, if you want someone to actually create content in Collibra, you need to have an alter license, which is quite costly.

The way it's done, it ensures that the people who actually use the solution are trained and they can correctly control the content, and how it's created and how it's governed, as opposed to having a free-for-all. It is a good model. That said, it can be costly.

We're just a customer.

We fought pretty hard to have Collibra as opposed to Axon from Informatica. For us, getting Collibra was crucial, and we're really enjoying working with it.

I'd advise people to start small and try to implement small pieces in a POC so you can gauge how it will work on a larger scale. It's important to really have a look at various use cases as well.

You really want to work to sell it to the final users so that it will have a heavier adoption rate.

I would rate the solution nine out of ten.

I don't use it as an individual. It's basically for my clients. I serve as a consultant for the tool. The typical use cases for the clients that we get is around metadata management and around building lineage. You can create a lineage by modifying out-of-the-box Collibra asset models.

While, for privacy reasons, I cannot share exact use cases, I can say that the solution helps smooth and streamline the processes of clients. 

The most valuable features of Collibra are the workflows and the data lineage capabilities. They help improve the client's existing processes. You can map those into workflows and those processes can directly be done on Collibra. Basically, what happens is, you directly script the metadata for the process that is happening.

I'm fairly new to the product, however, what I generally hear from my clients is that the requirement around having ways to ingest more metadata. Currently, with Collibra, they provide you a catalog platform, which helps you integrate or get metadata from a few commonly known platforms, like Tableau and IBM Db2, and Informatica. If they could bring them through, or if they could bring in more connectors to help us ingest metadata from other systems as well, that would be really helpful. That would reduce a lot of time and effort from our end.

If people had backward compatibility as well, that would be much better. I've also worked on other technologies, primarily Java, which is very, very much backward compatible. Any new implementation which they bring in does not impact your existing work to a heavy extent. It would be helpful if Collibra was similar.

I've been using this solution for the past two and a half to almost three years.

The stability as of now is quite good. We do get regular updates from the Collibra platform and that is good. In terms of performance, at the end of the day, it boils down to how your infrastructure is. However, we haven't really faced any issues with our clients.

If you have an on-premise setup, then the scalability is entirely in your hands it depends on the sizing. However, if you have a cloud-related Collibra setup then the scalability is pretty good. 

In terms of internal scalabilities, such as the different platforms we can bring on or onboard onto Collibra, it is good as of right now. However, if we have more connections or if you have leads to ingest data from these different sources, it could be better. That is an area where we can still see some improvement.

I'm more of a developer here, therefore, I've not really interacted with the Collibra support team. If a client needs help, we ask them to route it via their fortified product partners. We get a resolution that way. I haven't directly interacted with Collibra.

I was not involved in the initial setup as that is taken care of by the Collibra team.

We implement the solution for our clients according to their requirements. Collibra also does a lot of the implementation process as well.

I do not have visibility into the pricing of the product. It's not an aspect of the product I handle.

My overall IT experience is only for three years. I basically started working with Collibra. Therefore I have not really evaluated other solutions. I've never run a comparison with other market tools like Informatica or other ETL-based tools, for example.

If you know Collibra's history, the tool is fairly new to the market. It is maybe eight to 10 years old. Within the past three years, we've seen the Collibra platform, or the Collibra product, changing a lot and developing a lot. They've been incorporating a lot of user suggestions. I would say the DBA, the system we've learned, the product is still quite immature. However, it's developing. Earlier, they were using a few core APIs, which will now be deprecated in the newer version. Even though those are mapped to a newer functionality, it's an ever-changing thing. That does impact all your backend code and workflows. New users just need to be aware that it's still evolving.

Collibra generally, is trying to incorporate as many new solutions into its product. That sometimes comes at the cost of an existing solution being removed due to coaligned abilities which you have already kind of implemented with the clients. It's kind of a reimplementation on the newer versions for a newer component. It's something to be aware of.

From a client perspective, I rate it as a six out of ten. From a market perspective, I can rate it as a seven or eight. As much as I have heard that tool is comparatively unique and that lineage and the other capabilities like workflows that this brings to the table, compared to other products in the market, is kind of better. From a product perspective, I have to rate it as a six or a seven. And from a developer perspective, I'll rate it as a six. Overall, if I had to rate it on every aspect, I'd give it a seven out of ten.

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. 

We're a very large pharmaceutical organization so it's difficult to quantify exactly how many users are using Collibra.

Within our organization, there is a data governance team that we had set up. I am the person in charge of that team. While working on the data governance processes, we thought of leveraging Collibra for things like data dictionaries, developing data lineage, ensuring that business artifacts like KPI catalogs and board catalogs can be built within Collibra itself. 

This solution has done a lot for our organization and the trust amongst the data that we've been using has definitely improved. Earlier, these things were happening in silos, there were people who were doing manual documentation. Now, things are centrally available on Collibra, so it is more of a centralized platform. People are now able to track what is happening in the background of the data that they are using. Essentially, it has provided us with more trust and transparency — this is the real benefit that we've got out of Collibra.

Also, connecting the dots — things that used to be done in silos, now we have a centralized platform. Every team is aligned with what others are doing. It is not as if I am reporting a KPI, which has an "A" definition and somebody else is reporting a KPI with a "B" definition. When things are consolidated from a country level or a regional level and you're trying to present it to the leadership team, then there is a different picture to it. You're not using consistent calculations and definitions. This ability has been really effective for our organization.

It's a one-stop solution for all of our queries related to data that we are leveraging for our reporting. Pharma is totally dependent on what people are turning out as a report and what analysis or analytics they can derive out of it. From there, leadership accordingly makes a decision. It gives us more confidence in having a go-to platform that acts as a one-stop-shop solution for all of our queries.

Due to technological advancement and data becoming more critical for all reporting and analytics purposes, we are no longer restricted to primitive tools like Excel, etc. Earlier, we were leveraging these tools because we used to source data directly from data sources, but now, things have moved to the Azure platform and we have much more freedom in the cloud.

It's now really important for technical people to have some kind of lineage for these data sources because currently, we are not just leveraging data from the source and reporting it somewhere. We have thousands of reports with some transformation that occurs in between. Data is moving from one layer to another — all types, including raw, curated, and rich.

When our technical team works on it and our business demands new modifications, it becomes difficult for them to track that lineage and what impact it's going to have on the upstream and downstream system. This is one functionality of Collibra that we have leveraged extensively. 

We are in the process of migrating all our data sources towards the data lake — some has already been done and more is on the way. We want to connect all of our reports, which are either based on ClickView, Tableau, or PBA, directly to Collibra, as our data platform. If a business user wants to track down a KPI in a report to the rawest data from which we are sourcing it, there are a number of layers and transformations happening in between.

It is important for business users to track what is happening in the background. Are we leveraging the right thing? Are we applying the right kind of transformation or the right business-logic to arrive at a certain KPI? At the same time, the IT team needs to be able to know what kind of lineages there are. For example, If I make a change to one of these things, what impact will it have on the backend? This is one of the powerful functions of Collibra which we as an organization think is really useful — as an organization, we have been reaping the benefits thanks to this solution.

I am a business person — I am a team leader. My duty is to ensure that the data governance processes are set up; that's how I started to use Collibra. There are certain limitations I have observed in Collibra. With regards to our data lake, Collibra doesn't give us direct connectivity to the Azure Data Lake. We have to establish data lineages. We have to browse those files manually and then connect them via Collibra — that's how data dictionaries get published. Overall, it's quite a manual type of process which needs a lot of human intervention.

I've been hearing that tools like Talent are going to be available soon, which we hope to leverage in the near future. Talent is similar to other ETL or Informatica-type tools. It directly connects to the source system, captures all the transformation tools, and provides you with a spreadsheet that talks about data lineage, which can be fed into Collibra. If this functionality could be improved, it would be a great time-saving solution. It would require less effort and it would be a more automated kind of system, less dependent on human operation, which means that it would be less prone to errors as well.

We create and issue the management of workflows with Collibra. In regards to workflows, I find that they can be made very simple. For example, a request goes directly to the person who is in charge of that particular asset and some simpler workflows can be assigned to it. Recently, I find that the default process of issue management in Collibra is really complex — It wasn't really helpful to us.

I have been using Collibra Governance for one and a half years.

If deployed correctly and leveraged properly by the people, if the commercialization of the product within your organization, post-deployment, is good and you're able to transfer that value to people, then this solution definitely has huge power. In terms of data governance, as I mentioned, it can be a one-stop solution for all of your data governance needs. 

If commercialization, onboarding, and value from Collibra are conveyed properly to the teams, then definitely it's a powerful data governance tool.

No. Things were happening in silos. Everybody had their own way of doing data governance. There wasn't any connection or central platform to do that. Everybody was using their own method, platform, files, etc.

We have one person from our leadership team who has experience in data governance — 20 years of experience. Similarly, we had certain technical team members as well. The initial setup was a collaborative effort. Overall, I found the process to be a little complex. 

You actually need to get into a lot of theory to be able to understand the backend of Collibra and then be in a position to be able to implement it. Initially, it's a little complex but now that I've spent one and a half years working on it, I find it a little easier, but at the time of initiation, we found it to be a little complex.

Deployment took us roughly nine to ten months. 

Our data governance lead oversaw the initial deployment. In my team, there were around five team members who were supporting us through deployment. There were two technical members from the same organization that I worked for who were actually involved in the technical assessment. Then there were onshore business people, too. This was all new to our company — we just made decisions and then we started to go ahead with them. 

There was one expert from Collibra that our organization has partnered with because it was a new thing for us. That person actually acted as a guide and mentor, leading workshops and assessments — showing us what should go into Collibra. In a nutshell, these were all the people who were involved.

From a technical perspective, maintenance is required after deployment. We have a dedicated team who looks after this, we don't have to do anything. From an operation perspective, for the maintenance of the asset, you have to ensure that your information is real-time and updated on a regular basis. You cannot just feed this information once and then never look at it — in the data world, things keep on changing. You need to ensure that those dynamics are being catered to. From an operational perspective, yes, there are monthly processes in place that are there to ensure that whatever we have posted on Collibra is up to date and relevant.

From a technical perspective, I cannot contribute much because there is a dedicated team that makes all of the decisions. If we are upgrading Collibra, they are the ones who get the notification, they work with the team and then they agree on the next steps and then we just get notified that new features are going to be available. 

I was not involved in the licensing of this solution. 

We evaluated the pros and cons of another tool (I forget the name of it). From a forward-looking approach and long-term perspective, I think Collibra is far more powerful than the other tool.

Before you deploy or implement Collibra, just ensure that you have certain use cases that really qualify for leveraging Collibra. Assessment and evaluation are really important, first. Benefit analysis is the most important key.

What are the transformational changes that Collibra is going to bring? If it's going to improve your ROI by deploying it, then migrate over to it; just don't do it because everyone else is doing it — that's not a good enough reason. 

There are certain tools out there that can analyze data and generate reports with a few simple clicks. Collibra doesn't work like that until you have the ground knowledge of the metamodel — how the backend works and how your assets should be categorized. You cannot expect to directly deploy Collibra. You need certain experts in that area who do extensive research and understand the backend of Collibra, only then can you proceed with it. Once you are pro with it, it becomes much easier, but initially, it does require some research and hard work.

From what I have leveraged out of Collibra thus far, on a scale from one to ten, I would give it a rating of seven.

Our primary use case of this product is for metadata information for our technology assets. We also use it for all the governance dictionaries, and for minutes as well.

The solution is very useful for IT people but it's also helpful for those not literate or knowledgeable in IT. The sales department, for example, can track where the information is coming from, where the transformation is happening and where they can find a report for any specific asset. It's very important for them to have it handy, and I believe that for the people who need to know that information, it's very good.

The diagram showing the limits is absolutely magnificent. It shows an end-to-end business term or any asset going from end-to-end. From a visual perspective on the diagram, it's simply beautiful.

The workflows and the language they use needs to be improved. Programming the needs for every user on the workflows is a key improvement that is required. In addition, they haven't updated their training solution in a while. We need to implement a lot of things ourselves and they want us to move to the cloud but there are a lot of glitches in the system. There are three environments - stage, development and production. Often things work well in the first two stages and then when you get to production, they don't work. It happens a lot and their response is slow. 

I've been using this solution for 18 months. 

I would say that stability is around 85%-90%. It's very stable compared to other solutions on the market. 

Scalability is very good, excellent. 

Collibra provides one-on-one technical support, which gives access to a very knowledgeable person and their customer service is amazing. The only problem is that sometimes they don't know the answer so they have to check it out and get back to us. Sometimes you reach a dead end and that's the main problem of their system. We also now get in-house support.

We didn't switch from another solution, but we were using other solutions to control metadata. We used Infomatica for our transformation things. It wasn't like a governance tool. We also used Spark IS, an information solution, to harvest the data we needed.

The initial setup took a week because our systems are tricky due to security considerations. Deployment throughout the company took about six months, but that's an internal issue because of training implementation and that adds to the time. It's our main governance system so we had to move carefully. We already have 2,100 people using it. Operations uses it a lot and sales uses it for everything. 

For now, only 60% of our company is using it, so there's no ROI yet. 

Collibra started at a very reasonable price and then they increased the cost significantly by about 150% and almost lost us as a customer. It was something that the people from procurement and from finance ask whether the solution is really necessary.

At the time we also evaluated Unify, which became Boomi after it was purchased by Dell. That's an amazing tool as is Informatica. The issue there was that the price was too high. We went with Collibra because of the price and what it gives the end user.

Sometimes the technical support is messy but the system is great. It's a very good tool and I would suggest speaking directly with the technicians who develop the tool, rather than customer service. It's a great tool for a medium size company. if you're in a larger company, I would recommend implementing team by team. It's a tool that the end user needs to understand so if you implement it all at the one time, people will have difficulties and you won't have the support. 

I would rate this solution a seven out of 10. 

The primary use case is generally about IT people trying to manage their metadata to control what data their organization has and where it's going, as well as to manage data quality and integration. Ideally, that needs to be tied to their business outcome, but that's still quite a rare use of the product. I'm the president of our company and we are partners with Collibra.  

Collibra are very good at helping organizations get a handle on controlling data and the knowledge around where the data is, its type, etc. If you don't know something, you can't protect it, so they help with that.

Their user interface is much more business friendly than anybody else's. Also, their workflows, the rules and policies on workflows, are really strong. They're very good at that. I would also say that the roles and responsibilities, their way to manage people within that process is efficient. Their GDPR module is also pretty good. 

I think the connectivity with different applications could be improved so that they ingest metadata through different applications, through integration with applications. The integration with different metadata sources is not where it needs to be. The company strategy is also, honestly, infantile compared to a lot of companies. If they were to extend the GDPR, if they were to kind of anonymize that and make it more general so it could cover CCPA and a number of the other legislations around the world, that would probably be a good thing.

I've been using this solution for about six years. 

The stability is good but it's only as good as the processes within your company. 

The solution is scalable, it can handle large volumes of metadata.

The technical support is limited. It's high quality, but not high volume, meaning that they have some really good people, but not a ton of them. Nowadays, a lot of people are getting into tech, but they're not really experienced in the particular solutions they're dealing with. It's also potentially hard to find people for that area that are really good, because it requires different types of experience. They have to know the application, but they also have to understand how applications work, how data warehousing work, things like that. Nothing against young people, but when they've only been in the industry for a few years and don't necessarily have that experience, they may not be able to help as much as you might need.

The initial setup is pretty straightforward. 

I'd say that you need to understand what your business goals are around privacy and data, before implementing Collibra. The solution is not like an RSA Archer. They're not a security and risk application, they enable security and risks through management of metadata. They're a piece of the process, but they aren't the primary piece of that process. If somebody's looking at a security and risk application, I wouldn't necessarily say that this is the solution. They should look at data governance as part of the process of managing risk, but they shouldn't look at Collibra as primarily that type of application. If you're looking for a privacy and risk application you might want to look elsewhere, not because of quality issues but based on the full feature capabilities they'd be up against. I don't think Collibra can compete on those fronts. 

I would rate this solution an eight out of 10.