Collibra Governance Reviews

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. 

We use the solution to organize data. The IT team has access to the data and knows where it is stored, but when it comes to legal compliances and various regulations, the business itself does not have control over where the data is stored and how it is stored. Typically, the business wants to have control over where the data is stored, the various data classifications, and data sensitivity. That is the main reason why we use Collibra Governance.

I appreciate the range of features it has. Based on the reviews of some of the other tools we use, we find that the other tools lack in certain areas. If I had to choose a comprehensive tool across all the fields of data governance, I would opt for Collibra Governance.

The most valuable feature is the Technical Lineage. The fact that you can trace the auditability of a particular field or attribute across various systems is very useful.

There are a few things that need improvement. From a usability perspective, customers usually find some areas of the solution a bit complex. It takes a long time for the customers to get used to the UI and the interface. Another thing that the customers complain about when they opt for Collibra is the pricing. There are fees for additional features which mess with the customers' overall budgets.

I've been using Collibra Governance for about two and a half years.

It is a very stable solution. I would give it a nine out of ten. It works very well compared to other solutions on the market.

The scalability of the solution is good. I give it an eight out of ten.

The response time of technical support is typically high.

Neutral

Nowadays, most customers are looking into Microsoft Stack, so we use Microsoft Purview as well, although Calibra Governance is our preferred choice since it's much more stable than Purview.

Up until now, Collibra Governance has been the market leader and is always the first one to add new features. Purview tries to bring out a lot of features as fast as possible, but those features are not very stable and have a lot of bugs. Purview has the upper hand when it comes to the usability of the app system. It is easier for customers to understand the feature list while using Purview. For example, after using both solutions for a few weeks, they usually have a better grasp of Purview than Callibra Governance.

Since it is a SaaS platform in a way, the solution is deployed on Collibra cloud. The deployment is pretty straightforward since Collibra deploys it on its own. It takes about a week to get the core of the system up and running. After, we configure it to fit the specific needs.

On a scale from one to ten, the simplicity of the setup would be an eight.

Collibra Governance's pricing is based on its features. You get what you pay for. There are other solutions that are cost-effective but lower quality. With Collibra, you get a fair-value product if you pay a bit more.

I would not recommend using the Big Bang approach with Collibra Governance. You should understand the bigger picture of what you want to do. Start off with a few systems and four small modules. Get feedback from the business and then continuously evolve it. It is better to have the implementation spread out over a one-year period than have it crammed down within three to six months while trying to implement everything at once.

I would say that Collibra Governance is suitable for small to medium businesses. 

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

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.

Collibra Governance is mainly used as a one-stop solution for data discovery.

Using Collibra Governance means that we know the end to the life cycle of data across the team, which provides our data science and analytics team with sample data they can use to make decisions on what to do next.

Collibra Governance's most valuable features are data lineage and stewardships.

There are a lot of gaps in Collibra's support and documentation. In the next release, I would like Collibra Governance to include better integration with data ecosystem tools.

I've been using Collibra Governance for approximately a year.

Collibra Governance is stable with limited data sizes, but with bigger data sizes, you need to invest a lot in the job servers, which becomes a very costly operation.

Collibra Governance isn't that scalable.

It's very difficult to get support from Collibra.

Neutral

Previously, we used Apache Atlas and switched because it had very limited features.

The initial setup was very difficult - if you're looking at a high-availability or a production scale setup, you need to be technically sound. I would rate the ease of the setup process as two out of five. Deployment took around six months.

We used an in-house team.

Collibra Governance helps our organization, but getting a GMV or dollar value out of it is tough. I would rate its ROI as two or three out of five.

Collibra Governance is expensive - I would rate its pricing as one out of five. There are also additional costs for everything except the basic setup.

We evaluated Alation and OvalEdge.

Before implementing Collibra Governance, go through the tool very thoroughly because doing a POC or MVP is fine, but when you're looking at a production-scale deployment, it's very complicated. So explore other tools before jumping in with Collibra. I would rate Collibra Governance as six out of ten.

There is a master glossary which includes all of our business fields. The fields are related to particular lines of business such as account numbers. We then build business rules around these fields and complete data integrity checks. 

We plan to increase our usage of this solution over time. We will have to use other functionality within this application as it is currently limited. We currently have 12 team members using this solution. 

This solution is user friendly and offers multiple functionalities. It operates like a kind of a repository that allows you to find anything about a particular data set or field.

This solution could be improved with the the addition of process diagrams to help the many users of the platform understand all the fields.

We have used this solution for six months. 

This is a stable solution. 

The initial setup was straightforward. It was made easier due to the access we had to the Collibra team. The deployment took three months and involved three to four people.

I would rate this solution an eight out of ten. 

Our use cases include connecting a lot of legacy data systems to our logical components. For example, if somebody has a question that they post to us and say, "Tell me everywhere in our organization where we have a policy stored?" the primary use case is to logically define what a policy is, and then we use Collibra to tie that logical construct to a technical implementation. We may have six or eight, however many, different admin systems. We bring in the schemas of the way that those systems look, and then how a policy exists in this database and this table and this column, for example, in that legacy system. 

The second use case that we implement is the ability to track the provenance or the lineage as to how something changes over time. For example, if we bring data in from a legacy system and we use some tool set (e.g. Azure Data Factory) to extract the data into a Hadoop data lake, and then perform some transformations on it, we want to be able to track it; "It came from the source system here, and this field got changed to this name, and we applied this transformation on this field and it eventually shows up on this report here."

We use it to track where a policy exists and also how it got there: it exists on this report and here's how it got on that report, here are all the steps that it took getting through to that particular report from the actual source system itself. Because quite often what we're finding is that our business users will get a report and they'll say, "I think your report's wrong. How did you get that value on that report?" That provenance or lineage is what helps answer those questions.

We have data stewards who are the resources that if somebody proposes a new logical asset based on what they think the customer means, these data stewards are the ones that would get together and look at what's being proposed and make sure it works across all of our business units for a generic implementation, or create business unit specific terms if required. They're the ones that say a particular system or term or logical construct is ready for consumption by end users.

Another group we have is the end users. We try to have people use Collibra by asking, "Don't tell me what system you want to get access to, tell me what you're looking for in business terms/constructs." In our example, it would be the question, "Tell me about all the policies in our system." They would go to Collibra and "shop" for that data and pick a policy and put it into the shopping cart basket that Collibra provides as part of their interface. Then they would submit that request for approval/access to the underlying data.

We also have data stewards who approve the use of new/updated business terminology and end users who are looking for their data to make business decisions. We also have some power users who are the resources who are setting the direction for the application of where we want to go with it, (e.g. new workflows or new functionality within Collibra).

For us, the Collibra application is an on-premise installation (although we use IaaS VMs to host it on cloud); it is not their SaaS implementation.

One of the biggest questions that we had was we didn't know what to with the our tons of legacy systems. The company I work for is a fairly old company, it's over 120 years old within the insurance industry. There are lots of systems that have been around for upwards of say 40 or 50 years, so we're trying to consolidate and bring those down to target, to go from say 15 systems down to three. But not knowing what's in those other systems makes it difficult to do that rationalization. It's enabled us to first understand what we have and then to figure out how we get down to the target state architecture with a reduced number of target systems.

Out of box ingestions of technical metadata as well as ease of use for setting up new business metadata for users to represent their business terms

Collibra is very good at talking to modern database systems such as a normal RDBMS (e.g.DB2, SQL server or Oracle). Where it isn't great is with older technologies that you'll typically find in finance or insurance industries (e.g. VSAM or ISAM, or those types of older technologies). It just doesn't connect with them very easily. They do provide an ability to use a separate product called MuleSoft, which they used to license (as a bundle) up until last year until Salesforce bought MuleSoft, and that division is happening in 2021. With this 'bolt-on', you could go and get that data, but you had to write that code and maintain it yourself. It wasn't an out-of-box (OOB) feature, which is what we really liked from the Collibra offering. Our only way to access these older technologies was to create a MuleSoft flow, maintain, and deploy it. This leaves us with technical debt which will need to continually be maintained. In fact, we built all our custom Mulesoft flows using Mule 3.x and will soon be pushed to upgrade to Mule 4.x. This will not be a simple upgrade and will likely result in additional cost to bring in consulting resources more familiar with the technology. Since we do have a lot of older legacy systems, things that aren't greenfield, if you will, it adds a lot more overhead than what we were originally led to believe when we originally purchased the product.

We're not that deep into the Collibra product yet because it's only been a couple of years. We do like their ability to automate the workflows, such that, for example, if somebody comes in to say, "I want to request access to this data," you can build your own workflows to automate the approval process. There are some that are out-of-box, I think they could go a little bit further with some of their out-of-box workflows instead of having to create a workflow manually, get somebody to code it, and implement it. I think they could offer a bit more in that respect.

The second item that I think they could do better at is to have other products, or have things where they have a set of taxonomy per industry that says, "Here's what a policy is. Here's what a customer is," that kind of thing. They don't implement that out-of-box in Collibra, you have to do that yourself, whereas other products bring that to the table. Informatica, I believe, has their own insurance industry or industry specific taxonomy that would come with the product.

It makes adding the new logical constructs to Collibra a more manual workup to take care of. The classification becomes more manual because you don't get that out-of-box to say, "Hey, I recognize that that's a policy, because I know that about that and the taxonomy." You have to manually make that connection.

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

Collibra Governance's stability is quite good. It doesn't take a lot of maintenance to deal with it, it just runs. It doesn't cause a ton of issues and it doesn't require a lot of upgrades (we usually upgrade once/year). In the couple of years we've done, I think, two upgrades on it. The one thing that we're disappointed with is that 5.7.7 is their last on-premise implementation that you can do. You have to go to a SaaS offering by Collibra, after it's just been released end of November.

Being the industry that we're in, we're very risk averse, so our use of SaaS offerings isn't that large, and our company isn't prepared to put a lot into the cloud, especially when it comes to personally identifiable information (PII). We're very nervous about that. With that limitation, we would have preferred that Collibra would have extended the timeline of their on-premise offerings beyond this.

I don't have a lot to say about scalability because we haven't had the system pushed that hard. I think we started out with an initial 25 users, and we might have a couple of hundred now. We haven't had any complaints from end users in terms of not returning information in a timely fashion or the system isn't working as good as I would expect. We haven't had enough experience to comment on that. Our current installation is approximately 175 users with about 15-25 concurrent usage. We went with the vendor recommended VM sizings although we did put all services for Collibra on one VM (except JobServer and Connect as recommended). For larger implementations, Collibra will recommend that you split out services (e.g. DGC, Search, Repository) onto separate VMs to allow performance tuning but our implementation hasn't come to that yet. 

In my experience technical support is pretty good. They're fairly responsive. If I enter a case, I'll usually hear back either later that day, so maybe a five or an eight hour turnaround, or definitely within two business days. I find if it's beyond a basic question, it takes a little bit to get it pushed to another level, to their second level support. Sometimes it takes a while for them to say, "I don't know the answer, now I'll ask second level to assist me with that." Getting past the first level, like most vendors, is a bit difficult because they want the call answered there, but it is not unreasonable in any respect

We previously used the IBM Information Governance Catalog, IGC. We had used that as part of the whole suite (e.g. Information Analyzer, InfoSphere, etc.). We went out and did vendor assessments and had demos from the vendors come in to set a strategic direction. We determined what our strategic platform was going to be in terms of a data catalog. IGC just quite frankly wasn't anywhere in the realm of what Collibra could offer in comparison. It felt like comparing Windows 3.1 to a Windows 95 interface. Collibra is known as the 'Cadillac' offering from a user perspective. There are some things that it is not as technically good for, such as Alation is quite good at crowdsourcing or crowd approval approach. But in our opinion, Collibra offered the most features from one product overall. It's a bit on the pricier end, but when we looked at the Gartner Quadrants and Forrester Waves, it was always consistently either one or two up there with, say, Informatica or other tool sets like that.

That's actually what my role is, as the technical lead. I'm the one who did the installation, and is responsible for patching and that kind of stuff. I'm not an end-user of it as much, I don't go into it every day to do workflows or create the data, but if there's a technical request or something, that's where I would get engaged.

The initial setup is fairly straightforward. I found the Collibra pre-sales and their support pretty helpful. They got back to you in a timely manner to be able to do the setup. It wasn't a difficult implementation by any stretch. It was about what I expected in terms of the timeline that they had provided for us and what we needed to do.

In terms of the actual installation process, it was maybe a couple of days start to finish once the hardware and everything was there. Then you continue to do your configuration as time goes on to connect to different systems and whatnot.

Most of that was put forth on advice from the vendors. We said here's the usage count that we plan to have, here's how many systems we're targeting originally. We looked to Collibra to give us the recommendation as to VM sizing and implementing. We didn't really create our own, we used theirs and customized it slightly for our environments, but it was mostly a vendor-provided plan of implementation.

We used in-house resources to build/deploy the IaaS environment and complete the installation of Collibra. We have used 3rd party firms to develop custom Mulesoft flows for connecting legacy systems and custom workflows

We've had good ROI, because when we look at the amount of time invested, it's not necessarily dollars out the door; it's more about manual work avoidance. Instead of having somebody have to manually enter all of these different systems and characteristics, we can do integrations between our source systems and Collibra to get that automatically and refresh it. As people make changes to source systems as time goes on, we can automatically bring those into Collibra. It has allowed us to do one of the projects that we had on the books for this year, which was to understand what our critical systems were. Not only for disaster recovery, but where is our most important data about our customers? Where does that reside and how can we take that data and join it to understand more about our customers and their needs?

In our scenario, we have different business units with the same customer, but we can't make that realization that it's the same customer in different business units because of the way the systems grew separately over the years. Collibra is the one that's allowing us to tie that together. It opens up additional revenue streams with the ability to say, "Hey, I noticed you bought a product for this business unit from us. Did you know we also sell this product for this other business unit?" It allows us that cross-selling opportunity or upselling if you will (aka Revenue generation). That's a bit difficult to articulate or quantify in hard dollars, because there are so many steps going from a lead all the way to a sale. But we certainly believe that the information that Collibra has been able to provide us has helped or augmented our revenue generation streams. In a way it is a sales enablement tool.

In terms of pricing, it's not bad. You pay more money for the author licenses, which is where you do most of your entry and whatnot. Whereas consumers are basically viewing information and using the tool to say, "Hey, I want to look at this data." I think what we would like to get to eventually might be an enterprise license, rather than having to say, "I'm going to pay for 50 authors or 100 authors." At some point in the future, I could see us wanting an enterprise license.

They may offer that now, but it wasn't at a price that was palatable for our company at this point. Plus, we needed a few years to get uptake in it to justify going to that high level. It's just more money licensing wise, but not unrealistic, in my opinion. The money is well spent for the product and the services we're getting.

We just found that IGC was way behind the times. IBM had not really put any money into their product, it didn't connect with any of the systems that we wanted to do. It simply just didn't fill our needs.

We did look at the Informatica product and we did look at Alation.

I think what we found with Alation is that it was good. The user interface was impeccable, but it was not what we would consider the whole package. It was very good at the catalog portion, but in terms of interconnectivity with different systems, it did not have workflow, which was a key characteristic that we were looking for. Alation was a fairly new company. It was only maybe three or four years old at the time when we looked. There was concern about the staying power for that particular vendor. Not that their product wasn't good, it just wasn't as full a product as we would have had with Collibra but built on something for workflow, which we weren't interested in. We were looking for one product to do that.

The Informatica offering was quite good as well, but in our investigations and interviews with other companies in our industry, Informatica is quite a complex product to get up and running and to maintain. It's not cheap either, but when we looked at what it would take to care and feed our maintenance on the Informatica side of the house, in comparison to what we could do with Collibra, we chose Collibra.

Everything seems to be going the route of software as a service these days. It does take away somewhat your ability to customize like you want. Some products allow you to do that better with their SaaS offering than others. I would say that the data catalog space changes quite rapidly. When we did our investigation a couple of years ago, Alation hadn't been in business that long, they've continued to grow and maybe their offering has become better. Just because we chose something two or three years ago, doesn't mean that we shouldn't re-evaluate that in another couple of years to say, "Is this still the strategic product for us?"

There tends to be a lot of vertical integration going on. We once thought, "Well, let's just buy IBM because everything works with IBM." That doesn't seem to work any more. There seems to be a lot of best of the breed. But when you do that, there can be a lot of interoperability there that just doesn't work out. That people who like the IBM's of the world say, "We'll just buy our product because everything integrates." It truly doesn't in our experience.

You have to do your homework and definitely interview other customers to understand their experience for what is good and bad, because of course, sales isn't going to tell you that. But do your homework and make sure that you're talking to people who have not only installed the system, but have been able to use it for a few years, to see what's good about it, what's bad, and what they might have done differently. We talked to a number of different customers in the insurance field, in Canada, the U.S. and in Europe, and learned different things that we would have never considered on our criteria had we not talked to them.

On a scale of one to ten, I would peg it at a seven and a half, eight. I would put it higher, only except it doesn't connect as well to our legacy systems without additional programming and a separate tool, which they used to license as the whole product, but when MuleSoft got bought out by Salesforce, that business relationship was severed. Now we have to buy that MuleSoft product separately from Collibra. Now we have a data governance product that used to include MuleSoft (but does not now,) and now we have to deal with a second vendor to get that. It was nice when it was all one product. If they're going to say, "Use MuleSoft to get at your legacy systems," fine, sell me that product. But they won't do that anymore because Salesforce owns it.

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.

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.