I am a user who has worked at companies that use Collibra Platform as their data catalog and data intelligence platform tool. My first company, MetLife, used Collibra Platform, but I wouldn't know where they purchased it from because I joined after the implementation. Then I worked at HCL Tech, and one of our clients, Genmab, a pharmaceutical company, also used Collibra Platform. I was onboarded onto that project after the licensing and purchase were completed.

I worked at MetLife, which is an insurance company with different lines of businesses including US business, EMEA business, and LATAM. Based on the different geographies and lines of businesses, we needed to ingest the metadata of insurance products. Insurance, as part of the financial services industry, is highly regulated and must comply with regulations such as GDPR, HIPAA, and BCBS 239. Many insurance companies have faced heavy fines when they failed to comply with regulations, experienced customer data leaks, or had privacy breaches. Having data governed became critically important.

The main purpose of data governance in any industry is to have a single source of truth. For example, at PeerSpot, if you ask what a customer means, one person may have a specific definition while someone else may have a different definition. However, as an enterprise, you would want to define what a customer is, establish which attributes a customer should have such as customer ID, the date the customer was onboarded, and the revenue generated from that customer. Data governance ensures that every organization has a single source of truth and users have a common vocabulary.

The main challenge organizations face today is that business and IT are often at odds with each other. Business uses the data while IT generates it, leading to constant debates about ownership, control, and governance. My role as a data governance consultant was to build a bridge between the business and technical folks, and between business stakeholders and IT staff. We achieved this by leveraging Collibra Platform.

We started by creating the community structure. Community structure means organizing the metadata based on lines of business or geography. We created communities based on the geography and line of business. For the different communities we built, I worked closely with the US business data governance council, and most of our work was for the US business. Within the US business, there were many sub-lines of businesses, each of which had a business glossary. A business glossary is a container that contains all the business terms used in an organization. Every business term would have a definition, indicate which column it is stored in, and describe what business rule governs the business term.

Next, we ingested the technical metadata, which is called a physical data dictionary. Technical metadata includes schemas, tables, and columns. Collibra Platform has a unique functionality called Edge. Edge extracts metadata and registers any source such as databases stored in SQL, Oracle, Snowflake, and Fabric, which are all different sources we worked with. Collibra Platform has a tool using Edge, and the benefit is that the Linux servers are stored on your organization's server. For example, at MetLife, Collibra Platform's Edge servers would be stored on our MetLife cloud only, not externally. The organization is assured that their data is safe. Using Edge, we extracted the technical metadata of schemas, tables, and columns.

We created the business glossary and the physical data dictionary, then ingested the business rules and the data quality rules. Finally, we created a mapping specification using field mapping to create a lineage. A lineage is something which every stakeholder looks for and represents the flow of data or metadata from different sources to targets. In a typical scenario, metadata starts from a system of record or SOR, flows to a raw data zone or RDZ, then to a curated data zone or CDZ, and finally to a distribution data zone or TDZ. These are four different layers, and some organizations use a Medallion structure with gold, silver, and bronze levels. A lineage gives users a visual sight of where the metadata is coming from and where it is going.

Lineage helps with impact analysis. If an organization experiences a security breach and does not have Collibra Platform or data governance in place, they will be wondering where the data can be impacted and what customer data could be leaked, requiring reactive analysis. However, if lineage is already established, when a bug or ransomware hits systems, we already have lineage in place and can mitigate the downstream systems so that before data reaches them, we can pause dashboards or disconnect connections. We can understand the impact as soon as an incident occurs, allowing us to be proactive rather than reactive. This is why lineage is so critical to have in place beforehand.

For each of my different customers within MetLife, including those working on different insurance products such as long-term disability, short-term disability, and accident and health insurance, my role was to create the business glossary, the physical data dictionary, the business rules, the data quality rules, and ultimately the lineage.

The main purpose of using any data governance tool depends on why a business wants to do data governance. Some businesses may pursue data governance due to regulatory reporting requirements such as GDPR, HIPAA, and BCBS 239, while others may want to achieve operational efficiency. However, for the stakeholders I have worked with, they were looking for improved data trust and consistency.

Before Collibra Platform, insurance had different departments and teams such as claims, underwriting, actuarial, and finance departments. Since they did not have Collibra Platform in place, for the same terms such as loss ratio or premium, every department had a different definition. However, by implementing Collibra Platform, we had a single governed source of business definitions. That eliminated any conflicting numbers in the reports. The tensions between business and IT existed partly because of inconsistent definitions. By having Collibra Platform and business glossaries in place, it reduced the back and forth between the business and IT teams and increased confidence in the reporting for regulatory purposes.

We are audited every year at MetLife by the big four companies such as Deloitte and KPMG. Insurance companies have to go through many different kinds of audits each year. There is significant regulatory scrutiny, but since we had Collibra Platform beforehand, we had clearly documented data ownership and stewardship even before the audits were in place. For example, if there is a source system for long-term disability using a Snowflake source, sometimes the business does not know who owns it. At the time of reporting, everybody wants to put the blame on somebody else, which indicates a lack of ownership. An important part of data governance is to define roles and responsibilities beforehand. If Irina is responsible for a particular source system, then it is her responsibility to ensure that all business terms are consistent. By doing that beforehand, we had clearly defined who were the data owners and who were the stewards. We also had end-to-end lineage in place, from the source to the targets, which helped in regulatory reporting.

Auditors often ask for evidence in audits and want to see definitions, controls, and data flows. Since we had that beforehand, our teams spent almost 30 to 40% less time responding to audits and regulatory queries. Earlier, they would spend days and weeks preparing these reports and presentations, but almost 30 to 40% of time was saved by having Collibra Platform in place.

Another benefit is having a central single source of truth. The goal of any tool such as Collibra Platform is that any user across the organization can search for a term. MetLife is in many countries across the world, and any employee should be able to search for what a party identifier is, what accident and health insurance means, or what long-term disability is. If we did not have a central repository such as Collibra Platform, they would have to ask the most senior person they knew, who would then have to ask someone in the states. It would be difficult to find the right person who knows where the data is located, who owns it, and what its meaning and definition are. By having Collibra Platform, we have a central repository which allows users to discover and find curated best quality data beforehand.

Before Collibra Platform and after Collibra Platform, users saved at least two to three hours per week on average. Over a week, this may seem minimal, but translated across 50 weeks, that is almost 100 hours saved per employee per annum. When multiplied across an organization with tens of thousands of employees, this represents significant savings in hours per week. These benefits include saving time, being ready for audits, and having a single trustworthy central repository.

Collibra Platform's Edge capability is a very strong capability that allows us to extract metadata. The benefit of Edge is that it even does classification for us. For example, if there is a column which contains social security numbers, Collibra Platform will identify that this column appears to have social security numbers and will mask those columns automatically. It will suggest this to me, and then I have the opportunity to either approve or reject the suggestion. Ultimately, that is in the hand of us users. The extraction and classification features are very, very strong.

Collibra Platform also has very good mapping specification capabilities. As I mentioned, lineage is important, and Collibra Platform also has automated lineage. For example, if you have a source system in Oracle and your target is in SQL, if you scan these systems, Collibra Platform is capable of automatically identifying the relationship between the source and target and fetches the automated lineage as well. That is a very good feature.

The visual user interface is very helpful. I have worked with other data governance tools as well, and I found Collibra Platform to be one of the best tools because end users should have an easy time navigating through the metadata. When you search any term in the search bar at the top, such as risk or loss ratio, it gives you a list of search results. At the same time, on the left hand side, it gives you a filter panel. You can filter whether you are looking for a column or a table, a business term, or a data quality rule. You can filter by the kind of asset you are looking for, or even filter by line of business to see if you are looking for something specific to the US business or the Australia business. The search interface is very helpful.

The workflows are also very strong capabilities in Collibra Platform.

A separate team did the setup for this tool and was involved in setting it up. When they were doing the setup, it was a significant upfront investment in terms of the configuration, modeling, and governance design because the team first had to define the domains, the assets, and the roles. That takes time, and in the insurance environment where we had many legacy systems, this increased the setup effort. It would be helpful if Collibra Platform could have industry specific starter templates that could accelerate adoption.

As we ingested more and more metadata, sometimes the catalog searches became slower by a fraction of a second because there was more metadata in the tool. After inserting millions of rows into the physical data dictionaries, the catalog searches could become a little bit slower. Having some better performance optimization might help with this minor issue.

I have used Collibra Platform for around four years.

Collibra Platform is pretty stable and is a reliable tool, and I would use it again.

Collibra Platform is a scalable tool and is very scalable. It is very critical for a data governance tool to be stable and scalable because we start with critical data sets in one line of business, but ultimately, we want to cover the enterprise and all lines of businesses. Unless the tool is strong in its capabilities in terms of scalability, no organization would be able to implement data governance at large. Scalability is critical, and I think Collibra Platform is a suitable tool for scaling.

Collibra Platform has a Collibra University, and the Collibra Platform team helped us gain access to it. They also guided me to complete two learning paths, the Collibra Data Steward and the Collibra Solution Architect. The team has been very helpful in guiding us in terms of training and documentation. On the Collibra Learning Center, if you go on help, there is extensive documentation available. In terms of customer support, we would connect with them once a month to discuss any kinds of queries. Whenever we did have challenges, they were available, and we were satisfied with their support.

Collibra Platform is a premium tool and an enterprise grade premium tool, but I think it is justified because the only other tool more expensive than this is the Informatica suite, which includes Informatica Cloud Data Governance, Informatica EDC, and Axon. I think it is worth it because the features present in Collibra Platform are extensive. Sometimes companies consider Microsoft Purview because they get Purview for free with the Microsoft suite if they have an E5 license or something similar. However, they do not realize that with the free tool, they do not have as many capabilities as Collibra Platform has. I think it justifies the upfront investment, and we have seen good ROI in terms of the search time saved by our business users and the time saved in preparing for audits. We have seen good ROI in our business.

I use the Collibra Lineage visualization features. The solution helps me understand data flows effectively. Collibra Lineage impacts my data analysis by helping to identify where data is used, making it significantly useful. The solution facilitates compliance by defining where sensitive data is located, helping to trace sensitive data.

One of the best features of Collibra Lineage is that it provides an end-to-end perspective of where data is used in the enterprise.

The positive benefit from using Collibra Lineage is that it provides an end-to-end perspective of data usage in the organization.

There is room for improvement in Collibra Lineage as it could incorporate automation features which would allow it to find data lineage across a data stack independently.

I have been working with Collibra Lineage for approximately four or five years.

I don't have much experience with Collibra Lineage, so I cannot comment on whether it is straightforward in terms of installation or if there are challenges when implementing.

I personally don't participate in the installation of Collibra Lineage.

Collibra Lineage is a stable solution.

Collibra Lineage is scalable.

I did not communicate with their support for Collibra Lineage, so I would not know if they were helpful or responsive.

When it comes to implementing Collibra Lineage, three or four engineers are involved.

Using Collibra Lineage is beneficial in terms of finance.

The metrics I track to measure efficiency improvement after using Collibra Lineage include integration and analytics. The time spent to identify data usage is reduced significantly.

Because I have not used Collibra Lineage extensively, I will not comment on future updates, improvements, or features I would like to see, such as more customization, more AI features, a refreshed interface, or a lower price. I rate Collibra Lineage 8 out of 10.

Implementing Collibra Governance is definitely something that all organizations having data need. It's the kind of tool especially for large enterprises where data is distributed across multiple data stacks, bringing rigor for both data management and data engineering.

We use Collibra Governance for metadata management and access restrictions, as well as lineage.

We use Collibra's Data Stewardship features. In terms of role assignment and accountability, there are three levels of users: people who are data users, then there are data stewards, who are users of data enforcing compliance and rigor around data, and finally, the data governor who sets up policies and principles.

We have utilized Collibra's Business Glossary. It is good for reference of the data, understanding what the data is about, which helps maintain data accuracy.

Collibra's integration capabilities benefit our organization, although compared to the rest of the market, it is a bit cumbersome, but it's acceptable.

My experience with Collibra's collaboration tools in improving data literacy has been quite good. I think it is one of the best for helping people understand and discuss certain data sets and manage workflows.

In future updates, I would like to see more AI-based capability in Collibra Governance, wherein the data definitions can be auto-generated and lineage can be tracked down easier.

I've been working with it for probably 12 years.

The installation process is quite straightforward, but for it to be adapted by the organization presents challenges based on the organization, so it's not a technical challenge.

For a basic installation, I spend just a few weeks, probably about two weeks on setup and configuration.

Three to four people from my side usually take part in the implementation.

There are some benefits in the long run in terms of return on investment. While there are no direct cost reductions, there is significant indirect cost reduction. If I consider putting data governance in place without a tool like this, it's difficult, resulting in a significant cost improvement. If something else can be used instead and it's more expensive, that is a consideration.

Regarding licensing, I find it is one of the more expensive options, so it is not particularly affordable.

The interface is very good, with no complaints.

I do work with other vendors as well. Some other vendors I work with include Informatica, Atlan, and Suchi.

On a scale of 1-10, I rate Collibra Governance a 9.

We have a data platform and we use Collibra Catalog as enterprise governance tools. We are using Collibra Catalog for basic functionality.

It has various features such as cataloging data products and data sets, and it also has a marketplace and edge connectors to scan metadata. All these are various features, and the data quality aspects are there as well.

Discoverability is one of the key things we are always looking into.

Lineage is also available, including both technical and metadata lineage.

One of the very key drawbacks is that automation for access provisioning is not available. If I discover a data set or data product in the marketplace and want to access the data, this feature doesn't exist at all.

This is the biggest problem because without access automation enabled, users cannot get access to the underlying data.

We have been using it for 4 and 1/2 years now.

Deployment issues exist; every time we do a deployment, it erases the data in its previous versions. We have highlighted this to Collibra Catalog and have raised a ticket. They are working on it.

We are not satisfied as it is not yet completed. We raised this issue a year ago, but there have not been any results yet.

Response time is the main issue.

The solution is scalable.

We have multiple cataloging systems similar to Collibra Catalog.

Pricing is not under my purview as I am an architect. The platform team handles the licensing aspects.

The comparison shows that each tool has its own pros and cons.

Gartner identifies Collibra Catalog as the leader, which aligns with our observations.

I have read reports about Collibra Governance and Microsoft Purview on the website. We are currently using Collibra Catalog. We also use Tableau. I work as a Collibra Catalog architect. The tech support rating is six out of ten. Overall, I rate this solution 8 out of 10.

I have been working with Collibra Lineage for more than five years now, overall almost five years. I am using the product myself for molecular consultants and resellers at a consulting firm.

The best features of Collibra Lineage are quite user-friendly, and business users can use it much better than other catalog tools such as Talend or challenges according to my team. The traceability diagrams are very complicated and not user-friendly at all.

The automatic data flow mapping is effective; some of the integrations pose issues in terms of the configuration of those data sources, but it works fine. Even transformation platforms such as DVD work really well.

The integration with other Collibra Lineage products is valuable in our data governance initiatives. I have worked on many migration projects where organizations are moving away from other catalogs such as Talend or Informatica Axon and Informatica EDC to Collibra Lineage. I have worked on projects where we are creating the catalog from scratch on both fronts.

The configuration issues I face include troubleshooting that is not very helpful. I keep struggling with that and usually have to go to the Citizen data platform and the marketplace to get the answers I am looking for.

The controlled logs and documentation need improvement, particularly regarding how to access class features that they do not control, and documentation in terms of customization and UI customization. Dashboarding needs significant improvement as the widgets are not very clear or usable, and there is not much documentation around it.

To make Collibra Lineage better, additional features should be added to help technical users. They have improved significantly in terms of university courses in the last five years, but aspects such as AI governance and data notebook are not being promoted adequately. Data notebook is a very good feature, but there is a mismatch in the courses' speed and how quickly they are giving people the ability to learn about it.

I have been working with Collibra Lineage for more than five years now.

The implementation becomes more complicated, especially in terms of integration if there is no Collibra Lineage native connector. If you have to build gateways using the APIs or communicate with the APIs, it becomes significantly more complicated.

I would rate their technical support a seven or eight, as it depends on the payment tier. If you have paid for support, they respond to every email, and you have a personal account manager who takes care of all issues. If you just purchased a license without a support system, it is hard to get a decent reply on tickets, but this is true for most other catalog tools as well.

I usually recommend products such as Purview instead of Collibra Lineage, which is a significant downgrade from Collibra Lineage in terms of experience and key features. I have seen people moving to in-house catalog tools as well.

The product is definitely expensive. I have seen many customers moving away from Collibra Lineage after using it for a couple of years because the cost-benefit analysis does not give them a favorable report. They are paying too much for features they are not able to utilize.

The pricing presents both advantages and challenges. Many clients do not anticipate the effort required to develop a catalog and fully utilize it for data consumption. When considering the time and effort required to build a catalog and utilize it effectively, combined with the prices, it often does not make financial sense.

I usually recommend products such as Purview instead of Collibra Lineage, which is a significant downgrade from Collibra Lineage in terms of experience and key features. I have seen people moving to in-house catalog tools as well.

I would still recommend Collibra Lineage to others, as I am a champion. I am a two-time Ranger certified person, and I speak about Collibra Lineage in a positive light when I get the chance. I rate this solution 8 out of 10.

The use case for Collibra Catalog is for metadata management.

The best features in Collibra Catalog are apparent when we do the integration and establish when we fetch the data into Collibra. We have an option to store everything into a particular domain under which all the data can reside. This feature stands out because when I worked with Alation and Microsoft Purview, they did not have these capabilities.

Using lineage and Collibra Catalog has helped me overall improve the trust and transparency regarding data origin and transformation.

The business glossary feature in Collibra Catalog contributes to consistent data terminology across my teams because it is easy to use. If you want to search any business term or business-related assets, you can go to the glossary and search for it directly. Instead of using global search, you can navigate directly to the glossary and find the asset more easily.

Collibra Catalog has improved my organization through data cataloging as we were able to find assets more easily. It was organized in a structured way so that everybody can understand where the assets reside and how to navigate them.

I have utilized the sophisticated search capability in Collibra Catalog, and it can be improved by implementing more natural language search capabilities. Currently, we need to enter the asset names or domain names as it checks for exact matches. If we could enter natural language search queries, it should fetch the relevant details.

In Collibra Catalog, the main area that has room for improvement is the search functionality. It should be more natural language oriented instead of searching for exact names.

I have been using Collibra Catalog for 3 years.

I would rate the stability of Collibra Catalog as seven.

For scalability, I would rate Collibra Catalog as eight.

I would rate support for Collibra Catalog a seven. There are some documentation materials which we were unable to understand clearly. More clear documentation on the Catalog site would be beneficial.

When comparing Collibra Catalog to other vendors' products in the market, I noticed that Alation has more features. In Alation, we have natural language search along with several filters which can be applied on the search itself. These features are not present in Collibra Catalog.

The deployment for Collibra Catalog took about 10 to 20 minutes to complete.

I haven't worked on GDPR and CCPA regulations, so I am not sure about their implementation.

The same number of users continue to work with Collibra Catalog.

I would recommend Collibra Catalog to other users if they implement changes such as natural text search. There are some small bugs that need fixing, but I would still recommend it. If they improve these aspects, it will be more beneficial for everyone.

I rate Collibra Catalog an eight out of ten.