I am using Collibra at one of my clients. We implemented Collibra there as well.

When I initially started with Collibra, it was just a data cataloging platform with governance workflows around it. Now they have acquired a lot of other tools, or they have merged or acquired different platforms.

It is a complete suite of tools for managing data. We can monitor data quality and take actions on the profiling results obtained by running data quality checks. Collibra helps catalog data assets, monitor the health of data assets, and take necessary actions. If we find data quality issues, it also provides a medium to capture those issues and how to remediate them.

The workflows allow the creation of custom workflows based on needs. The newest addition in their tool suite is AI governance, which allows cataloging all AI models currently deployed or even in the pre-production stage. It helps document model meanings and the risks involved, thus managing all risks related to AI deployments.

Collibra is working on making the latest version more user-intuitive. The previous versions were easier for technical resources to use, however, not so much for business people who are not tech-savvy. If it can become more user-intuitive and work on integrating with communication platforms like Slack or Teams, it would significantly help business users.

I have done implementations of Collibra for three to four years now.

Performance-wise, Collibra is better than other catalogs in the market. It is quite stable.

Collibra is pretty robust and scalable, given the way they have developed their product and the connectors they have established. People can easily add resources to it.

Their support team is good. However, it depends on which tier you are in and what kind of support you have, which is related to your licensing. Enterprise-grade customers get good customer support.

Pricing is definitely one of the costliest in the data catalog market. It competes with the likes of Informatica in terms of price. It is best suited for established Fortune 500 companies.

I would give Collibra a nine out of ten. For bigger organizations, it is worth the money as a tool. However, smaller organizations can get value out of some other tool, and for them, Collibra may not be the best choice.

The primary use case for Collibra Catalog in my organization is for documenting all the metadata that we have in the company. Apart from that, I am also focusing on many different layers on it, including data lineage, data quality, business glossaries, and access management workflow.

In the company that I'm working for, there are lots of different analytical groups, so it is going to save much more time for IT people.. Previously, when I was working at a more business-oriented company, our primary audience was the business people. This demonstrates that the improvements depend on the different organization structures and how you're defining your data governance goal and vision.

Except for data quality, everything is perfect. Once you have your data systems integrated with the Collibra platform, and when you set up the frequency of refreshing the metadata from that data system, it happens automatically. It is based on how you define that data refresh.

If the price is a bit reduced, that would be better. Improving the data quality landscape much better in the platform would be beneficial because the data quality landscape hasn't matured to function well compared to other competitors.

I've been working in Collibra for close to two years.

From one to ten, I would rate the stability of the solution as eigh out of ten.

I would rate the scalability of the solution as eight out of ten, which indicates no issues with scalability.

I would rate the technical support from Collibra as seven because to work in the Collibra platform, especially if you are going to do it in your own cloud services, they ask for specific consultants to work in our company. So it's not entirely independent for us to work on it when it comes to the IT landscape.

I worked in Alation and Informatica before, and I moved to Collibra right now. Informatica is a fully mature data management platform, which provides different landscapes like master data management, data governance, and data quality, wherein Collibra provides only data catalog or governance. I prefer Informatica since it is a completely mature platform in terms of data management aspects.

The setup is simple. It depends on in which platform you're going to deploy it, whether in the cloud or on premise, and if in the cloud, whether it's your company's cloud or Collibra's cloud.

They wanted us to collaborate only with the specific consulting providers to work on the Collibra platform, especially when it is in our own cloud services.

A suggestion for Collibra would be to improve collaboration with many different other technologies, as that would make it a frontrunner in the data catalog service provider space. It would be beneficial for Collibra to integrate with business intelligence tools and show us good data lineage mapping.

I'd rate the solution eight out of ten.

It is mainly for documentation purposes, to document metadata in a data catalog, and also to improve understanding, access, and exploration of data.

I've been an external consultant, advising clients on IT solutions and helping them implement these solutions, including Collibra Governance. It's used strategically to find the correct tools for the clients and operationally to implement them.

The data quality module has improved significantly, and the data lineage feature is beneficial for understanding where data is coming from and identifying data duplications.

The platform can sometimes be unstable, particularly in terms of speed and reconnection issues. There's also potential for improvements in AI and AI governance, which I don't see clear use cases for yet.

I've used the solution for four years in total.

I would rate the stability as a seven out of ten. The platform can sometimes be unstable, with occasional hiccups or fallouts requiring reconnection.

I would rate the scalability as eight out of ten.

The technical support is quite good. I would rate it as eight out of ten.

We are also familiar with Purview. We don't see Collibra so much in small companies as they have a big initial cost compared to other tools like Microsoft's Purview, where you pay less initially.

For those with IT experience, it's straightforward. For those without data experience, it can be more difficult, though this is common with many tools.

The price is quite high. Collibra has high initial costs for licensing that can be a barrier to small and medium-sized companies starting with it.

I would recommend Collibra Governance depending on the needs of the company. It's a very good tool but probably not suitable for all companies.

I'd rate the solution nine out of ten.

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

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

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

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

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

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

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

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

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

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

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

We created custom data models in Collibra Lineage for domains and communities. Under each domain, we created databases and linked data dictionaries. We set up workflows by linking controls, which were attested by control owners quarterly. All of this was automated.

The solution allowed us to quickly and efficiently implement our data governance operating model, including accountabilities, regulatory lineage, and data dictionaries. This was much faster and more efficient than manual methods or other tools like Informatica. I prefer Collibra Lineage for its self-service capabilities.

I created a use case and gave users access to data stores, allowing them to implement their data sets easily. In contrast, Informatica requires a dedicated team of IT experts to handle these tasks.

The solution's APIs can be seamlessly connected to anything.

It would be better if features like the privacy module and AI-based Collibra DQ were included in one package instead of being separate and requiring additional costs. Currently, the basic package covers lineage and documentation, but the extra modules come at an extra cost.

I have been using the product for one and a half years.

I never had any issues with the tool's stability.

I rate the solution's scalability a nine out of ten.

The solution's support is good. They would come to us whenever we had any issues.

The main differences between Collibra Lineage and Informatica are significant, particularly for small to mid-sized organizations. First, Informatica requires a dedicated team, which incurs a huge cost, making it less suitable for smaller organizations. Second, Informatica's tools are very scattered. For instance, to create a domain, you need to use Axon, and then for lineage, you must use EDC. For profiling, Informatica Developer or Analyst is required. These different tools are not well-connected to display everything on one screen. While Informatica is trying to improve with its cloud version, not many users have adopted it yet. These are the two main areas where Informatica lags.

The initial setup was straightforward. Collibra Lineage engineers helped with the setup by getting on calls with our IT team. I also benefited from its resident architect program, which provided a dedicated employee to assist with creating workflows. This was more efficient and cost-effective than hiring an external IT person.

For deploying Collibra Lineage, we needed four people: myself as the lead, one IT resource for backups, the Collibra Lineage resident architect, and one person for uploading data. The process took three to four months to complete. It doesn't require much maintenance. The solution provided a dedicated person for our account who informed us of updates. Our IT guy would then handle the update easily.

We had Collibra Lineage at Bank of the West, which was acquired by BMO Bank. BMO already used Informatica, so we had to switch from Collibra Lineage to Informatica. The tool's team was very supportive during the transition. In the future, if we have a chance, we'll choose Collibra Lineage again.

I rate the overall product a nine out of ten.

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

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

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

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

I have been using Collibra Governance for three months.

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

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

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

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

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

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

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

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

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

I use the solution to link the technical and business terms and see the lineage between different technical terms. To track data flow, we start on the report level if there is a compliance requirement. We can see which data set a particular resource is using. We can see how the data table for the data set is created. We go back and trace the source. We try to define it from the source to the target end to end.

The product increases trust in the data. We know what is affected and where we need to update things if we change something.

The diagrams are good for data visualization. It is for technical and business terms. The technical lineage is for technical terms and data. Earlier, we used to maintain the data manually. Now, everything is automated. Sometimes, we still need to verify whether the lineage created automatically is correct or not because it might have a lot of information that is not needed. It is very easy to integrate Collibra Lineage with other tools. It provides APIs. It can be for any language like Java and Python. We can use the template provided in the marketplace.

We have to pay separately for each connector. The product must be cheaper. There must be a common license for the product.

I have been using the solution since 2016.

The tool is stable. It provides good column-level and view-level lineage. I did not find stored procedures in the product. In the documentation, the product says that it is possible for some sources, though. I have not worked on every source that the product supports.

The tool is scalable. The solution is used by the people who use Catalog in our organization. It is available to everyone. We have to configure it once. Once configured, it will be available to everyone in a read-only mode. We need two developers for maintenance.

The support team is common for Catalog and Lineage. When we raise a concern, we must mention what our issue is. It is diverted automatically to the right team.

The setup is similar to the setup of Catalog. Catalog is a pre-requisite. It must be installed and configured first. Once the Catalog is installed, we must run the script for Lineage on the same server by configuring the details we want to scan. We can read the documentation and follow it easily. If we get stuck somewhere, the support team will help us. It is pretty straightforward.

The tool helps trace the lineage of complex environments.

The licensing cost depends on our requirements.

I will recommend the tool to others. It saves time spent in creating lineage manually and maintains it over a long time. Overall, I rate the solution a nine out of ten.

Catalog is primarily used for metadata cataloging and enriching it with additional information, such as adding business terms. Then, if lineage support is available in the tool, we can link business terms to technical terms.

Additionally, we can store sample data. If there's a client requirement, we can link physical metadata with reports or datasets. This allows users who need access to a particular dataset to obtain it by creating a dataset from the Catalog metadata.

For data discovery, we create datasets. The most frequently used datasets are featured on the dashboard. Users can create their own if their requirements aren't met by the most frequently used datasets. We also create data requests, and owners can approve these requests, which adds a process layer to accessing particular datasets.

So, it has been effective for data discovery in our company.

I use different functionalities within the tool. I use Collibra Catalog for metadata management or Collibra Lineage for data governance.

Once configured, data in the Catalog will be automatically updated, reducing the need for manual maintenance. So, the automation feature has positively impacted our data management tasks.

The data lineage capability is valuable as it shows how different sources are connected and how data flows, which is crucial for projects like migrations.

Moreover, data lineage visualization in Collibra Catalog aids our data governance initiatives. It's very important for identifying impacted reports during updates, making it crucial for decision-making due to its ability to link business and technical terms.

I'd like to see more integration with other reporting sources like Qlik Sense, beyond the currently supported ones like Tableau and Power BI.

I have been using it since 2019. It has been a long time.

Collibra updates the job server every quarter, so it's a stable solution that requires quarterly updates.

I would rate the stability a nine out of ten because it's quite good.

It's scalable. We create different configurations for each data source to minimize latency and ensure efficient data governance. This decentralized approach makes it highly scalable.

I would rate it a nine out of ten because it's quite good. It supports multiple authentication methods, not just username and password. It supports mechanisms like Windows authentication or any other supported source, so there's no issue.

We make it available to everyone in the company. Moreover, most users are on the client side during implementation.

The customer service and support have improved, and Collibra provides very good solutions now. They have a knowledge base that can answer our queries, suggesting solutions before we need to contact support.

The setup is quite easy and takes about 30 minutes to an hour if you have everything you need. Configuration isn't very difficult.

Deployment involves creating a job server in the client-hosted environment and configuring it to connect to all data tools, like MySQL, Oracle, or SQL Server. Then, we establish a connection between the job server and Collibra.

Data governance instances and the job server send requests to the actual data sources. Metadata gathered from the sources is passed to Collibra through this setup.

We're moving towards cloud solutions, so Collibra Data Intelligence is on the cloud. Collibra Edge can be server-based, but the job server can also be on-premises. It supports both setups, but the direction is towards cloud-only solutions.

One person can maintain the solution, and we need one service account for it.

Collibra offers a per-user licensing model.

Overall, I would rate the solution an eight out of ten because we can connect to multiple sources or create custom connectors, making it a good solution.

I highly recommend it.

We mostly use Collibra Governance for governance-related tasks like building business glossaries and creating policies.

Collibra Governance comes with a lot of features, and we have used it in one of our projects for metadata management and data lineage. I have used the solution to create governance rules and a centralized repository for business glossaries.

The solution's metadata management is pretty novice and could be improved.

I have been using Collibra Governance for around one year.

I rate Collibra Governance a nine out of ten for stability.

Collibra Governance is more suitable for medium-level and enterprise businesses.

I rate Collibra Governance a nine out of ten for scalability.

The solution's technical support was good, but there was a delay in their response time, possibly because of the time zones.

The solution’s initial setup is simple.

The solution's deployment will not take more than a week and can be done in five working days.

The solution's pricing is moderate and not very expensive.

Informatica is coming up with some level of data governance. erwin Data Modeler is quickly emerging as a competitor for Collibra in the coming days.

Collibra Governance is deployed on the cloud in our organization.

Overall, I rate Collibra Governance an eight out of ten.