Collibra Platform Reviews

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. 

Positive

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. 

The product’s primary use case is metadata management. It helps us capture different datasets, including images, glossaries, etc.

Collibra Catalog has significantly enhanced data governance and compliance for our team, primarily through its valuable feature of endpoint lineage enabling visual representation of the data. However, it takes a lot of manual effort for the same. They could introduce more features to align the process.

A key area for improvement in Collibra Catalog lies in its integration capabilities, particularly with a broader range of sources such as MongoDB and others. It is a time-consuming process for the engineering team to set up custom connectors. Thus, they could provide a wide range of connectors to address this issue.

We have been using Collibra Catalog for three or four years.

I rate the product’s stability an eight out of ten.

We encounter complexities in scaling the platform. It requires a lot of manual effort. At present, we only have 60 to 70 users in our organization. Our objective is to implement it for around 2000 users per month.

I rate the scalability a six out of ten.

I haven’t interacted directly with the technical support team. From the higher-level perspective, there have been interactions regarding our requirements, although the turnaround time for addressing the issues needs improvement.

The initial setup is complicated in terms of accessibility for enterprise users. Determining the optimal number of licenses for an enterprise proved to be a complex task, adding a layer of complexity to the implementation. For governance, they should include customized workflows.

The product is highly priced compared to other vendors. It becomes a challenge as we have to incur additional costs for widespread connectors that are unavailable in the product. It takes a good amount of time and effort to build custom connectors as well. There could be better integration with other systems instead.

I recommend Collibra Catalog to others and rate it a seven 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.

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.

Neutral

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.

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

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

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

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

I have been using Collibra Governance for three months. 

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

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

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

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

Positive

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

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

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

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

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

Collibra is for the classification of data. Collibra is being sourced to all the intakes for the company, which might be legacy systems or new systems or might be lineage as well. Collibra takes up and does its own governance over there, and the data is fed into Ataccama. Ataccama and Collibra seem to be cascaded, but Collibra is the first player. But that doesn't mean it saves a lot for Ataccama.

The solution's most valuable features are its scalability and how it can be integrated to any other intakes.

Collibra gives a lot of facilities in the cloud, but achieving those facilities on-prem becomes a big challenge. Collibra should loosen up those areas there and try to give stakes for that. The uses can vary. They can be limited to a small amount, or they can be a huge chunk. If Collibra thinks the utilization should be controlled and monitored by them on a cloud level, making for highly scalable data, it's good for them. But when the customer needs it, Collibra will be in the minute volume, in which case they will go for the on-premise service. That's what I feel Collibra lacks because some things cannot be integrated for on-premise customers.

I've used this solution for two years.

Overall, Collibra is a stable tool. Because of the scalability, the volumes are big, and you must have patience. That's where Collibra gets conflicted. There is highly scalable data with big databases connected. You'll need patience to wait for the batch lists to be completed. Calibra is slow but stable.

Collibra is highly scalable. Since Collibra works with Ataccama, 60 to 70 people use this solution.

The initial setup is exhaustive, but I cannot say that it's difficult or easy.

Collibra is a bit expensive.

I recommend Collibra only when customers have a very sparse intake. Such as if they have primitive lineages and data sources that they cannot make obsolete or remove. Suppose they have varieties of intakes. In that case, I definitely would ask customers to go for Collibra. That's not because an intake can be integrated into Collibra. The profitability is that Collibra is integrated at the output end. The team is working on visualization. The service team is very preemptive and efficient. Collibra will give you a good scoop. If a company is vast enough and has various intakes, databases, and sources, Collibra is good for them.

I rate Collibra a seven out of ten. Depending on the client, the rating may vary. If someone has told you that they have various sparse intakes and need to govern their data, Collibra will be a nine out of ten. But for a company with a limited intake, I would say that Collibra would be a load for them on the price side.

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

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

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

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

The quality and visibility of the data links are great.

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

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

The technical support could be better.

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

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

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

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

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

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

Neutral

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

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

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

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

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

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

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

I would rate it nine out of ten overall.  

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.

Positive

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.