Collibra Platform Reviews

I work with Collibra Data Intelligence Platform. I am experienced in both platforms, but more experienced with Collibra Data Intelligence Platform. I have experience creating workflows, harvesting technical lineage, and working with Data Governance along with data quality.

The workflows in Collibra Data Intelligence Platform are unique as no other Data Governance tool has this feature. The data quality functionality provides cutting-edge, next-level insights when compared to other tools such as Alation and Microsoft Purview. In governance, Collibra Data Intelligence Platform has an upper hand.

The mapping features in Collibra Data Intelligence Platform allow users to import and export Excel files. While importing Excel files, users can map to numerous assets. We can build relations using these imports and mappings, and obtain lineage information. Additionally, there is integration between Data Quality and the data intelligence platform, which enables another type of mapping.

The workflows in Collibra Data Intelligence Platform save substantial time by allowing us to create and assign tasks to business stewards and stakeholders. Instead of sending emails each day, we can create tasks that automatically generate notifications to streamline the process.

The main advantage of Purview is its integration with Microsoft solutions. Data can be harvested from any solution within Azure, data fabric, or other platforms easily with Purview. With Collibra Data Intelligence Platform, users need to create and establish connections, which requires entering connection details. This process is more time-consuming in Collibra Data Intelligence Platform compared to Purview, where everything can be done in minutes. Additionally, Purview includes data products, which Collibra Data Intelligence Platform is currently introducing. For stakeholders, data products are crucial.

I have been using the solution for three years, precisely two years and ten months. This July it will be three years. I started as a fresher in Data Governance and have been working in this field since the beginning.

I have not experienced any downtime or stability issues until now.

I have not had any experience working with AI governance-related API. I am satisfied with their support team. I encountered some issues with data quality initially in Collibra Data Intelligence Platform, and they resolved those issues. I also faced challenges with establishing data quality rules in DQC aggregation files, which were resolved by the support team.

There were no blockers during setup. It was straightforward to create workflows and deploy them into Collibra Data Intelligence Platform by following the documentation.

Data quality in Collibra Data Intelligence Platform involves six dimensions: accuracy, completeness, integrity, and timeliness. The platform's Data Quality encompasses all these aspects.

Task completion time depends on the specific tasks in Collibra Data Intelligence Platform. For example, an approval task typically takes less than one hour.

Collibra Data Intelligence Platform introduced AI governance approximately two years ago. It features assessments that work in conjunction with AI governance, where users answer questions created by stakeholders or Data Owners.

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.

Neutral

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.

My main use case for Collibra Platform is reporting governance and building the data lineage by connecting to Unity Catalog and documenting KPIs, dimensions, and business reports. Once those reports are implemented by a developer using this data lineage, we could do end-to-end traceability if some KPIs are shown wrong in the report, then we leverage this data lineage to check the actual data source, the underlying field, table, etc., to do the root cause analysis.

For example, we have multiple data sources for building the reports using Collibra Platform, and we plugged in Tableau metadata and SAP Analytical Cloud, which are two of the main data sources for visualization, with our back end being SAP BW and sometimes SAP HANA. When a director from the business sends or documents the report in Collibra Platform, highlighting the requirements and KPIs, this is the first phase of the lifecycle of the report as a candidate or draft. Once it goes to the formal review process with business stakeholders and the data governance council, it is approved and goes for actual implementation to the developers, who implement these reports in BW and visualize them in Tableau or SAP Analytical Cloud platform. If one of the KPIs in a report is shown wrong, then using the data lineage in Collibra Platform, we could see which particular KPI is sourced from which SAP BW or SAP HANA table. Then the developer quickly finds out the root cause, fixes it, and showcases it to the end user using this data lineage capability in Collibra Platform. This is one of the practical use cases we implemented via Collibra Platform.

We have some other use cases, such as building the data quality report on certain data assets where we leverage Collibra Platform. For example, we work with the business to document their data assets in the form of data attributes, which are consumed by other businesses, and they set up business rules against those data attributes. Our data quality team creates data quality checks that are documented in Collibra Platform, and using the data lineage, we could see the quality of a specific attribute. We have traffic light indicators, such as green for good and red for an obvious problem, and in cases with certain errors, it is easy for the end user to consume this data attribute for reporting or quality purposes by seeing the data quality scorecard, which helps in deciding whether it is worth using or not. If not, they could trigger a workflow to the end data owner to fix those data quality issues, allowing them to leverage those data assets in their reports or use cases.

The best features of Collibra Platform include workflows primarily for governance perspective, where you can define your asset lifecycle, and use these workflows to govern those and collaborate with other stakeholders. We gather feedback collectively and notify when certain attributes or assets are changed. Another important feature is the data lineage I have described earlier, which helps in impact assessment before making any changes, showing where a particular field is being used in a report, data quality report, or normal report. It also assists in root cause analysis if something breaks down in your data pipeline. Recently, Collibra Platform also implemented certain AI features, such as generating descriptions for technical metadata that often lacks descriptions in data sources, which helps to define out-of-the-box or standard definitions of data assets such as tables and columns. These are the main features, and Collibra Platform also offers AI governance, which we do not use currently but is a powerful feature in Collibra Platform.

Collibra Platform helps to understand underlying policies and compliance classifications, including PII or non-PII classifications, crucial for accessing confidential data. This significantly eases the data finding and shopping process, allowing for quick access to necessary data.

The governance implemented provides clear ownership, so you already know who the actual owner is without chasing around. You find the real owner in Collibra Platform, which is always up to date, helping to identify the concerned party, and using a workflow, you define the lifecycle of collaboration, such as who should participate, who should be the reviewer and approver, and who should take action on the data, involving data stewards, business data stewards, technical data stewards, and the actual data owners. This makes life easier, improving data findability or searchability by approximately thirty to forty percent through these workflows.

Collibra Platform's platform needs improvement in certain areas such as workflows designed for administration that send excessive notifications, and sometimes it is unclear how many times a workflow instance was triggered. There are intelligence gaps that need addressing, along with user experience, especially with searchability when similar data assets have redundancy in SAP systems. Although certain improvements were made, such as defining weightages for certain assets to prioritize search results, more fine-tuning is still beneficial.

For migrating assets from one environment to another, we use import-export functionality, which can be cumbersome and manual. Leveraging AI could simplify the process by automatically listing assets for movement, requiring only a couple of clicks, providing a win for administration purposes.

I have been using Collibra Platform for the last ten years.

Collibra Platform is stable.

We scaled from a few hundred to over a thousand users, highlighting effective scalability for us.

Customer support was great.

We did not previously use a different solution.

Getting started with Collibra Platform was quite tough initially, as it involved change management to lift and shift to new technology. We set up as per governance policy, starting small, onboarding business data users for reporting governance, documenting reports, KPIs, and dimensions, leveraging workflows to collaborate efficiently. We identified data owners from each business domain and began with critical data elements, around one hundred to three hundred elements and their associated KPIs. Regular biweekly touchpoints helped to understand their journey, the value gained, and areas for improvement. Over roughly two years, we saw significant adoption growth from a few hundred to over a thousand users, and this journey continues.

We have seen a return on investment, as previously it took weeks or even months to find the actual data owner, while now it takes just seconds or a few minutes, indicating a significant increase. The reduction in time needed to find and search for data is acknowledged by our senior management as they actively use Collibra Platform.

Before choosing Collibra Platform, we evaluated other options, including Informatica.

My advice for others considering Collibra Platform is to start with a small vanilla platform and your use case rather than attempting a big bang theory. Starting small can provide a significant impact, such as reporting, which also draws senior management attention. I would rate this product an eight overall.

I used Collibra Catalog primarily for cataloging all the assets. We created data dictionaries by ingesting data from multiple databases into Collibra Catalog and setting up workflows for review and approval processes.

The most valuable features of Collibra Catalog are its customizability and ease of use. We created data dictionaries both by ingesting our database structures and for non-database sources. We also set up different communities, defining ownership and stewardship with customizable workflows.

There is an issue with Collibra Catalog's pricing model, especially for organizations with many databases, as the initial package comes with a limited number of connectors. This can lead to manual efforts to connect more databases, increasing costs. It would be beneficial if they offered more connectors as part of the initial package.

We used Collibra Catalog as long as we had Collibra, starting from when we began cataloging all our assets.

I did not have any issues with the stability of Collibra Catalog.

Collibra Catalog is quite scalable. We were a big bank and had thousands of assets without any issues.

When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved. Without the program, the support was decent, with response times of 24-48 hours. Sometimes the support was useful, and sometimes it was not.

Neutral

My company initially used Collibra, but after being acquired by BMO, which had a contract with Informatica, we had to switch. BMO had recently renewed their contract with Informatica, which led to letting go of Collibra.

The initial setup was straightforward with the involvement of our IT team. It is important to have a Collibra Resident Architect for a successful implementation, which we found more effective than hiring external contractors.

We used the Collibra Resident Architect program instead of hiring contractors. This was a cost-effective approach, and it was extremely beneficial to have a knowledgeable Collibra employee assist with setup and configuration.

The pricing for Collibra was good since we did not have many add-ons. However, adding modules like Privacy could become expensive. The value is still greater when considering the cost of customizing other tools.

I have experience comparing Microsoft Purview and Data Hub alongside Collibra. Collibra is favored for governance, while Purview, integrated with Azure, is a better fit for engineers than business users.

I would definitely recommend Collibra Catalog to others. Of all the catalogs I've used, Collibra stands out as being more of a full tool for governance. As long as Collibra can connect to your databases, it cannot be easily beaten. I rate the overall solution an 8 out of 10.

We are a customer of Collibra. Collibra Governance is applied in our data management workflows by creating all the business functions separately, maintaining the data sources of those KPIs and everything separately on those businesses.

Collibra Governance provides ease of use. The portal is self-explanatory with lots of documentation on its usage, making implementation and understanding simple for our team.

The most important feature is the ease of use. The portal is very self-explanatory and robust. The tool also provides integration with a lot of sources.

There should be more detailed documentation on the selectors and certain information, and a reduction in cost as compared to other tools. The data marketplace solution could be more flexible in filtering capabilities. Additionally, their responsive time in technical support can be quicker.

I have been working with Collibra Governance for almost two years.

The solution is stable, and I would rate it as a seven out fo ten.

On a scale of one to ten, the scalability of the solution is around seven or eight out of ten.

Technical support is effective in providing solutions. That said, their response time can be improved. I would rate it around five or six out of ten.

Neutral

We have not used another solution till now but are considering others, especially due to cost.

It is mostly straightforward, especially if you have the infrastructure ready.

I wish the tool could be less expensive compared to other tools.

We are looking into Purview due to costs and features differences.

The tool is intuitive, easy to learn, and would be better if the costs were reduced.

I'd rate the solution seven 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.

Positive

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.

My use case for Collibra Lineage is for data governance; the purpose is to manage and govern our data effectively.

The best features of Collibra Lineage include its ability to map data flows and provide clear visualizations. I appreciate the interface, the reporting capabilities, and the overall user experience about this product. I use the automatic data flow mapping and visualization feature, and it helps my organization by providing clarity in understanding data lineage.

I have been using this solution for three years, and the improvements I have seen include better data quality and compliance, which benefits my business mainly by reducing risks.

There are areas of improvement in Collibra Lineage, including pricing, support, and reporting. Regarding pricing, it is somewhat expensive, and I think it could be more cost-efficient.

I have been using Collibra Lineage for three years.

The deployment of Collibra Lineage was complex in general.

I experience occasional downtime, bugs, and some glitches.

I would rate the scalability of Collibra Lineage as a nine; it is a scalable solution for my business.

I would rate the technical support from one to ten as a seven, with ten being the best.

Neutral

Approximately twenty users work with Collibra Lineage.

I would definitely recommend this product to other users. The impact of Collibra Lineage on my data governance processes is significant in ensuring data quality and compliance. The integration with other Collibra products is valuable in my data governance initiatives.

The deployment was done through cloud and took about a month. I am just a customer, and my clients are generally small to medium businesses. My overall rating for Collibra Lineage is 9 out of 10.

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.

Neutral

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.