The primary use case for the solution is the governance of data dictionaries. It is useful for managing and classifying data on a large scale.

The product has significantly improved data governance by providing a centralized platform for managing data assets and ensuring consistent definitions. It has led to better data quality and more efficient compliance with regulatory requirements.

The product's most valuable features are cataloging and classification.

They could simplify the platform's setup and design process. It requires significant IT involvement and expertise, which can be a barrier for smaller organizations.

We have been using Collibra Governance for approximately five years.

The product is stable and reliable. I rate the stability an eight.

The product is scalable, but the extent to which it scales effectively depends on how well it is designed and implemented.

I rate the scalability an eight.

The product's pricing is high, which its comprehensive features and capabilities may justify. However, the cost can be a consideration for smaller organizations or those with limited budgets.

As a data governance advisor, I evaluate various solutions based on their fit for the client's requirements. While I recommend this solution when it meets the organization's needs, there are more than one-size-fits-all solutions.

Integration with it can vary based on the client's IT landscape. For some organizations, integration is straightforward, while for others, it can be quite complex.

Its user interface is generally user-friendly, but it could benefit from some enhancements to improve ease of navigation and customization. While functional, a more intuitive design could help users operate the platform more efficiently.

Its performance can vary depending on how well it is configured and the scale at which it is deployed.

It has strong data privacy and security features, including robust encryption and access controls. It is designed to comply with various data protection regulations, crucial for maintaining data security.

It offers extensive customization, allowing tailored configurations to meet specific organizational needs. However, achieving this level of customization often requires considerable time and technical expertise.

It has strong user adoption and satisfaction due to its comprehensive features and capabilities. However, user experiences can vary based on the organization's specific needs and the solution's implementation.

I rate it a seven 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.

We have a full-time user interface in-house.

The solution makes data more discoverable and transparent.

We can easily connect to sources. It is like plug-and-play.

The workflow documentation must be improved. It is our number one pain point.

I have been using the solution for six to seven years.

The customer service is bad. It is not the best. I rate support two or three out of ten. The support team must be communicative and stay in touch with the customers.

The core functionality is good. The initial setup becomes challenging if there are any vulnerabilities or changes because not much documentation is available.

I am using the tool because my current organization decided to use it. My previous organization used a more enhanced tool. There are other tools with better functionalities. Overall, I rate the tool a six 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.

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.

We use the product for classification based on the different regulations and compliance requirements.

The platform is customizable. In comparison, Informatica Axon has predefined facets. Meanwhile, Collibra lets us create custom assets. It helps us build a powerful workflow mechanism where there can be any stewardship, including issue management governing assets using policies, regulations, or business rules. They are integrated very well. It has a lot of connectors with different source systems and efficient cataloging features.

There could be more integration similar to Snowflake, for instance. They do support integration, but complete lineage is not possible. Certain implementations, including lineage maps, could be user-friendly. At the moment, there needs to be more lineage between data sources. It needs improvements in terms of attribute connectivity during data transformation.

We have been using Collibra Governance for seven or eight years.

It is a stable platform.

Collibra Governance is suitable for enterprise businesses. It is a SaaS product. Thus, the end users don’t have to maintain scalability or maintenance.

The technical support team is responsive.

I have worked with Informatica Axon and Data Catalog. In comparison, Collibra has better workflow management features. I recommend it for technical usage as well. However, Axon is more user-friendly for creating lineage diagrams. It has ready-to-use templates for deployment.

The initial setup process is complicated. However, once you get good training and understanding of the system, it is very straightforward. Some of the configurations require support. It takes around a week or two to complete all the configuration for the existing ecosystem.

For Informatica, we have to buy cataloging and governance separately. Meanwhile, Collibra offers one structure for both. We purchase its annual license. There is an extra cost for additional users.

I rate Collibra Governance an eight out of ten.