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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.
A lot of time gets saved in data search, data discovery, and data analysis, which translates into a good return on investment.
Implementing Collibra Data Catalog can be cost-effective if its features align well with the business requirements.
With traditional development requiring many specialized roles, Palantir Foundry allows us to operate efficiently with fewer personnel.
We saved approximately 20 to 35 percent in man-hours needed and the timing improved our project timelines by approximately 50 to 55 percent.
One clear example was the pipeline optimization I mentioned, where we reduced execution time by thirty to forty percent.
There were weekly sessions with them that covered the loads and highlighted when it exceeded a threshold.
They provide quick and high-quality responses.
When using the Collibra Resident Architect program, the customer service was excellent, with issues quickly resolved.
They are knowledgeable, and their boot camps demonstrate solutions in just three days, which typically takes months or years.
When I seek help regarding code in Slate, it can take considerable time for the team to find the right answer or documentation, especially since the responses depend on the level of support provided, and specific queries regarding coding usually require reaching out to more experienced developers.
The support staff are extremely knowledgeable and good at what they are doing.
We were a big bank and had thousands of assets without any issues.
Our organization has more than 10,000 employees without any glitch, without any hang, and without any slowness.
It can handle growth in users, assets, metadata, and integrations, but it requires good governance and administration.
We work with large volumes of healthcare data, and it has been able to handle all the large-scale ingestion, transformation, and distributed processing workflows effectively.
For scalability, I would rate it ten out of ten because you have a lot of flexibility.
Regarding scalability, if you have billions and trillions of records, Palantir Foundry accommodates ETL pipelines with a dedicated compute profile.
The performance and reliability of Collibra Platform is excellent since we use the SaaS cloud offering.
It does not lag, and it can handle large volumes of data in less time.
Collibra Platform is stable.
Live data streaming is very hard and it keeps breaking, so it is not very stable and depends a lot on the satellite network.
I get more technical support from Palantir.
Palantir Foundry has been a stable and reliable enterprise platform.
Users often find it challenging to utilize data governance tools, with ease of use ranked as an important criterion by 2028 standards.
Integration with tools such as Power BI, Tableau, or notebooks would be great for handling large data processing.
Leveraging AI could simplify the process by automatically listing assets for movement, requiring only a couple of clicks, providing a win for administration purposes.
The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
I want to build conversational BI or conversational agents quickly that can connect to MCPs, and other MCPs that I can communicate with in Palantir Foundry, which are areas to advance forward.
An improvement would be that in case of any changes done by the Palantir team, those changes need to be tested thoroughly so there are no downstream impacts, ensuring that the business is not affected by any modifications in the system.
Collibra has high initial costs for licensing that can be a barrier to small and medium-sized companies starting with it.
There are plans to increase license rates.
Adding modules like Privacy could become expensive.
Its high initial pricing can be intimidating, but it becomes cost-effective as it reduces the need for a development team.
In terms of getting a contractor to work on that, I would probably say it is more expensive because there are fewer people with that skillset compared to, say, Databricks or Azure.
We can consult it in the right way regarding Palantir Foundry use, as it is still a gray area right now concerning costing.
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.
We have saved up to 30% of manual work as a specific process or workflow became faster.
Another important feature is the data lineage, 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.
The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries.
The main advantage is you can decentralize the analytics, and you will have everything in one place, so that you do not need to rely on multiple departments working on different tools.
The low-code solutions made our lives easier because not everybody is too technical to get started and the barrier to entry is very low.
| Product | Mindshare (%) |
|---|---|
| Collibra Platform | 7.6% |
| Microsoft Purview Data Governance | 8.6% |
| Varonis Platform | 5.2% |
| Other | 78.6% |
| Product | Mindshare (%) |
|---|---|
| Palantir Foundry | 2.0% |
| Informatica Intelligent Data Management Cloud (IDMC) | 3.7% |
| SSIS | 3.6% |
| Other | 90.7% |
| Company Size | Count |
|---|---|
| Small Business | 24 |
| Midsize Enterprise | 14 |
| Large Enterprise | 62 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 7 |
| Large Enterprise | 49 |
Collibra Platform is preferred for workflows, data lineage, and a user-friendly interface. It enhances metadata management with robust collaboration, flexible customization, and powerful reporting, aiding organizations in effective data management.
Collibra Platform provides dependable solutions for metadata management, data lineage, and governance. It strengthens data governance with cataloging, glossaries, automation, and integration, supporting compliance and data quality management. Despite challenges with integration and metadata ingestion, the platform is vital for data governance programs, offering comprehensive AI capabilities and streamlined processes for enterprise data management.
What are Collibra Platform's key features?
What benefits should be sought in reviews?
In industries, Collibra Platform supports IT teams through metadata management and data quality assurance. It is widely used for compliance initiatives like GDPR, speeding up digital transformation and enforcing policy management. Organizations employ it to consolidate business and technical metadata, ensuring effective enterprise-scale data management in diverse sectors.
Palantir Foundry offers intuitive data management and application development, prioritizing accessibility through low-code/no-code tools, enabling users to integrate, analyze, and collaborate efficiently.
Palantir Foundry centers on user accessibility, data governance, and real-time capabilities, streamlining processes with low-code/no-code development. It supports comprehensive data analysis and integration, enhanced by digital twin features that align virtual and physical interactions. Despite high costs and performance challenges with large datasets, it remains a prime choice for sectors needing structured and unstructured data integration. Key areas include robust data security, lineage tracking, and predictive analytics, promoted through a unified management platform adaptable to diverse needs.
What are the key features of Palantir Foundry?In manufacturing, Palantir Foundry aids in engineering pipeline models and semantic frameworks, while utilities utilize its analytics to enhance service delivery. Insurance firms leverage its capability to assess and predict customer behavior. Throughout these industries, Foundry integrates across cloud environments, bridging structured and unstructured data from various sources.
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