Our use cases are mostly related to data analytics. We are building some dashboards and ETL pipelines on the Palantir side. Palantir Foundry is a low-code/no-code platform with a user-friendly UI. It is better than Databricks, where you need to code. Palantir Foundry has better data lineage. However, Databricks also provides many features with Databricks Unity Catalog.
The AI engine that comes with Palantir Foundry is quite interesting. We have a lot of data from various trials and analyses. We need a machine learning and analytical feature that can push huge amounts of data into the application based on pre-set rules.
Palantir Foundry is being used for multiple hybrid cloud integrations in one of the services we provide for an existing US-based customer. It's all about getting together data from Azure and Amazon and then providing a hybrid platform through Palantir Foundry. We then provide the analytics or insights enablement for the customer.
We use Palantir Foundry for data engineering and self-service tools. Palantir is a great service tool for business users who don't have the necessary IT skills. It helps them to easily draw up their own models and use cases with data by simply using Palantir's drag and drop tool. It's a great tool for us to say, "Here's your data. You can play around it, build models with it, aggregate tables, and check everything on your own." It's a self-service tool. It's deployed on cloud. The cloud provider is AWS. Over 300 people are using this solution in my organization. It's used on a daily basis.
Our primary use case is for data engineering and some data analysis, bringing in data from several sources and using data wrangling and data managing to support the reporting tools we have. We use the reporting apps for some of our basic reporting. We are customers of Palantir.
This is a data integration tool with multiple components that link to multiple sources to create repositories, transform data and make it available for dashboards or management purposes. We're based in the UAE and I'm a senior manager, customer and user of this solution.
I didn't use Foundry, but I went through some training, and my team became certified in it. When I left the company, there were probably 100 research projects that had been added to it. I did it project by project. Around 30 were completed. About 40 or 50 were in progress, while there were 20 more in the queue. You could reuse data and leverage data that had been imported. We imported lots of Epic data. You needed permission to see the Epic data. Someone with a research project approved by the institution could ask permission to join it with other data. In a relational world, you could say, "I'll give you database permissions, but I'll need to mask these columns that are based on those." It's similar to an SQL database. People submitted their project requests to a project review committee. The capacity was limited because people needed to understand the platform, but I'm sure they have trained more people on it since then.
This solution is used more for the analytics available on the platform. The main use was for a COVID-19 White House initiative that was handled by the Vice President, Michael Pence.
Associate - Inhouse Consulting at a pharma/biotech company with 10,001+ employees
Real User
2020-07-12T11:48:52Z
Jul 12, 2020
We use this solution for everything, including sales. One of our use cases is performing machine learning to gives us an understanding of customer behavior, and which message should be used to target different customers.
Palantir Foundry is an enterprise data management platform offering comprehensive tooling for working with big data. Because it is an operating system made for modern enterprises, it is highly available and a continuously updated platform. Palantir Foundry is a fully managed SaaS platform that spans from cloud hosting and data integration to flexible analytics, visualization, model-building, operational decision-making, and decision capture. It equips technical and non-technical users to...
Our use cases are mostly related to data analytics. We are building some dashboards and ETL pipelines on the Palantir side. Palantir Foundry is a low-code/no-code platform with a user-friendly UI. It is better than Databricks, where you need to code. Palantir Foundry has better data lineage. However, Databricks also provides many features with Databricks Unity Catalog.
The AI engine that comes with Palantir Foundry is quite interesting. We have a lot of data from various trials and analyses. We need a machine learning and analytical feature that can push huge amounts of data into the application based on pre-set rules.
Palantir Foundry is being used for multiple hybrid cloud integrations in one of the services we provide for an existing US-based customer. It's all about getting together data from Azure and Amazon and then providing a hybrid platform through Palantir Foundry. We then provide the analytics or insights enablement for the customer.
We use Palantir Foundry for data engineering and self-service tools. Palantir is a great service tool for business users who don't have the necessary IT skills. It helps them to easily draw up their own models and use cases with data by simply using Palantir's drag and drop tool. It's a great tool for us to say, "Here's your data. You can play around it, build models with it, aggregate tables, and check everything on your own." It's a self-service tool. It's deployed on cloud. The cloud provider is AWS. Over 300 people are using this solution in my organization. It's used on a daily basis.
Our primary use case is for data engineering and some data analysis, bringing in data from several sources and using data wrangling and data managing to support the reporting tools we have. We use the reporting apps for some of our basic reporting. We are customers of Palantir.
This is a data integration tool with multiple components that link to multiple sources to create repositories, transform data and make it available for dashboards or management purposes. We're based in the UAE and I'm a senior manager, customer and user of this solution.
I didn't use Foundry, but I went through some training, and my team became certified in it. When I left the company, there were probably 100 research projects that had been added to it. I did it project by project. Around 30 were completed. About 40 or 50 were in progress, while there were 20 more in the queue. You could reuse data and leverage data that had been imported. We imported lots of Epic data. You needed permission to see the Epic data. Someone with a research project approved by the institution could ask permission to join it with other data. In a relational world, you could say, "I'll give you database permissions, but I'll need to mask these columns that are based on those." It's similar to an SQL database. People submitted their project requests to a project review committee. The capacity was limited because people needed to understand the platform, but I'm sure they have trained more people on it since then.
This solution is used more for the analytics available on the platform. The main use was for a COVID-19 White House initiative that was handled by the Vice President, Michael Pence.
We use this solution for everything, including sales. One of our use cases is performing machine learning to gives us an understanding of customer behavior, and which message should be used to target different customers.