In this Palantir Foundry Developer Training is designed to equip professionals with the technical expertise needed to build scalable data-driven solutions on the Palantir Foundry platform. Foundry is a powerful enterprise data integration and analytics platform that enables seamless collaboration, data governance, and operational decision-making at scale. This hands-on training course provides in-depth knowledge of key Foundry components, including Code Repositories, Object Explorer, Ontology, Pipelines, Transformations, and Data Lineage. Participants will gain practical experience in building and deploying data pipelines, automating workflows, integrating diverse data sources, and working with Foundry’s ontology layer for semantic modeling. Whether you're a data engineer, developer, or analyst, this course is tailored to help you harness the full potential of Palantir Foundry’s development environment.
By the end of the course, learners will be able to navigate the Foundry interface, collaborate on projects, write transformation logic using PySpark or SQL, and deploy data applications that align with enterprise needs. This training is ideal for professionals aiming to advance their careers in data engineering, analytics, or enterprise IT architecture.
Course Objectives:
In this course, you will learn to:
- Understand the architecture and core components of Palantir Foundry.
- Navigate and utilize the Foundry platform interface efficiently.
- Build, manage, and deploy data pipelines using Code Workbooks and Pipelines.
- Integrate and transform data from various sources using PySpark or SQL.
- Model business data using Ontology and Object Explorer for semantic consistency.
- Implement data lineage tracking and manage data versioning.
- Automate workflows and schedule data processing jobs within Foundry.
- Collaborate effectively using Code Repositories and project workspaces.
- Apply role-based access control and data governance best practices.
Course content
Introduction to Palantir Foundry
- Overview of the Foundry platform
- Key features and architecture
- User interface and navigation
Data Integration and Ingestion
- Connecting to data sources
- Ingesting structured and unstructured data
- Managing datasets and schema
Foundry Pipelines
- Creating and managing pipelines
- Code Workbooks and Spark transformations
- Pipeline scheduling and monitoring
Data Transformation Using PySpark and SQL
- Writing transformations with PySpark
- SQL-based transformations
- Best practices for scalable processing
Ontology and Data Modeling
- Introduction to Ontology in Foundry
- Creating and managing object types
- Linking data to business concepts
Code Repositories and Version Control
- Managing projects with Code Repositories
- Collaboration with version control
- Code review and deployment workflow
Automation and Workflow Orchestration
- Automating data workflows
- Event-driven processing
- Job dependency management
Data Governance and Access Control
- Role-based access management
- Data lineage and audit trails
- Compliance and security features
Visualization and Reporting
- Creating dashboards and reports
- Integration with BI tools
- Sharing insights with stakeholders
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Course Prerequisites
- Basic understanding of data engineering concepts
- Familiarity with SQL and Python programming
- Prior experience with ETL processes and cloud or big data tools is an advantage.
Who can attend
- Data Engineers
- Data Analysts
- ETL Developers
- Business Intelligence Professionals
- Software Developers
- Data Scientists
- Technical Project Managers
- Big Data Professionals
- IT Professionals working on data integration and transformation platforms
Number of Hours: 25hrs
Certification
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- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
FAQs
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- One to One Training
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- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Materials
- Preparing for Certification
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