2
Palantir Data Engineer Cert Exam with verified detailed || || || || || || || ||
answers
Data transformation - ✔✔scalable build system for data that leverages multimodal compute
|| || || || || || || || || || || ||
to produce output datasets
|| || ||
Pipeline Management - ✔✔- capabilities combine change management, data quality, and
|| || || || || || || || || || ||
data loading features.
|| ||
- enables fast, flexible, and scalable delivery of data pipelines while providing robustness
|| || || || || || || || || || || || ||
and security
||
- Data engineers can define health checks that guarantee only fully compliant data will be
|| || || || || || || || || || || || || || ||
deployed to production. Where issues are found, the platform provides diagnostics on the
|| || || || || || || || || || || || ||
discrepancies detected. ||
Hyper Auto - ✔✔support for Software-Defined Data Integration (SDDI) to not only connect
|| || || || || || || || || || || || ||
to ERP and CRM, but generate fast data pipelines that could then feed into the Ontology to
|| || || || || || || || || || || || || || || || ||
translate data into operational || || ||
External Transformations - ✔✔perform scheduled syncs and exports to external systems
|| || || || || || || || || || ||
using REST APIs. Recommended to use Code Repositories in Foundry to write external
|| || || || || || || || || || || || ||
Python transforms ||
Dataset - ✔✔- most essential representation of data, fundamentally a wrapper around a
|| || || || || || || || || || || || ||
collection of files stored in a backing file system that allows for perms, schema
|| || || || || || || || || || || || || ||
management, version control and updates || || || || ||
- structured (tabular - parquet, csv)
|| || || || ||
- unstructured (images, video, PDFs)
|| || || ||
- semi-structured (XML, JSON)
|| || ||
- transactions - git commands for the datasets (open, committed, updating)
|| || || || || || || || || ||
, 2
Streams - ✔✔similar to dataset, but a representation of data - wrapped around a collection
|| || || || || || || || || || || || || || ||
of rows that are tabular
|| || || || ||
- provides a lower latency view of the data
|| || || || || || || ||
- hot buffer - low latency to pull from storage
|| || || || || || || || || ||
- cold buffer - transferred over to this every few minutes to archive data
|| || || || || || || || || || || || || ||
- high throughput and compressed stream types
|| || || || || ||
Media Set - ✔✔Multiple files with common schema (file format), used to work with high-
|| || || || || || || || || || || || || ||
scale, unstructured data (multiple pdfs)
|| || || ||
Jobs - ✔✔ran on datasets to compute after changes
|| || || || || || || || ||
- jobspec - encapsulated by a job, and it is the definition of how a job should be constructed
|| || || || || || || || || || || || || || || || || || ||
- job types: data connection sync, code repository, health checks, analytical applications,
|| || || || || || || || || || || ||
exports
Schedules - ✔✔used to run builds off of a trigger, which could be a time or action/event
|| || || || || || || || || || || || || || || ||
Health checks - ✔✔used to validate data quality that is scheduled
|| || || || || || || || || || ||
- job level, build level, and freshness check
|| || || || || || ||
Virtual Tables - ✔✔allows you to query tables in supported data platforms without storing it
|| || || || || || || || || || || || || ||
in a dataset (so data coming from other places)
|| || || || || || || || ||
Change Data Capture (CDC) - ✔✔enterprise data integration pattern often used to stream
|| || || || || || || || || || || || ||
real-time updates from a relational database to other consumers, supporting syncs,
|| || || || || || || || || || ||
processes, stores from file systems that produce capture feeds || || || || || || || || ||
Palantir Data Engineer Cert Exam with verified detailed || || || || || || || ||
answers
Data transformation - ✔✔scalable build system for data that leverages multimodal compute
|| || || || || || || || || || || ||
to produce output datasets
|| || ||
Pipeline Management - ✔✔- capabilities combine change management, data quality, and
|| || || || || || || || || || ||
data loading features.
|| ||
- enables fast, flexible, and scalable delivery of data pipelines while providing robustness
|| || || || || || || || || || || || ||
and security
||
- Data engineers can define health checks that guarantee only fully compliant data will be
|| || || || || || || || || || || || || || ||
deployed to production. Where issues are found, the platform provides diagnostics on the
|| || || || || || || || || || || || ||
discrepancies detected. ||
Hyper Auto - ✔✔support for Software-Defined Data Integration (SDDI) to not only connect
|| || || || || || || || || || || || ||
to ERP and CRM, but generate fast data pipelines that could then feed into the Ontology to
|| || || || || || || || || || || || || || || || ||
translate data into operational || || ||
External Transformations - ✔✔perform scheduled syncs and exports to external systems
|| || || || || || || || || || ||
using REST APIs. Recommended to use Code Repositories in Foundry to write external
|| || || || || || || || || || || || ||
Python transforms ||
Dataset - ✔✔- most essential representation of data, fundamentally a wrapper around a
|| || || || || || || || || || || || ||
collection of files stored in a backing file system that allows for perms, schema
|| || || || || || || || || || || || || ||
management, version control and updates || || || || ||
- structured (tabular - parquet, csv)
|| || || || ||
- unstructured (images, video, PDFs)
|| || || ||
- semi-structured (XML, JSON)
|| || ||
- transactions - git commands for the datasets (open, committed, updating)
|| || || || || || || || || ||
, 2
Streams - ✔✔similar to dataset, but a representation of data - wrapped around a collection
|| || || || || || || || || || || || || || ||
of rows that are tabular
|| || || || ||
- provides a lower latency view of the data
|| || || || || || || ||
- hot buffer - low latency to pull from storage
|| || || || || || || || || ||
- cold buffer - transferred over to this every few minutes to archive data
|| || || || || || || || || || || || || ||
- high throughput and compressed stream types
|| || || || || ||
Media Set - ✔✔Multiple files with common schema (file format), used to work with high-
|| || || || || || || || || || || || || ||
scale, unstructured data (multiple pdfs)
|| || || ||
Jobs - ✔✔ran on datasets to compute after changes
|| || || || || || || || ||
- jobspec - encapsulated by a job, and it is the definition of how a job should be constructed
|| || || || || || || || || || || || || || || || || || ||
- job types: data connection sync, code repository, health checks, analytical applications,
|| || || || || || || || || || || ||
exports
Schedules - ✔✔used to run builds off of a trigger, which could be a time or action/event
|| || || || || || || || || || || || || || || ||
Health checks - ✔✔used to validate data quality that is scheduled
|| || || || || || || || || || ||
- job level, build level, and freshness check
|| || || || || || ||
Virtual Tables - ✔✔allows you to query tables in supported data platforms without storing it
|| || || || || || || || || || || || || ||
in a dataset (so data coming from other places)
|| || || || || || || || ||
Change Data Capture (CDC) - ✔✔enterprise data integration pattern often used to stream
|| || || || || || || || || || || || ||
real-time updates from a relational database to other consumers, supporting syncs,
|| || || || || || || || || || ||
processes, stores from file systems that produce capture feeds || || || || || || || || ||
