Data Engineer Basics - Transform and Contextualize

Learn how to transform and contextualize data using Cognite Data Fusion and Python SDK.

Learn how to transform and contextualize data with Cognite Data Fusion (CDF) using its interface and Cognite Python SDK. From transforming data using CDF, matching entities using Python SDK to modeling your industrial data, this learning path consists of all the relevant courses and a final assessment.

The path has two parts:

Using Cognite Data Fusion's user interface

Using Cognite's Python SDK

CDF Transformations

Match Entities: Concept and UI

Interactive Engineering Diagrams: Concept and UI

Cognite Data Modeling

Python SDK Transformations

Match Entities with Python SDK

Interactive Engineering Diagrams with Python SDK

Cognite Data Modeling

Click the buttons below for more information.

Learn how to transform industrial data using Cognite Data Fusion (CDF) and Cognite Python SDK.
Explain the concepts associated with contextualization tools like entity matching and interactive engineering diagrams.
Learn how to use different contextualization tools using CDF and Cognite Python SDK.
Explore the fundamental concepts, practical applications, and advanced techniques for effectively organizing, querying, and managing industrial data.

Before you start this learning path, we suggest that you go through Cognite Data Fusion Fundamentals firsr. Also, it is recommended to have some previous experience with Python.

This is the second of two learning paths for data engineers. You'll earn a badge for each and a certificate upon completion of both learning paths and passing the final assessment here.

Course	Learning goals
CDF Transformations	Understand why you should use CDF Transformations. Find detailed information about the target schema. Write SQL queries and use SparkSQL and Cognite’s custom functions to transform data. Schedule and run data transformations.
Match Entities: Concept and UI	Explain how entity matching works. Evaluate when it is beneficial to use entity matching and when to choose other tools to contextualize data. Contextualize data using entity matching. Explain different entity matching models and their mode of operation.
Match Entities with Python SDK	Learn about matching entities using Python SDK, different entity matching models, and more.
Interactive Engineering Diagrams: Concept and UI	Explain how the interactive engineering diagrams tool works. Evaluate when it is beneficial to use the interactive engineering diagrams and other tools. Understand the engineering diagram parsing algorithm.
Python SDK Transformations	Work with CDF RAW tables. Identify three ways of transforming data: with CDF Transformations, Cognite Python SDK, and Cognite Transformations CLI. Create, deploy, run and monitor transformations using Cognite Python SDK.
Cognite Data Modeling	Learn how to build and manage an industrial knowledge graph and model relations between entities. Explore advanced structuring techniques for enhancing knowledge graphs through schemas, containers, views, and data models. Learn instance ingestion and management using the /apply and /delete endpoints. Explore the capabilities of querying graphs within CDF. Learn about access control in Data Modeling Learn to create generic and use-case-specific asset hierarchies within CDF. Learn about AI search within CDF
Data Engineer Basics: Transform and Contextualize - Assessment	Earn a data engineer basics certificate on completion of the exam.

Connect with other learners and the rest of Cognite's Community on Cognite Hub.