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Course : Data Integration with Cloud Data FusionOfficial course, preparation for Google Cloud certification exams
Practical course - 2d
- 14h00 - Ref. DID
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 | Identify data integration needs and use cases for Cloud Data Fusion |
| Understand the capabilities and main components of the Cloud Data Fusion platform |
| Design and execute batch and real-time processing pipelines |
| Use Wrangler and connectors to transform and integrate multi-source data |
| Configure runtime environment, supervise, troubleshoot and understand metadata and lineage |
Intended audience
Data engineers, data analysts.
Prerequisites
Completion of the "Big Data and Machine Learning Fundamentals" course Ref. GCD or equivalent knowledge.
Certification
We recommend you take this course if you want to prepare for certification as a "Google Cloud Professional Data Engineer".
Comment passer votre examen ?
Comment passer votre examen ?
Practical details
Teaching methods
Training in French. Official course material in English and digital format. Good understanding of written English.
Course schedule
1 Introduction to data integration and Cloud Data Fusion
- Understand the need for data integration.
- List the situations/cases where data integration can help companies.
- List available data integration platforms and tools.
- Identify data integration challenges.
- Understand how to use Cloud Data Fusion as a data integration platform.
- Create a Cloud Data Fusion instance.
- Discover the basic framework and main components of Cloud Data Fusion.
2 Building pipelines
- Understanding Cloud Data Fusion architecture.
- Define a data pipeline.
- Understand the DAG representation of a data pipeline.
- Learn how to use Pipeline Studio and its components.
- Design a simple pipeline using Pipeline Studio.
- Deploy and run a pipeline.
3 Building complex pipelines
- Perform branching, merging and joining operations.
- Execute the pipeline with execution arguments using macros.
- Working with error handlers.
- Execute pre- and post-pipeline runs using actions and notifications.
- Plan pipeline execution.
- Import and export existing pipelines.
4 Pipeline execution environment
- Understand the composition of a runtime environment.
- Configure your pipeline's execution environment, logging and metrics.
- Understand concepts such as calculation profile and provisioner.
- Create a calculation profile.
- Create pipeline alerts.
- Monitor the running pipeline.
5 Building transformations and preparing data with Wrangler
- Understand how to use Wrangler and its main components.
- Transform data using Wrangler's user interface.
- Transform data using CLI directives/methods.
- Create and use user-defined directives.
6 Connectors and streaming pipelines
- Understand data integration architecture.
- List the different connectors.
- Use the Cloud Data Loss Prevention (DLP) API.
- Understand the reference architecture of streaming pipelines.
- Build and run a streaming pipeline.
7 Metadata and data lineage
- List metadata types.
- Differentiate between commercial, technical and operational metadata.
- Understand data lineage.
- Understand the importance of maintaining data lineage.
- Differentiate between metadata and data lineage.
PARTICIPANTS
Data engineers, data analysts.
PREREQUISITES
Completion of the "Big Data and Machine Learning Fundamentals" course Ref. GCD or equivalent knowledge.
TRAINER QUALIFICATIONS
The experts who lead the training courses are specialists in the subjects covered. They are approved by the publisher and certified for the course. They have also been validated by our teaching teams in terms of both professional knowledge and teaching skills for each course they teach. They have at least three to ten years of experience in their field and hold or have held positions of responsibility in companies.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training course.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you have specific accessibility requirements? Contact Ms FOSSE, disability advisor, at the following address: psh-accueil@orsys.fr so that we can assess your request and its feasibility.
Data engineers, data analysts.
PREREQUISITES
Completion of the "Big Data and Machine Learning Fundamentals" course Ref. GCD or equivalent knowledge.
TRAINER QUALIFICATIONS
The experts who lead the training courses are specialists in the subjects covered. They are approved by the publisher and certified for the course. They have also been validated by our teaching teams in terms of both professional knowledge and teaching skills for each course they teach. They have at least three to ten years of experience in their field and hold or have held positions of responsibility in companies.
ASSESSMENT TERMS
Assessment of targeted skills prior to training.
Assessment by the participant, at the end of the training course, of the skills acquired during the training course.
Validation by the trainer of the participant's learning outcomes, specifying the tools used: multiple-choice questions, role-playing exercises, etc.
At the end of each training course, ITTCERT provides participants with a course evaluation questionnaire, which is then analysed by our teaching teams. Participants also complete an official evaluation of the publisher.
An attendance sheet for each half-day of attendance is provided at the end of the training course, along with a certificate of completion if the participant has attended the entire session.
Assessment of targeted skills prior to training.
Assessment by the participant, at the end of the training course, of the skills acquired during the training course.
Validation by the trainer of the participant's learning outcomes, specifying the tools used: multiple-choice questions, role-playing exercises, etc.
At the end of each training course, ITTCERT provides participants with a course evaluation questionnaire, which is then analysed by our teaching teams. Participants also complete an official evaluation of the publisher.
An attendance sheet for each half-day of attendance is provided at the end of the training course, along with a certificate of completion if the participant has attended the entire session.
TEACHING AIDS AND TECHNICAL RESOURCES
The teaching resources used are the publisher's official materials and practical exercises.
The teaching resources used are the publisher's official materials and practical exercises.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training course.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you have specific accessibility requirements? Contact Ms FOSSE, disability advisor, at the following address: psh-accueil@orsys.fr so that we can assess your request and its feasibility.
Dates and locations
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