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Ensuring Solution Quality
The last section of the certification exam evaluates the ability of the learners to design for security & compliance, including identity & access management, legal compliance, data security, and privacy ensuring. Moreover, they should be able to ensure flexibility & portability, reliability & fidelity, as well as scalability & efficiency.
This course will show you how to manage big data including loading, extracting, cleaning, and validating data. At the end of the training, you can easily create machine learning and statistical models as well as visualizing query results. This program is a bit lengthy but you have to practice well to get the knowledge needed on the actual exam. These are the following modules covered in the course:
- Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
- Custom Model building Utilizing Cloud AutoML
- Big Data Analytics with Cloud Al Platform Notebook
- Building a Data Warehouse
- Prebuilt ML Models APIs for Unsaturated Data
- Advanced BigQuery Performance and Functionality
- Serverless Data Processing with Cloud Dataflow
- Creating a Data Lake
- Custom Model building Using SQL in BigQuery ML
- Performing Spark on Cloud Dataproc
- Introduction to Data Engineering
- Introduction to Building Batch Data Pipelines
- Introduction to Processing Streaming Data
- Production ML Pipelines and use of Kubeflow
- Serverless Messaging Using Cloud Sub/Pub
- Cloud Dataflow Streaming Features
- Bigtable Streaming Features and High-Throughput BigQuery
These modules involve everything the candidate requires for passing the Professional Data Engineer certification exam. Thus, you will not miss anything if you are taking this learning program keenly and apply the required knowledge in an appropriate way. You would end up getting a good score and achieving the Google Professional Data Engineer certification.
Reference: https://cloud.google.com/certification/data-engineer
Google Professional Data Engineer Certified Professional salary
The average salary of a Google Professional Data Engineer Certified Expert in
- India - 25,42,327 INR
- United State - 151,247 USD
- England - 115,632 POUND
- Europe - 135,347 EURO
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Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 22% | - Batch and streaming data processing design
|
| Topic 2: Operationalizing machine learning models | 26% | - Model deployment and monitoring
|
| Topic 3: Ensuring solution quality | 28% | - Reliability and performance
|
| Topic 4: Building and operationalizing data processing systems | 24% | - Data ingestion and integration
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