Today, the fast developed society is full of chance and challenge, so all of us may face the problem how to get more qualified and competent. You may have heard that Professional-Data-Engineer certification has been one of the hottest certification which many IT candidates want to gain. In fact, Google Cloud Certified Professional-Data-Engineer is incredibly worthwhile. The characters reflected by the person who gets certified are more excellent and outstanding. In work, they may shows strong dedication and willingness, and have strong execution to do project. Besides, companies also prefer to choose the people who are certified, because they can bring more economy benefit with high efficiency. So in order to get a better job and create a comfortable life, you should pay attention to the Professional-Data-Engineer certification. Now, I think it is a good chance to prepare for the Professional-Data-Engineer exam test.

Following are some reference material for actual Google Professional-Data-Engineer exam test

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:

• Custom Model building Using SQL in BigQuery ML
• Serverless Messaging Using Cloud Sub/Pub
• Introduction to Data Engineering
• Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
• Production ML Pipelines and use of Kubeflow
• Serverless Data Processing with Cloud Dataflow
• Bigtable Streaming Features and High-Throughput BigQuery
• Cloud Dataflow Streaming Features
• Advanced BigQuery Performance and Functionality
• Building a Data Warehouse
• Prebuilt ML Models APIs for Unsaturated Data
• Big Data Analytics with Cloud Al Platform Notebook
• Custom Model building Utilizing Cloud AutoML
• Performing Spark on Cloud Dataproc
• Introduction to Building Batch Data Pipelines
• Introduction to Processing Streaming Data
• Creating a Data Lake

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.

The Professional Data Engineer exam is the industry-standard exam that proves the candidate’s ability to do data-driven decision-making by assembling, transforming, and publishing data. If you are rooting for a career in data engineering, you should take this test. It will lead you to attain the Professional Data Engineer certification issued by Google.

Understanding functional and technical aspects of Google Professional Data Engineer Exam Building and operationalizing data processing systems

The following will be discussed here:

• Transformation
• Monitoring pipelines
• Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
• Awareness of current state and how to migrate a design to a future state
• Lifecycle management of data
• Validating a migration
• Provisioning resources
• Storage costs and performance
• Building and operationalizing pipelines
• Data acquisition and import
• Adjusting pipelines
• Integrating with new data sources
• Testing and quality control
• Data cleansing
• Building and operationalizing storage systems
• Batch and streaming
• Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore)
• Building and operationalizing processing infrastructure
• Building and operationalizing data processing systems

Reference: https://cloud.google.com/certification/data-engineer

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