Google Professional Data Engineer Practice Tests

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Google Professional Data Engineer Practice Tests

Three practice exams having scenarios related to Data Engineering aspect of GCP which enable you to master Google Professional Data Engineer Certification Exam

  • Assess yourself for the Google Professional Data Engineer Certification Exam
  • Ensure that you are fully prepared for the exam
  • Appear for these exams only when you feel you are ready to take the exam

Topics covered in the exams –

  • Storage – BigQuery, BigTable, Spanner, Cloud DataStore, Cloud Storage etc.
  • Processing – DataProc, DataFlow, Spark, Beam etc.
  • Analysis – BigQuery, Hive etc.
  • Visualization – DataStudio
  • Ingestion – Cloud Pub/Sub, Kafka etc.
  • Modeling – ML APIs, ML Concepts, AI Platform, Accelerator, Troubleshooting etc.
  • Misc – Dataprep, Data Catalog, Auto Scaling, Stackdriver, IAM etc

Note:

This course is not dump of the actual exam but it is for assessing your preparation before the real exam.

Below are our more courses –

  1. Big Data Crash Course | Learn Hadoop, Spark, NiFi and Kafka
  2. Big Data For Architects | Build Big Data Pipelines and Compare Key Big Data Technologies
  3. Google Data Engineer Certification Practice Exams
  4. Setup Single Node Cloudera Cluster on Google Cloud

What can a data engineer certification do for you? The need for data engineers is constantly growing and certified data engineers are some of the top paid certified professionals. Data engineers have a wide range of skills including the ability to design systems to ingest large volumes of data, store data cost-effectively, and efficiently process and analyze data with tools ranging from reporting and visualization to machine learning. Earning a Google Cloud Professional Data Engineer certification demonstrates you have the knowledge and skills to build, tune, and monitor high-performance data engineering systems.

Who this course is for:

  • Anyone who wants assess the Google Professional Data Engineer exam before appearing for the actual exam
  • Anyone interested in becoming a data engineer or data analyst

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