Google Professional Data Engineer (GCP Cheat Sheet – Blog

Data engineers allow corporations to manage all aspects of data science, including advanced analytics and insight generation. This role requires you to have the right skills and knowledge. This cheat sheet will help you on your journey to become a GCP Professional data engineer. This means that trusting and having reliable knowledge is essential to a good job. For better revision, you will need to have accurate study resources and in-depth information.
This cheat sheet will cover the basic requirements of a professional data engineer and then provide the best resources to help you prepare for the exam. Let’s get started with the basics.
Google Professional Data Engineer (GCP).
Before we get to the exam requirements, let’s first understand the basics of the exam. GCP Professional Data Engineer helps data-driven decisions by collecting, transforming, publishing, and publishing data. Data engineers are responsible for designing, operating, securing, and monitoring data processing systems, with a special emphasis on security and compliance. You will also need to consider the scalability, efficiency, reliability, fidelity, flexibility and portability. The Google Cloud Certified Professional Data Engineer exam evaluates your abilities in a variety of areas, including:
First, designing data processing systems
Second, Operationalizing and building data processing systems
Third, Operationalizing machine-learning models
Lastly, Ensuring solution quality
Basic Skill Requirements
There are certain skills you need to be a Google Cloud Platform Data Engineer (GCP Data Engineer)
First, proficiency in Python or SQL languages
Understanding the cloud platforms is second.
Third, understanding Machine Learning (ML), concepts
Fourth, the basics of Java and Scala programming
Knowledge of SQL and NoSQL databases is then required.
Finally, the principles of data warehousing/data modeling
GCP Exam Prerequisites
For any exam, the pre-requisites section is crucial. You must ensure that you have reviewed the entire section in order to be sure you have met all requirements.
First, you must have scalability.
Second, you should be able design and monitor data processing systems, with a special emphasis on security.
Finally, a data engineer must be able leverage and continuously train existing machine learning models.
Quick Preparation Guide: Google Cloud Certified Professional data Engineer
This guide will assist you in your final revision for GCP Data Engineer exam. It will also provide valuable study resources and methods. You will also find sections that help you locate the topic you are interested in. Let’s get started with the quick guide.
Exam Objectives
Exam objectives are broken down into sections, which allows you to review all topics in a sequential order. This will allow you to identify weak and strong areas. Then, you can start revising accordingly. You can also review the exam guide to see if your skills match the topics of the exam. The following are the main topics for the GCP Cloud Certified Professional Data Engineer:
1. Designing data processing systems
1.1 Selecting the right storage technology
Mapping storage systems to business needs (Google Documentation:Best practices in enterprise organizations)
Data modeling (Google Documentation,Schema and Data Model,Data model)
Tradeoffs involving latency, throughput, transactions (Google Documentation:Database consistency)
Distributed systems (Google Docation: Using clusters for large scale technical computing in the cloud. Choosing the right architecture to distribute global data is key.
Schema design (Google Documentation:Designing your schema)
1.2 Designing data pipelines.
Data p

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