GCP Data Engineer Certification – Cheat Sheet

  1. Home
  2. Cloud Computing
  3. GCP Data Engineer Certification – Cheat Sheet
GCP Data Engineer Certification - Cheat Sheet

The market for artificial intelligence and machine learning-powered solutions is expected to grow to $1,2 billion by 2023. As this demand is not fleeting and will continue to stay with us for a longer time, it becomes extremely essential to consider the business needs now and then in the future. Furthermore, the world has witnessed that the GCP data engineering role has evolved and now requires a larger set of skills. Well, this whole scenario boils us down to the most important thing i.e GCP Data Engineer Certification- Cheat Sheet. 

Therefore, in view to address the evolving skills set for the potential aspirants, the following article will be presenting the cheat sheet accompanying some major exam details. 

Why Take Google Cloud Certified Data Engineer Certification?

Data management, Data Analytics, Machine Learning, and Artificial Intelligence are all red-hot topics. And who does all of these better than Google?

Why choose GCP Data Engineer?

Acquiring a Google Data Engineer certification is not a bed full of thrones. In other words, it is not difficult to become Google certified. Google certification adds a meaningful impact on your career and job in the IT industry. It has been witnessing a good track record with positive value and benefits for both employees and employers. GCP encompasses the following benefits- 

  • First things first, it enhances the knowledge and understanding of technology and the product
  • Secondly, provides you an extra edge over other candidates
  • Subsequently, acts as proof of your continuous learning
  • In addition, recognizes you as a Google certified data engineer professional globally
  • Moreover, increases your chances of getting better opportunities and a higher pay scale

Now that we have acquired the benefits, we will move forward and focus on the necessary details for the Google Data Engineer certification.

GCP Data Engineer: Overview

The GCP Data Engineer exam is best suitable for individuals with an interest in data investigation. Candidates for the GCP Data Engineer certification exam assume roles for data-based decision making. The objective of the certification is the validation of the abilities of an individual for the collection, transformation, and publishing of data. 

Exam Details

The GCP Data Engineer certification exam comprises of multiple-choice and multiple-select format for the questions. The total duration of the exam is 2 hours, and candidates can choose the test center located at the google database.

The registration fee for the exam is USD 200, along with applicable taxes. The GCP Data Engineer certification exam is available in only four languages i.e., English, Portuguese, Japanese, and Spanish.

Exam Details for GCP Data Engineer Exam

Prerequisites

The prerequisites for the GCP Data Engineer certification exam is vital for every aspiring Data Engineer. And, the most prominent highlight for the GCP Data Engineer is that it doesn’t require any prerequisites. However, candidates need to fulfill the recommended experience required for the GCP Data Engineer certification exam.

So, one needs a minimum of three years of industry experience in data-based roles along with more than one year of practical experience in the design and management of solutions using GCP can be helpful. Also, another crucial prerequisite that candidates must fulfill for authenticating their eligibility is the candidate’s age. Candidates should be at least 18 years of age or more to appear for the examination. 

Course Outline

Before you begin your GCP Data Engineer journey, you should know about the course outline which includes various topics and subtopics that need special attention and consideration. The course outline helps the candidates to plan a positive outcome. Therefore, it is highly important to understand the course outline, so you can completely focus on the exam objectives during your Google data engineer certification preparation. The following domains that are covered in the exam:

Section 1: Designing data processing systems (22%)

1.1 Designing for security and compliance. Considerations include:

1.2 Designing for reliability and fidelity. Considerations include:

1.3 Designing for flexibility and portability. Considerations include

1.4 Designing data migrations. Considerations include:

Section 2: Ingesting and processing the data (25%)

2.1 Planning the data pipelines. Considerations include:

2.2 Building the pipelines. Considerations include:

2.3 Deploying and operationalizing the pipelines. Considerations include:

Section 3: Storing the data (20%)

3.1 Selecting storage systems. Considerations include:

3.2 Planning for using a data warehouse. Considerations include:

  • Designing the data model (Google Documentation: Data model)
  • Deciding the degree of data normalization (Google Documentation: Normalization)
  • Mapping business requirements
  • Defining architecture to support data access patterns (Google Documentation: Data analytics design patterns)

3.3 Using a data lake. Considerations include

3.4 Designing for a data mesh. Considerations include:

Section 4: Preparing and using data for analysis (15%)

4.1 Preparing data for visualization. Considerations include:

4.2 Sharing data. Considerations include:

4.3 Exploring and analyzing data. Considerations include:

  • Preparing data for feature engineering (training and serving machine learning models)
  • Conducting data discovery (Google Documentation: Discover data)

Section 5: Maintaining and automating data workloads (18%)

5.1 Optimizing resources. Considerations include:

5.2 Designing automation and repeatability. Considerations include:

5.3 Organizing workloads based on business requirements. Considerations include:

5.4 Monitoring and troubleshooting processes. Considerations include:

5.5 Maintaining awareness of failures and mitigating impact. Considerations include:

Google Cloud Platform

Notably, Google has become the ace of market space by providing standard services. Currently, every other Google cloud cheat sheet marks third or fourth among public cloud vendors creating tough competition to Amazon, Microsoft, and IBM. There is a slight difference in the definition of Google Cloud Platform depending on its spruce. However, the most general notion about GCP is that it is the collection of cloud computing services provided by Google. The architecture of GCP is based on the infrastructure used by Google internally for end-user products such as YouTube and Google Search. 

Products and Services on Google Cloud Platform

Google Cloud Platform cheat sheet is basically a compendium of products and services that are being offered. In other words, the ever-expanding portfolio of offerings by GCP is one of its most prominent highlights. We may think of the following products and services falling in the category of Google Cloud Platform.

  • Computing and hosting
  • Machine learning
  • Storage
  • Big data
  • Networking
  • Databases
  • Computing and Hosting Services

Summing Up

Well done on making it this far! We hope that this article has been helpful and hopefully a confidence booster for those taking the exam soon. The above-mentioned certification details and the GCP cheat sheet will provide some great advice and major areas to look for. Moreover, the cheat sheet will definitely act as your salvation to pass the exam without commercial experience.

Getting a GCP Data Engineer certification can help you validate and recognize your expertise on Google Cloud Platform. Are you thinking to give your skills a recognition? If yes, then check out our Google Cloud certification training courses. Top it off with hundreds of real-time exam practice papers on GCP Data Engineer certification.

Design and operate powerful big data and machine learning solutions using Google Cloud Platform. Prepare and become a Certified GCP Data Engineer Now!

Menu