How I Passed GCP Data Engineer Certification Exam in Year 2021.

Recently, I have successfully pass my GCP Data Engineering Certification and i would like to share my experience over the forum which may help other members of the community.

Preparation Roadmap

Official Study Book for GCP-Data Engineering Certification is: Professional Data Engineering Study Guide, which can be ordered from here.

Week 1: — Study material.

Useful Videos

1. What is BigTable?: https://www.youtube.com/watch?v=Lq9uDOM4whI
2. What is Spanner?: https://www.youtube.com/watch?v=bUSU1e9j8wc
3. What is Streaming Analytics?:https://www.youtube.com/watch?v=JRHy8fUQLYQ

Reading Articles/Documents

1. BigTable Replication:(eventually consistent by default) you need to understand replication use case and how they are impacted by eventual consistency. Document Link that can be referred.
2. Spanner Replication: (strongly consistent) you need to understand how strong consistency are implemented with Spanner replicas. Document Link that can be referred.
3. Cloud Storage-data lake: you need to understand that how different GCP products can be used as part of an overall solution. Document Link that can be referred.
4. Cloud Data-Lifecycle Platform: you need to understand the role of the different products within the data lifecycle. Document Link that can be referred.

Labs for Practice

Find the labs on https://googlecourses.qwiklabs.com.

1. Do the Bigtable: Qwik Start — Command Line lab
2. Do the Cloud Spanner: Qwik Start -lab
3. Loading Taxi Data into Google Cloud SQL

Week 2: — Study material.

Useful Videos

1. How to Schedule Snapshot for Automatic Backup?: https://www.youtube.com/watch?v=Lq9uDOM4whI
2. How to control access for Cloud Storage?: https://www.youtube.com/watch?v=DYGFcIB23oA&list=PLIivdWyY5sqJcBvDh5dfPoblLGhG1R1-O&index=5
3. What are best practices for Block Storage?: https://youtu.be/QNpOm_nuZVU

Reading Articles/Documents

1. Cloud Storage features: you need to get familiar with all listed features of Cloud Storage. Document Link that can be referred here.
2. Google Transfer Appliance: you need to understand use case for Transfer Appliance and the basic procedure to use it. Document Link that can be referred here.
3. Transferring large volume of data to Google Cloud: you need to understand especially the different options available from Google, and the use case for each of them e.g. gsutil, Storage Transfer Service, transfer Appliance etc. Document Link that can be referred here.

Labs for Practice

Find the labs on https://googlecourses.qwiklabs.com. Some labs may not present over ‘qwiklabs’.

1. Do the ‘Google Cloud Storage — Bucket lock’ lab.
2. ‘Clean Up Unused and Orphaned Persistent Disks’ Lab.
3. ‘Cloud CDN’ Lab.
4. ‘Optimizing Cost with Google Cloud Storage’ Labs.

Week 3: — Study material.

Useful Videos

1. What is Map Reduce?: https://www.youtube.com/watch?v=43fqzaSH0CQ
2. What is a columnar database?: https://www.youtube.com/watch?v=8KGVFB3kVHQ
3. Creating a large Dataproc cluster with preemptible VMs: https://www.youtube.com/watch?v=iyqtKV0fnFc
4. Memory store in a minute: https://www.youtube.com/watch?v=ra3Vow3-HHg
5. High Availability and DR in Cloud SQL: https://www.youtube.com/watch?v=ghdleRvGExg

Reading Articles/Documents

1. What are Cloud Storage features: you need to get familiar with all the features listed here for Cloud Storage. Document Link that can be referred here.
2. Transferring large datasets to Google Cloud: you need to get familiar especially the different options available from Google, and the use case for each of them e.g. gsutil, Storage Transfer Service, transfer Appliance etc. Document Link that can be referred here.
3. What is Google Transfer Appliance: you need to get familiar with the use case for Transfer Appliance and the basic procedure. Document Link that can be referred here.

Labs for Practice

Find the labs on https://googlecourses.qwiklabs.com. Some labs may not present over ‘qwiklabs’.

1. Do the ‘Datastore:Qwik Start lab’ lab.
2. Do the ‘Building an IoT Analytics Pipeline on Google Cloud’ lab.
3. Do the ‘Do the Bigtable: Qwik Start — Hbase Shell lab’ lab.
4. Do the ‘Creating Date-Partitioned Tables in BigQuery’ lab.

Week 4: — Study material.

Useful Videos

1. What is analysing Geospatial data in BigQuery GIS?: https://www.youtube.com/watch?v=BUEmvT3p_zE
2. How to protect data with authorized views?: https://www.youtube.com/watch?v=8fNnqshJ2Nw
3. What are user defined functions: https://www.youtube.com/watch?v=c3dtgLWRycs

Reading Articles/Documents

1. Big Query explained: Storage Overview: you need to get familiar with the key concepts. Document link that can be referred here.
2. What are 7 best practices for production Dataproc clusters: you need to get familiar with each of these best practice of Dataproc. Document link that can be referred here.
3. Pub/sub and realtime analytics: you need to get familiar with how Pub/Sub complements data analytics. Document link that can be referred here.

Labs for Practice

Find the labs on https://googlecourses.qwiklabs.com. Some labs may not present over ‘qwiklabs’. But make sure you enroll in the Engineer Data in Google Cloud quest.

1. Do the ‘Explore and Create Reports with Data Studio’ lab.
2. Do the ‘ETL Processing on Google Cloud Using Dataflow and BigQuery’ lab.

Week 5: — Study material.

Useful Videos

1. What is Decision Pyramid: How to choosing the Right ML Tools?: https://www.youtube.com/watch?v=pm_-pVPvZ-4
2. What are the seven steps of machine learning?: https://www.youtube.com/watch?v=nKW8Ndu7Mjw
3. Learn Apache Beam in 15 minutes or less: https://www.youtube.com/watch?v=go8G0tW4KgU

Reading Articles/Documents

1. Beam Programming Guide: you need to get familiar with the key concepts. Document link that can be referred here.
2. ML Crash Course — basic ML terminology: you need to get familiar with the key concepts. Document link that can be referred here.
3. Pub/Sub: you need to get familiar with the key concepts. Document link that can be referred here.
4. ML topics on DE exam — Miscellaneous notes: you need to get familiar with the key concepts. Document link that can be referred here.

Labs for Practice

Find the labs on https://googlecourses.qwiklabs.com. Some labs may not present over ‘qwiklabs’. But make sure you enroll in the Engineer Data in Google Cloud quest.

1. Do the ‘Cloud Composer: Copying BigQuery Tables Across Different Locations’ lab.
2. Do the ‘Creating a Data Transformation Pipeline with Cloud Dataprep’ lab.

Week 6: — Study material.

Useful Videos

1. What is Cloud TPU?: https://www.youtube.com/watch?v=pm_-pVPvZ-4
2. What is Tensorflow Playground ?: https://www.youtube.com/watch?v=nKW8Ndu7Mjw
3. How to integrating 4 Machine Learning APIs: https://www.youtube.com/watch?v=JlzvXRegkOU
4. Awesome GCP — walkthrough of sample exam questions as needed: https://www.youtube.com/channel/UCIGDDqu5DzlaaC4XzXj_4-A

Reading Articles/Documents

1. Kubeflow use cases: you need to get familiar with the basic use cases for Kubeflow. Document link that can be referred here.
2. Best practices for ML optimization on Google Cloud: you need to understand how the different tools in Google Cloud are used in an ML project. Document link that can be referred here.

Practice Test:-

1. Test1
2. Test2
3. Test3
4. Test4
5. Test5
6. Test6

Thank you!! All the best for your preparation.