Grab your thinking cap: Roadmap for the Data+ track

5 days left for the Learn to Earn Cloud Challenge (depending on your time zone) and all eyes are on the thinking cap! Completing any two of these games along with the new Data+ badge to be eligible!

Let’s take a Qwik look at the roadmap of the 5th and final game of this challenge…


In this game you’ll learn next-level data skills to add to your resume. Complete these 12 labs to climb the leaderboard:

  • Start the Data+ challenge with the Introduction to SQL for BigQuery and Cloud SQL lab where you will learn to distinguish databases from tables and projects.
  • Move on to the Dataflow: Qwik Start — Template lab in which you will create a streaming pipeline using one of Google’s Cloud Dataflow templates.
  • Next in the Dataprep: Qwik Start Lab you will learn to use Dataprep to manipulate a dataset.
  • In Using BigQuery in the Google Cloud Console lab you will query public tables and load sample data into BigQuery using the GCP Console.
  • Use BigQuery to troubleshoot common SQL errors, query the data-to-insights public dataset, use the Query Validator, and troubleshoot syntax and logical SQL errors in the Troubleshooting Common SQL Errors with BigQuery Lab.
  • Learn how to create a Data Fusion instance and deploy a sample pipeline in the Getting Started with Cloud Data Fusion Lab.
  • Then, learn how to use a bash script to download selected data from a large public data set that is available on the internet with the Ingesting Data Into The Cloud Lab.
  • Simulate a real-time real world data set from a historical data set with the Processing Data with Google Cloud Dataflow lab.
  • Learn how to connect Google Data Studio to Google BigQuery data tables, create charts, and explore the relationships between dimensions and measures in Explore and Create Reports with Data Studio lab.
  • Use Machine Learning (ML) to analyze the public NCAA dataset and predict NCAA tournament brackets with the Bracketology with Google Machine Learning lab.
  • Wrap up this game by learning to explore millions of New York City yellow taxi cab trips available in a BigQuery Public Dataset, create a ML model inside of BigQuery to predict the fare, and evaluate the performance of your model to make predictions with the Predict Taxi Fare with a BigQuery ML Forecasting Model.

So follow the road map and make your way to the next step in your Google Cloud learning journey… and pick up a cap along the way!