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Data Engineering

9 Labs · 49 Credits · 7h 5m

Cert Exam Practice Data engineering

This Quest is intended to provide hands-on practice for those preparing for the Google Cloud Certified Professional Data Engineer Certification. Students will get hands-on exposure to a wide range of Google Cloud Services and techniques which are closely mapped to the topic areas in the certification test. Be aware that while practice with these labs will increase your knowledge and abilities in these topic areas, you will need other preparation to succeed in the question and answer test itself (such as work experience).

Weather Data in BigQuery

In this lab you analyze historical weather observations using BigQuery and use weather data in conjunction with other datasets. This lab is part of a series of labs on processing scientific data.

Icon  fundamental fundamental 5 Credits 35 Minutes

Analyzing Natality Data Using Datalab and BigQuery

In this lab you analyze a large (137 million rows) natality dataset using Google BigQuery and Cloud Datalab. This lab is part of a series of labs on processing scientific data.

Icon  advanced advanced 7 Credits 30 Minutes

Predicting Baby Weight with TensorFlow on Cloud ML Engine

In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.

Icon  expert expert 9 Credits 1 Hour 30 Minutes

Bigtable: Qwik Start - Hbase Shell

This hands-on lab will show you how to use the HBase shell to connect to a Cloud Bigtable instance.

Icon  intro introductory 1 Credit 30 Minutes

Run a Big Data Text Processing Pipeline in Cloud Dataflow

In this lab you will use Google Cloud Dataflow to create a Maven project with the Cloud Dataflow SDK, and run a distributed word count pipeline using the Google Cloud Platform Console.

Icon  advanced advanced 7 Credits 40 Minutes

Dataproc: Qwik Start - Console

This page shows you how to use the Google Cloud Platform Console to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster.

Icon  intro introductory 1 Credit 30 Minutes

Building an IoT Analytics Pipeline on Google Cloud Platform

This lab shows you how to connect and manage devices using Cloud IoT Core; ingest the steam of information using Cloud Pub/Sub; process the IoT data using Cloud Dataflow; use BigQuery to analyze the IoT data.

Icon  advanced advanced 7 Credits 50 Minutes

Working with Google Cloud Dataprep

Cloud Dataprep is Google's self-service data preparation tool. In this lab, you will learn how to use Cloud Dataprep to clean and enrich multiple datasets using a mock use case scenario of customer info and purchase history.

Icon  fundamental fundamental 5 Credits 1 Hour

Classify Text into Categories with the Natural Language API

In this lab you’ll learn how to classify text into categories using the Natural Language API

Icon  advanced advanced 7 Credits 1 Hour