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From Data to Insights with Google Cloud Platform (DIGCP)

 

Course Overview

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course!

This three-day instructor-led class teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The course covers data loading, querying, schema modeling, optimizing performance, query pricing, data visualization, and machine learning.

Who should attend

This class is intended for the following:

  • Data Analysts, Business Analysts, Business Intelligence professionals
  • Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform

Certifications

This course is part of the following Certifications:

Prerequisites

To get the most out of this course, participants should have:

  • Basic proficiency with ANSI SQL

Course Objectives

This course teaches participants the following skills:

  • Derive insights from data using the analysis and visualization tools on Google Cloud Platform
  • Load, clean, and transform data at scale with Google Cloud Dataprep
  • Explore and Visualize data using Google Data Studio
  • Troubleshoot, optimize, and write high performance queries
  • Practice with pre-built ML APIs for image and text understanding
  • Train classification and forecasting ML models using SQL with BQML

Course Content

  • Module 1: Introduction to Data on the Google Cloud Platform
  • Module 2: Big Data Tools Overview
  • Module 3: Exploring your Data with SQL
  • Module 4: Google BigQuery Pricing
  • Module 5: Cleaning and Transforming your Data
  • Module 6: Storing and Exporting Data
  • Module 7: Ingesting New Datasets into Google BigQuery
  • Module 8: Data Visualization
  • Module 9: Joining and Merging Datasets
  • Module 10: Advanced Functions and Clauses
  • Module 11: Schema Design and Nested Data Structures
  • Module 12: More Visualization with Google Data Studio
  • Module 13: Optimizing for Performance
  • Module 14: Data Access
  • Module 15: Notebooks in the Cloud
  • Module 16: How Google does Machine Learning
  • Module 17: Applying Machine Learning to your Datasets (BQML)
Online Training

Duration 3 days

Price (excl. tax)
  • 1,950.— €
Digital courseware

Courseware language: English

Classroom Training

Duration 3 days

Price (excl. tax)
  • Germany: 1,950.— €
  • Switzerland: CHF 2,620.—
incl. catering Digital courseware

Courseware language: English

Schedule

Instructor-led Online Training:   Course conducted online in a virtual classroom.
FLEX Classroom Training (hybrid course):   Course participation either on-site in the classroom or online from the workplace or from home.
English
Time zone: Central European Summer Time (CEST)   ±1 hour
Online Training This is a FLEX course.
Time zone: Greenwich Mean Time (GMT)
Online Training Time zone: Greenwich Mean Time (GMT)
Online Training This is a FLEX course.
Time zone: Greenwich Mean Time (GMT)
Online Training This is a FLEX course.
Time zone: British Summer Time (BST)
2 hours difference
Online Training This is a FLEX course.
Time zone: Gulf Standard Time (GST)
3 hours difference
Online Training This is a FLEX course.
Time zone: Gulf Standard Time (GST)
7 hours difference
Online Training Time zone: Central Standard Time (CST)
Online Training Time zone: Central Daylight Time (CDT)
Online Training Time zone: Central Daylight Time (CDT)
Online Training Time zone: Central Daylight Time (CDT)
FLEX Classroom Training (hybrid course):   Course participation either on-site in the classroom or online from the workplace or from home.
Germany

Currently no local training dates available.  Request a date

Fast Lane Flex™ Classroom If you can't find a suitable date, don't forget to check our world-wide FLEX training schedule.