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Description

Welcome to
Google BigQuery for Marketers and Agencies
,

the Google BigQuery course that focuses on growing the technical knowledge and expertise of the marketing professional! This course is designed to bridge the gap between data analysis and digital marketing, and help you become a data-driven decision-maker. The course curriculum is put together in a progressive fashion, starting with an introduction to the most useful SQL queries for marketers, the role of both BigQuery and SQL in the larger data ecosystem, and then diving into two hands-on projects, where you can use everything you have learned.
By the end of the course, you will be able to:
Explore eCommerce and CRM user-level data in Google Analytics 360 (Project #1)
Visualize active queries and data tables in Google Data Studio (Project #2)
Explore semi-structured data with ARRAY_AGG, UNNEST and STRUCT
Filter values with the WHERE clause to identify insights
Ingest .CSV files and create permanent BigQuery tables
Combine multiple data tables with different types of JOINs - INNER, LEFT and RIGHT
Aggregate data with SUM, COUNT and GROUP BY
Create nested queries by using the WITH clause
What are the students who took the course saying?
"Very good course that shows you the basics of Google Big Query and its integration with Data Studio. The teacher shows you, step by step, the most important things to know with passion. I recommend this course to anyone who wants to take the first steps in the Big Query World."
- Massimo
"Very good course! I am glad that I have chosen it. Materials are easy for understanding. I was familiar with SQL before, but never worked with it in BigQuery. Now I know how to do it. Thank you very much!"
- Mariia
"This course is brilliant! really! I have been collecting data with Google Analytics for a few years. But this course taught how to take that data to the next step and now I can speak to what can be done with this data, and how it can be combined with other data sources etc. I especially like the way Lachezar explains key concepts that helped me put together the puzzle of GA data to BigQuery and from there to data visulization. Thanks Lachezar."
- Muhammad
Who is the instructor?
Lachezar Arabadzhiev is a digital markitech with 4+ years of experience in performance analytics and data visualization. Lachezar began his career as a digital marketer at Microsoft, but soon transitioned to the measurement and analytics world, where he has had the opportunity to work with major brands such as Air Canada, RBC, Kimberly-Clark, Mazda and HSBC.
Lachezar has been working with Data Studio and BigQuery since early 2017 and has built a wide variety of visualizations and automation flows. From performance-based dashboards with joined GMP sources (Google Analytics 360, Campaign Manager and Display & Video 360) to audience-driven segmentation views with user-level eCommerce data.
Lachezar is a certified GMP expert and an official speaker at the Canadian Google Data & Analytics Summit, 2018.
Who this course is for:
Digital Marketers
Campaign Managers
Performance Managers
Paid Media Managers
SEO/SEM Specialists
AdOps Specialists
Digital Analysts

What you'll learn

Become a technical marketer who is savvy in both digital marketing and data analysis

Exploring eCommerce and CRM user-level data in Google Analytics 360 (Project #1)

Write advanced queries with UNNEST, STRUCT and ARRAY_AGG

Query multiple tables with different type of JOIN statements - INNER, LEFT and RIGHT

Aggregate data with SUM, COUNT, GROUP BY and create aliases with AS

Understand subqueries by using the WITH clause

Visualize BigQuery tables and queries in Google Data Studio (Project #2)

Identify high-value customers and activate insights in Google Ads

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Getting started with Google BigQuery
7
1.1-Welcome to the Course!
1.2-What are Google BigQuery and SQL?
1.3-Setting up your BigQuery Sandbox account in Google Cloud Platform (GCP)
1.4-Disabling Editor Tabs
1.5-Navigating the Google BigQuery interface
1.6-Using the BigQuery Solutions Manual
1.7-Downloading the BigQuery course datasets
2-Creating and querying tables with SQL in Google BigQuery
8
2.1-Ingesting a CSV dataset into BigQuery and creating a table
2.2-Writing your first query with the SELECT, FROM and LIMIT clauses
2.3-Aggregating data with SUM, COUNT, GROUP BY and creating aliases with AS
2.4-Filtering values with WHERE and sorting data with ORDER BY
2.5-Understanding subqueries by using the WITH clause
2.6-Exporting your queries and results into a BigQuery table
2.7-Knowledge Check
2.8-Write a SUM Query
3-Exploring semi-structured data with ARRAY_AGG, UNNEST and STRUCT
6
3.1-What is an "Array" and why does it matter?
3.2-Grouping values together with STRUCT to define array hierarchy
3.3-Creating an array in an existing flattened table with ARRAY_AGG
3.4-Filtering and unnesting arrays with UNNEST
3.5-Knowledge Check
3.6-Create an ARRAY
4-Combing multiple tables with different JOIN statements
6
4.1-What are the different types of SQL JOINs?
4.2-Joining tables with a one-to-one relationship (INNER and LEFT JOINs)
4.3-Calculating percentage difference within a JOIN
4.4-Introducing multiple JOIN keys in many-to-many table relationships
4.5-Knowledge Check
4.6-Create an INNER JOIN
5-Project 1: Exploring eCommerce and CRM user-level data in Google Analytics 360
7
5.1-Setting up a public Google Analytics 360 dataset in BigQuery
5.2-Understanding website traffic sources and volume (Users, Sessions and Pageviews)
5.3-Re-grouping your traffic sources (Default Channel Groupings) with CASE
5.4-Part 1: Analyzing best-selling products and categories with WHERE and UNNEST
5.5-Part 2: Analyzing best-selling products and categories with WHERE and UNNEST
5.6-Identifying high-value customers to find CRM matches and activate insights
5.7-Practical Activity
6-Project 2: Visualizing BigQuery tables and queries in Google Data Studio
5
6.1-Connecting your BigQuery table to Data Studio
6.2-Visualizing your table by using different chart types
6.3-Writing Custom SQL queries directly in Data Studio
6.4-Using the Google Data Studio Explorer for generating insights faster
6.5-Practical Activity
7-Conclusion
3
7.1-Next Steps
7.2-The Beginner’s Guide to Using BigQuery with Google Data Studio
7.3-PROMO: Supermetrics for Google BigQuery