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BigQuery for Data Analysts

Google Cloud Training

This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.

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This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.

Note: This course refreshes many basic topics covered in the From Data to Insights specialization about using BigQuery as a data analyst, and also covers new products like Dataform.

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What's inside

Syllabus

Course Introduction
This module introduces the course agenda.
BigQuery for Data Analysts
In the first module, we look at analytics challenges faced by data analysts and compare big data on-premises versus on the Cloud. We then introduce BigQuery, which is Google Cloud’s enterprise data warehouse, and review its features that make BigQuery a great option for your data analytics needs. And finally, we’ll learn from real-world use cases of companies transformed through analytics on the Cloud.
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Exploring and Preparing your Data with BigQuery
This module is all about exploring your data with SQL, or structured query language. We go from very simple select statements to more complex queries that explore various datasets.
Cleaning and Transforming your Data
In this module, we discuss principles about data integrity, and then we look at how to use SQL to clean, prepare, and transform your data. The last section of this module also briefly introduces other products like Dataprep, Cloud Data Fusion, Dataflow, Dataproc, and Dataform that can help with data preparation and transformation.
Ingesting and Storing New BigQuery Datasets
This module talks about ingesting and storing data into BigQuery native storage. We discuss when to use Extract and Load, versus Extract, Load and Transform, versus Extract Transform and Load approaches for loading data into BigQuery.We also cover external data sources, where you can run your query in BigQuery, but the data is hosted outside of BigQuery.
Visualizing Your Insights from BigQuery
This module is where all that hard work around ingesting, cleaning, preparing, and transforming your data comes to fruition as you get to visualize insights from your data by building insightful dashboards and reports. We start off with a little visualization theory and some best practices, and then look at tools, like Looker Studio and Connected Sheets, that can connect to BigQuery and help create impactful visualizations to capture and convey your insights. Although SQL is a powerful query language, programming languages such as Python, Java, or R provide syntaxes and a large array of built-in statistical functions that data analysts might find more expressive and easier to manipulate for certain types of data analysis. Such tools include open source web-based applications like Jupyter Notebooks, and so we discuss these as well.
Developing scalable data transformations pipelines in BigQuery with Dataform
Creating, maintaining, and versioning SQL pipelines is a lot of hard work. And many times, data analysts have to use multiple tools to achieve this. So in this module, we introduce Dataform, a new product that offers a unified end-to-end experience to develop, version control, and orchestrate SQL pipelines in BigQuery.
BigQuery Studio
In this module, we will start off by talking about what BigQuery Studio is, and the reason we built it. Next, we describe in a little more detail all the great capabilities that come with BigQuery Studio. In the end, we wrap up the module with a demo to walk you through the cool features and show you how to use it.
Summary
This module recaps the key topics covered in the course.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches how to analyze data and make business decisions with BigQuery
Covers data exploration, transformation, loading, and visualization
Shows how to build and version SQL pipelines in BigQuery with Dataform
Introduces BigQuery Studio and explains its capabilities
Provides hands-on labs and demos for practical application

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Activities

Coming soon We're preparing activities for BigQuery for Data Analysts. These are activities you can do either before, during, or after a course.

Career center

Learners who complete BigQuery for Data Analysts will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use their knowledge of data and machine learning to build models that can predict outcomes and solve problems. This course can be helpful for aspiring Data Scientists by providing a foundation in using BigQuery, a popular data warehouse platform. You will learn about data ingestion, transformation, and querying techniques that are essential for Data Scientists.
Data Architect
Data Architects design and implement data management solutions. This course can be helpful for Data Architects by providing a foundation in using BigQuery, a popular data warehouse platform. You will learn about data ingestion, transformation, and querying techniques that are essential for Data Architects.
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. This course can be helpful for Machine Learning Engineers by providing a foundation in using BigQuery, a popular data warehouse platform. You will learn about data ingestion, transformation, and querying techniques that are essential for Machine Learning Engineers.
Data Engineer
Data Engineers design, build, and maintain the systems that process and store data. This course can be helpful for aspiring Data Engineers by providing a strong foundation in using BigQuery, a popular data warehouse platform. You will learn about data ingestion, transformation, and querying techniques that are essential for Data Engineers.
Database Administrator
Database Administrators manage and maintain databases. This course can be helpful for Database Administrators by providing a foundation in using BigQuery, a popular data warehouse platform. You will learn about data ingestion, transformation, and querying techniques that are essential for Database Administrators.
Business Analyst
Business Analysts use data to understand business problems and develop solutions. This course can be helpful for Business Analysts by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to explore data, identify trends, and communicate insights to stakeholders, which are valuable skills for Business Analysts.
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. This course can be helpful for Marketing Analysts by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze customer data, identify trends, and measure the effectiveness of marketing campaigns, which are valuable skills for Marketing Analysts.
Sales Analyst
Sales Analysts use data to understand sales trends and identify opportunities. This course can be helpful for Sales Analysts by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze sales data, identify trends, and forecast sales, which are valuable skills for Sales Analysts.
Financial Analyst
Financial Analysts use data to evaluate financial performance and make investment decisions. This course can be helpful for Financial Analysts by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze financial data, identify trends, and make data-driven investment decisions, which are valuable skills for Financial Analysts.
Data Analyst
Data Analysts use their knowledge of data and analytical tools to help businesses make informed decisions and solve problems. This course can be a useful step towards becoming a Data Analyst by providing a foundation in using BigQuery, a powerful data analysis tool. Through hands-on labs and demos, you will learn how to ingest, transform, and query data in BigQuery, which are critical skills for Data Analysts.
Product Manager
Product Managers develop and manage products. This course can be helpful for Product Managers by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze product usage data, identify customer needs, and make data-driven decisions, which are valuable skills for Product Managers.
Risk Analyst
Risk Analysts use data to identify and manage risks. This course can be helpful for Risk Analysts by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze risk data, identify trends, and develop risk mitigation strategies, which are valuable skills for Risk Analysts.
Software Engineer
Software Engineers design, build, and maintain software applications. This course can be helpful for Software Engineers by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn about data ingestion, transformation, and querying techniques that can be applied to software development projects.
Project Manager
Project Managers plan, execute, and deliver projects. This course can be helpful for Project Managers by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to track project progress, identify risks, and communicate with stakeholders, which are valuable skills for Project Managers.
Auditor
Auditors examine financial records and statements to ensure accuracy and compliance. This course may be helpful for Auditors by providing a foundation in using BigQuery, a powerful data analysis tool. You will learn how to use BigQuery to analyze financial data, identify trends, and detect anomalies, which can assist in the auditing process.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in BigQuery for Data Analysts.
A cookbook style guide to BigQuery tools and services. Especially useful for readers who want to get a quick start with BigQuery. A more useful reference than current reading.
Comprehensive guide to Hadoop, a framework for distributed storage and processing of big data. While not specifically focused on GCP, this book will help readers understand the underlying concepts and technologies that are used in BigQuery.
Comprehensive guide to Spark, a fast and general-purpose distributed computing framework. While not specifically focused on GCP, this book will help readers understand the underlying concepts and technologies that are used in BigQuery.
Comprehensive guide to SQL, a language for querying and manipulating data. As this course uses SQL extensively, this book is recommended to help improve SQL skills.
Provides a comprehensive overview of the Python and JavaScript libraries for data visualization. While this course focuses on different tools, it is helpful for readers who want to learn more about data visualization in general.
Introduces readers to the Python libraries for data analysis, specifically Pandas. While this course focuses on different tools, it is helpful for readers who want to learn more about data analysis in general.
Comprehensive guide to machine learning with Python. While not specifically focused on BigQuery, this book will help readers understand the underlying concepts and technologies that are used in machine learning, which common use case for BigQuery.
Practical guide to deep learning with fastai and PyTorch. While not specifically focused on BigQuery, this book will help readers understand the underlying concepts and technologies that are used in deep learning, which common use case for BigQuery.
Comprehensive guide to natural language processing with Python. While not specifically focused on BigQuery, this book will help readers understand the underlying concepts and technologies that are used in natural language processing, which common use case for BigQuery.
Comprehensive guide to machine learning with scikit-learn, Keras, and TensorFlow. While not specifically focused on BigQuery, this book will help readers understand the underlying concepts and technologies that are used in machine learning, which common use case for BigQuery.

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