Chapter 16: BigQuery: Introduction
In this chapter we’ll cover an Introduction to BigQuery: What BigQuery is, when we should or should not use this tool, and the limitations of the current data-stack in Looker Studio.
We’ll also cover how we can bring in and work with data in BigQuery, as well as how to connect it to Looker Studio, and finally, we’ll take a look at some case studies on how BigQuery is used.
16.1. Introduction to BigQuery
Welcome to the advanced Looker Studio course, where we'll dive into the world of BigQuery. This lesson will help you understand what BigQuery is, why it's interesting, and how it might fit into your business. By the end of this lesson, you'll be equipped with the knowledge to decide whether or not BigQuery is right for you and your organization.
Why Consider BigQuery?
Before we jump into the specifics of BigQuery, let's discuss why you might want to consider it in the first place. You may have heard about others using it and wondered if it's worth exploring for your own purposes.
Limitations of Your Current Data Stack
Every data stack has its limitations. Whether you're currently using Looker Studio or another tool, understanding these limitations can help you determine if BigQuery could be a valuable addition to your arsenal.
What is BigQuery?
BigQuery is a powerful tool that can help overcome some of these limitations. In this section, we'll explore what makes BigQuery unique and how it can benefit your data analysis process.
When Should You Use BigQuery?
Not every situation calls for using BigQuery. In this part of the lesson, we'll discuss when incorporating this tool might make sense for your business needs.
Bringing Data into BigQuery
If you decide that utilizing BigQuery is a good move for your organization, you'll need to bring your data into it so that you can work with it effectively. We'll cover various methods for importing data into this platform.
Working with Data within BigQuery
Once your data is inside BigQuery, there are numerous ways to manipulate and analyze it. We'll go over some key techniques for working with data within this environment.
Connecting Looker Studio to BigQuery
To get even more value from using both tools together, we'll discuss how to connect Looker Studio to BigQuery. This connection will enable you to take full advantage of the capabilities offered by both platforms.
Case Studies
Finally, we'll explore some real-life case studies that demonstrate the power and potential of combining Looker Studio and BigQuery. By examining these examples, you'll gain a better understanding of how these tools can work together to create valuable insights for your business.
16.2. Why Do We Need BigQuery?
16.3. What is BigQuery?
16.4. BigQuery Pricing Explained
16.5. How Fast is BigQuery?
16.6. When Should we Consider BigQuery?
16.7. Google Sheet vs BigQuery Data Pipeline
16.8 Importing Data into BigQuery
16.9. Importing Google Analytics Data to BigQuery
16.10 Importing Data from Marketing Tools into BigQuery
16.11. Working with Data in BigQuery with SQL
16.12. Connecting Looker Studio to BigQuery
16.13. BigQuery & Looker Studio Case Study: Affiliate Performance Dashboard
16.14. BigQuery & Looker Studio Case Study: Labor Performance
16.15. Shopify, Klavyio RFM Segmentation with BigQuery ML
16.16. Store Inventory Capacity Outlook: BigQuery and Looker Studio Case Study
16.17. Location Exploration Case Study with BigQuery and Looker Studio
16.18. Discussion: BigQuery and BigQuery ML Use Cases
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