What is Google BigQuery and why should marketers use it?

Explore the possibilities BigQuery opens for your company and discover use cases and best practices.

  • Consolidate all your data in one place — no more silos
  • Automate your marketing reports — break the routine
  • Develop your skillset to become a data-driven marketer
  • Learn more about Google Cloud and its possibilities
  • Discover the complete analytics process from data collection to data visualisation

Google BigQuery Explaining- Data Analytics Infrastructure

Working with your analytics tools like GA or Adobe Analytics comprises two parts — data collection and data visualisation. In most cases, you can't interfere with how your data is collected, stored and moved during the analytics process. But with Google BigQuery, you can collect the data, consolidate it in a single place, store it within the warehouse, work with some data formula/function to transform the data you need, and eventually visualise the data.

Data Analytics Infrastrcuture. The slide is taken from CXL for reference.
Data Analytics Infrastrcuture. The slide is taken from CXL for reference.
Intro to GCP. The slide is taken from CXL for reference.
Cloud Payment Schema.
BigQuery Data Strucutre.

Google Cloud Platform Account Set up

To login into the Google Cloud Platform, you need to visit this link and set up an account. You will be asked to insert your credit card details, but we are using free BigQuery for learning purposes in this article, and it can function without a credit card.

Click Get started for free to complete your setup.
Google Cloud Platform Dashboard.
Pin the everyday use of the features on your left nav menu.

Google BigQuery Interface

BigQuery has features built-in that allow you to recap all the works you did, proactively save specific queries and share them with others. Here're the features you need to take a look at:

  • Query history- include the text of all queries that you have run previously, but note that this history is limited to 1,000 queries and looks back up to 6 months.
  • Saved queries- save the specific queries that are commonly used.
  • Job history- show the record of what was going on in the BigQuery. For example, automated imports from Cloud Storage with the help of Cloud Function to BigQuery tables.
  • Transfers- activate a transfer of data from different Google services to Google BigQuery.
  • Scheduled queries- If you have an automating dashboard, this feature will help you schedule some queries and renew your data in a specific timeframe you set.
  • Reservations- This is a new feature that is still in beta. Reservation has two pricing tiers: on-demand model pricing and flat-rate pricing. On-demand pricing lets you pay the amount of data you consume, whereas Flat-Rate pricing refers to a stable monthly cost of BigQuery that does not limit the amount you use. The large enterprise would have preferred flat-rate pricing over the on-demand.
  • BI Engine- is a business intelligence engine that makes your analysis faster, which we will dive into more details later.
  • Resource- let you explore the public dataset, pin/add an available project, and connect via API.
  • Query editor: let you write your query

Google BigQuery Sandbox — Add Public Dataset

So, let's explore BigQuery Sandbox. In Sandbox mode, you can try BigQuery in two ways:

  • Public data set/ Your own data for 60 days storage
Explore public datasets for testing.
Select the public datasets you need.
  • Test the data sets to understand further if it can be helpful.
  • Need some temporary analysis with SQL but don't want to sign on for a free trial
Create Dataset

Wrapping up

Google BigQuery is a powerful tool for marketers looking to get the most out of their data. It provides easy, high-speed querying and analysis of large datasets in seconds. Google BigQuery helps you get insights from your data quickly, without having to worry about managing servers or getting slowed down by analytics software.



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janet wong

“Everything is theoretically impossible, until it is done.” Robert A. Heinlein.