Build a data warehouse

Build a Data Warehouse with BigQuery

Set up a data warehouse using data that is loaded and transformed in BigQuery, including creating Machine Learning models. Analyze data results using dashboards in Looker Studio.

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Who this is for

Data Engineers, Data Analysts, Data Scientists

What you will learn

How to build a data warehouse with BigQuery and how to build dashboards using Looker Studio

How you’ll deploy

Once you've signed up for Google Cloud, you can deploy through the console.

Overview

What is a data warehouse?

A data warehouse is a system used for the analysis and reporting of structured and semi-structured data from multiple sources. Organizations use data warehouses to consolidate, govern, and manage large amounts of business data for analysis. Many organizations are moving from traditional data warehouses that are on-premises to cloud data warehouses, which provide more cost savings, scalability, and flexibility

What is a cloud data warehouse?

A cloud services provider manages and hosts a cloud data warehouse solution. This gives you the inherent flexibility of a cloud environment along with more predictable costs, which can be based on usage or a fixed amount.

The up-front investment is typically much lower and lead times are shorter than on-premises solutions because you don’t have to buy hardware, thereby reducing CapEx.

What is the benefit of using BigQuery as a cloud data warehouse?

Companies of all sizes use BigQuery to consolidate siloed data into one location to perform data analysis and get insights across business data. This allows companies to make decisions in real time, streamline business reporting, and incorporate machine learning into data analysis to predict future business opportunities. BigQuery is a completely serverless and cost-effective cloud data warehouse that works across clouds and scales with your data. With business intelligence, machine learning and AI built in, BigQuery offers a unified data platform to store, analyze and share insights with ease.

What are common business use cases for a data warehouse like BigQuery?

Organizations use BigQuery to solve many business challenges with data. Common use cases of BigQuery as a data warehouse include analyzing marketing performance and building predictive audiences with Google Analytics data, real-time fraud detection, supply chain and operational analysis, demand forecasting and much more.

Solution Details

Data Warehouse with BigQuery

Deploys an example data warehouse with dashboards for you to explore how to create and analyze data.

Solution Architecture

Data lands in a Cloud Storage bucket
Cloud Functions facilitates the data movement
Data is loaded into BigQuery from an external table
Data is transformed in BigQuery using a stored procedure
Dashboards are created from the data to perform more analytics

Create a data warehouse with BigQuery

Google Cloud Experience Level

Beginner

Estimated deployment time

12 min

2 min to configure, 10 min to deploy

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