Following are the main advantages of using Google BigQuery for Google Analytics:
#1 BigQuery is specially designed for storing and querying big data (very large data sets, usually in terabytes).
#2 Since BigQuery is a data warehouse, it is an excellent tool for combining data from several data sources (like Google Analytics, Google Ads, Facebook etc) for the purpose of advanced reporting and analysis.
Thus the use of BigQuery helps in fixing data integration issues and enables robust cross-device and cross-platform data analysis and reporting.
#3 You can access raw hit level Google Analytics data in BigQuery which is not possible when you use the Google Analytics user interface.
For example, you can easily combine session-based dimensions (like source/medium) with user-level or page-level dimensions and metrics in BigQuery.
This is one of the biggest advantages of using BigQuery. It makes advanced data segmentation and analysis possible. It removes most of the limitations which come when you use the GA user interface or API for querying analytics data.
There are companies/analysts out there who use BigQuery a lot more than the GA user interfaces for querying data.
#6 There are many limitations when you query user-level data via the GA user interface.
For example, you can not query Goal Conversion rate data by users. But there are no such limitations with BigQuery. You can easily query user-level data in BigQuery.
#7 When you use the GA user interface, the goals and view filters do not work retroactively. The goal and filter data is collected and reported only from the date you first set up your tracking.
So if you want to calculate say goal conversion rate based on historical data then it is not possible. But BigQuery has no such limitations. You can calculate both goal completions and goal conversion rate based on historical data.
#8 BigQuery allows you to easily filter out or modify incorrect data from your analysis and reports. But when you use GA user interface to query data, you can not easily filter out incorrect data and you can not modify incorrect data. Data once skewed is skewed for good in the GA user interface.
#9 You can easily integrate BigQuery with data visualization tools like Google Data Studio and can thus easily visualize Google Analytics data.
#10 When you use BigQuery you can easily store and re-run queries thus saving a lot of time in data retrieval.
#11 BigQuery allows you to query even terabytes of data within seconds. Since BigQuery can execute SQL statements very fast, it can be used for realtime analytics.
#12 You can store a massive amount of data in BigQuery for relatively low prices.
#13 BigQuery is actually easy to learn and use thought it may look quite scary if you have never used it before.
#14 You don’t need to install or set up anything in order to use BigQuery. You can be up and running in a few minutes/hours.
#15 BigQuery is easy to use with multiple users and teams.
"How to use Digital Analytics to generate floods of new Sales and Customers without spending years figuring everything out on your own."
Here’s what we’re going to cover in this training…
#1 Why digital analytics is the key to online business success.
#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.
#4 Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
#5 The number 1 reason why conversion optimization is not working for your business.
#6 How to advertise on any marketing platform for FREE with an unlimited budget.
#7 How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
About the Author
Himanshu Sharma
Founder, OptimizeSmart.com
Over 15 years of experience in digital analytics and marketing
Author of four best-selling books on digital analytics and conversion optimization
Nominated for Digital Analytics Association Awards for Excellence
Runs one of the most popular blogs in the world on digital analytics
Consultant to countless small and big businesses over the decade
