Connecting GA data sets to Google BigQuery (BQ) gives marketers control over their data sets access to advanced modelling, analysis, and activation capabilities. Huge amounts of data can be stored in BQ, a warehouse on the Google Cloud Platform. For better analytical performance, it supports data warehouses and queries billions of rows in seconds. You should know how to integrate shopify to google bigquery.
Spreadsheets are already starting to give way to Google BQ in companies that need to analyse more sophisticated data. With the help of this specialist tool, you can swiftly transition to the most sophisticated business intelligence applications, such as Tableau, Looker, and Google Data Studio, and fast obtain meaningful insights from raw data.
Why Is Google BigQuery Useful For Digital Marketers
The following are some ways that Google BQ makes the world of marketing data analysis simpler, clearer, and less frustrating.
Process Large Datasets
For digital marketers dealing with regularly updated datasets that include multiple rows and columns, Google BQ is the ideal tool.
With its drag-and-drop interface and highly optimized technological design, this cloud-based platform makes it simple to extract insights from your data without needing to spend hours coding. As a result, even when working with datasets that span terabytes, you may anticipate rapid data analysis. It is very important to know about the process to move ShipHero data to Google BigQuery.
Keep All of Your Historical Data in One Location
It is infuriating to work with marketing solutions that only provide a restricted amount of past data. Frequently, even companies who promise extra months when particular apps are introduced to their APIs are not up to par.
One excellent illustration is the Google Search Console, which offers 16 months of extra historical data with Super metrics for Google Sheets in addition to six months of historical data with the conventional interface.
This is where Google BQ comes into play, giving you the ability to centrally save all of your history data across all platforms. You obtain a vast library as a result, making it easier to manage your data, get insightful insights instantly, and conduct smooth analysis.
Combine Information from Various Sources
Bringing and storing all of your data in one location makes data-driven analytics in the contemporary, fast-paced world easier. In the end, you can devote all of your attention and energy on reporting and analysing data for better marketing outcomes.
Everything may be stored in Google BQ, a reliable data warehouse that includes pre- and post-conversion data, ad data, and site analytics data.
Automatically Refresh Data
The process of manually updating the data snapshots is quite time-consuming and ineffective for digital marketers who use Spreadsheets for data analysis and reporting.
These datasets can be automatically refreshed on a regular basis with BigQuery. The strong API linkages to backend systems make this possible. While your dashboards continue to display the most recent data, you may focus on other important tasks.
Analyze data on-the-spot
In order to obtain insightful information, ad hoc data analysis entails arbitrarily slicing and dicing your data, generating unique metrics from primary fields, organizing these dimensions into hierarchical groups, and applying sophisticated filters to visuals.
Connecting BigQuery to your data analysis or visualization tool will allow you to execute this activity easily in addition to other usual analysis chores.
What is Google BigQuery
Google’s BigQuery stores data. BigQuery, part of Google Cloud Platform, lets you host and use large databases at low cost and high performance. BigQuery can analyse geospatial data and build machine learning models, among other things.
Google Analytics and BigQuery
Google Analytics native BigQuery integration lets you export raw analytics data to this warehouse. Exported data can also come from Google Ads or Salesforce. You can use this raw data in each scenario, but BigQuery’s actual value is in its ability to form associations between databases and exploit each one independently. We think a data warehouse like BigQuery can integrate all your data sources and eliminate data silos.
How Can BigQuery Benefit Your Business
BigQuery may assist your firm in analysing and maximizing the value of its data to assist with marketing and business choices. It will put you ahead of the curve when it comes to coming up with fresh approaches to working with and utilizing your data.
Recognize your data
You’ll learn more about the structure and storage of Google Analytics data as you work with BigQuery. Hit-level data in the warehouse and session-based online reports, for instance, differ significantly. Understanding this distinction will help you make the most of your data.
Accelerate the Reporting Process
In a handful of seconds, BigQuery can process billions of data and provide an accurate answer because of Google’s lightning-fast cloud-based architecture. For example, you may use Google App Scripts to automate the execution of queries, store the results to an automatically updated database, and use Data Studio to view the results. Compared to the traditional GA reports, this technique can frequently provide results more quickly and conveniently.
More in-depth analysis is possible by using this warehouse to explore Google Analytics data. Using your unprocessed analytics data, creating your own goals, KPIs, dimension-based classifications, etc. BigQuery is an affordable solution that enables you to use the data from your business to conduct in-depth ad hoc analysis.