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Exporting data from Google Analytics—or Universal Analytics—to Google BigQuery: Saving your historical data

After nine years of dedicated service, Google Analytics— or Universal Analytics—will finally step down and give the crown to its successor—Google Analytics 4. Google Analytics has been around for 15 years, and for the very first time, Google gives the platform a complete makeover. This time we’re not only talking about a brand new UI ...

Apr 19, 2022 | 6 minute read

How to query data in cloud storage from BigQuery

It seems like data lakes are all the rage these days. Why is that? And more importantly, if you work with marketing data, why should you care? And if you do care, but don’t know how to query data in your cloud storage bucket from BigQuery, how would you go about doing that? In this ...

Apr 28, 2021 | 9 minute read

How to query Google Sheets data in BigQuery

When I first started using Google Sheets, I thought it was a joke. My first experience with it back in 2010 was in high school when I was in my Intro to Accounting class. My exact thoughts were, “There’s no way Google can pack as much functionality into a web browser as Microsoft does into ...

Mar 17, 2021 | 6 minute read

How we use Supermetrics and BigQuery at Supermetrics

Like most fast-growing SaaS companies, we use a ton of data to track and spur our growth at Supermetrics.  A big part of the credit here goes to our 3-person growth team, who is in charge of tracking and analyzing our marketing and sales performance as well as sharing their insights with the rest of ...

Jul 1, 2020 | 6 minute read

3 steps to building custom schemas to a data warehouse

While you’ve always been able to use common data extraction schemas in Supermetrics for BigQuery, you might occasionally also want to pull metrics that aren’t covered by a standard schema. To tackle this need, we’ve launched a new feature: the schema builder. The schema builder offers an easy way for you to create custom data ...

May 27, 2020 | 4 minute read

redshift vs. snowflake vs. bigquery

Because of the increasingly fragmented marketing data landscape, data-driven marketers now need specialized tools to reduce the time it takes for data to be processed into information. While marketing data warehouses are not a new concept, the legacy model to implement them has serious drawbacks. Customers need to first purchase large capacity hardware, install and ...

Mar 24, 2020 | 8 minute read

10-MINUTE-READ · By Jessi Carr & Eddie Zaldivar (Inseev Interactive) Inseev Interactive is a San Diego-based performance digital marketing agency founded in 2013. Although they were launched with a primary focus on SEO services, they quickly expanded into a variety of other services, including paid media management, CRO consulting, and affiliate management. Inseev has always been ...

Feb 10, 2020

6-MINUTE READ · By Andy Kozak Google BigQuery presents a new way to store and analyze data extracted from different data sources. Utilizing the power of the Google Cloud Platform, larger data volumes and complex queries can get processed in minutes. Loading data into Google BigQuery is easy: Supermetrics for BigQuery provides native connectors for ...

Jan 27, 2020

6-MINUTE READ · By Riku Mikkonen With the amount of marketing data produced daily, demands presented for storage and computing power are on the rise. Many marketers are faced with insufficient capabilities and spend a lot of time waiting for reports. Could a marketing data warehouse using Google BigQuery be the solution they are looking ...

Jan 17, 2020

How to Compare PPC Campaign Performance Across Multiple Networks with BigQuery

8-MINUTE READ · By Misty Faucheux If you run PPC marketing campaigns across many different platforms, then you know the struggle of trying to consolidate your important data into a single location. In most cases, data is downloaded from, say, Facebook or Google Ads, and stored in a folder on someone’s computer or hosted drive. ...

May 21, 2019

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