How can your organization ensure data access and transparency? Measure yourself against this model, courtesy of our partners at Slalom.
Our latest dbt (data build tool) package helps accelerate your Mixpanel event analytics.
Through automated data pipelines, analysts can access the data they need and engineering teams can complete higher-value projects.
Looking for a Segment and Fivetran comparison? This article covers some fundamental differences between a specialized data integration tool and a customer data platform.
In a Slack discussion, the two CEOs explain why the Fivetran-dbt integration is great for data analytics engineering enthusiasts. After the recent launch of Fivetran dbt Transformations, both the Fivetran and Fishtown Analytics teams received questions about the newly available feature. (Fishtown is the team behind dbt.) Fivetran CEO George Fraser and Fishtown Analytics CEO Tristan Handy addressed those questions on Slack, and discussed the harmonious relationship between the two companies.
Growing heavy civil construction business brings on a modern data stack of Fivetran, BigQuery and Looker to gain a competitive edge. Want to hear more from Emery Sapp & Son's Clayton Hicklin? Join him and a number of other incredible data professionals at the 2020 Modern Data Stack Conference October 21-22. Register here.
Data scientists and engineers at the online data science education platform focus on attribution, customer lifetime value and the ideal customer profile.
This is the introduction to the Fivetran Architecture Academy series, in which we discuss the technological principles underlying how Fivetran works. Fivetran is at the forefront of automated data integration. Specifically, we believe that extracting, loading and transforming data should be effortless and involve a minimum of human intervention. This is reflected in the design philosophy of our automated data pipeline.
Make enterprise data more accurate, and instantly actionable, by adding automated data integration to your stack. Today’s enterprises and medium-sized companies are looking to ensure that critical business decisions are guided by rigorous data analysis. They have scaled up their analytics teams (composed of data engineers, data scientists and data analysts), and their IT departments have tried to meet the needs of those teams.