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Why Hiring a Data Analyst Won't Solve Your Business Problems

As businesses increasingly leverage data-driven decision making, the ability to use and understand data at the company-wide level becomes mission critical. While tech behemoths like Netflix, Airbnb, and Spotify have strong data cultures built over the last decade, most companies often face challenges getting up and running with data.

George Fraser and Tristan Handy Discuss the Fivetran-Fishtown Partnership

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.

Emery Sapp & Sons Builds Civil Infrastructure, Not Data Pipelines

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.

What Is the Architecture of Automated Data Integration?

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.

The Importance of Automation to the Enterprise Data Stack

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.