Let’s precisely define the different kinds of data repositories to understand which ones meet your business needs. October 29, 2020 A data repository serves as a centralized location to combine data from a variety of sources and provides users with a platform to perform analytical tasks. There are several kinds of data repositories, each with distinct characteristics and intended use cases. Let’s discuss the peculiarities and uses of data warehouses, data marts and data lakes.

Learn the how and what of analytics and data integration.

Learn how to get your organization started with automated data integration.

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.

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.

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.

Automated data integration can help you jumpstart your machine learning efforts. Learn about the modern data science stack. It’s an oft-cited factoid that data scientists spend only 20% of their time doing actual data science work, while the rest of their time is spent on doing what is often delightfully referred to as “data munging” — that is, obtaining, cleaning, and preparing data for analysis.

Gartner names Fivetran in the 2020 Gartner Magic Quadrant in the data integration tools category. Today, we’re proud to share that Fivetran has been recognized in the August 2020 Gartner Magic Quadrant for Data Integration Tools for the first time. The data integration market is rapidly evolving and expanding as organizations increasingly understand the value of analytics and the importance of data-backed decisions in driving business success.

Fivetran or Stitch for automated ELT? Learn the pros & cons of each platform. October 5, 2020 We commonly hear from our customers that when they initially evaluated cloud data integration solutions, both Fivetran and Stitch came up in their cursory searches. With the Stitch's announcement of their free plan deprecation, we’ve received an influx of questions on how the two solutions differ. Below, we highlight the differences in the approaches to handling automated ELT as well as pricing.