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Fivetran Facilitates Growth and Efficiency for Frontify's Branding Platform
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Databases
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Cement
- Equipment & Machinery
Applicable Functions
- Sales & Marketing
- Warehouse & Inventory Management
Use Cases
- Building Automation & Control
- Time Sensitive Networking
Services
- Data Science Services
The Challenge
Frontify, a platform that helps companies grow their brands, faced a significant challenge in building a single source of truth for their data. The company needed to understand how people interacted with their platform to optimize user experience and resource allocation. However, their data analytics team was small, and their data infrastructure was unstable. They relied on custom Python scripts to pull data from business applications into a MySQL database, which often resulted in slow, incomplete data. Their BI tool was user-unfriendly and slow, causing reluctance among employees to use it. The data team was burdened with the task of updating reports and dashboards. To address these issues and become truly data-driven, Frontify needed a scalable and powerful data stack that could be accessible to everyone.
About The Customer
Frontify, launched in 2013, is a cloud platform that helps companies grow their brands by connecting all the important elements and stakeholders in one place. The platform provides a holistic set of solutions, tools, integrations, and templates that cover every aspect of the brand journey. As part of a recent $50 million funding round, Frontify is focusing on further advancing its technology and enhancing its analytics capability, which is central to its mission. The company's data team, which has grown to four people, is now primarily focused on data engineering and analytics.
The Solution
Frontify's data team evaluated Modern Data Stack components to find the best solution for their business. They chose Snowflake as their data warehouse vendor and Fivetran for automated ELT due to its range of connectors, encryption handling, ease of use, and transformation capabilities. ThoughtSpot was selected as their business intelligence tool to enable users to engage directly with their data. Transitioning from the MySQL database to the new stack involved building a raw data layer in Snowflake that incorporated Fivetran data sources and custom ETL scripts. A data mart was created for reporting and analytics with 'self-service' search-driven analytics on top. Fivetran connectors now feed data to Snowflake from various sources, including HubSpot for sales and marketing and Zuora and Recurly for recurring revenues. The new data infrastructure has transformed the roles of the data team, allowing them to focus on data engineering and analytics rather than building and fixing data pipelines manually.
Operational Impact
Quantitative Benefit
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