Fivetran Case Studies SpotOn Accelerates Reporting with Fivetran Transformations for dbt Core

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	SpotOn Accelerates Reporting with Fivetran Transformations for dbt Core Fivetran

SpotOn Accelerates Reporting with Fivetran Transformations for dbt Core

Fivetran

Technology Category	Infrastructure as a Service (IaaS) - Cloud Databases Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries	Electrical Grids Equipment & Machinery
Applicable Functions	Product Research & Development
Use Cases	Leasing Finance Automation Time Sensitive Networking
Services	Cloud Planning, Design & Implementation Services
Challenge	SpotOn, a rapidly growing software and payment company, faced significant challenges in efficiently transforming their captured customer transaction data into fast, reliable, and informative reporting for their clients. As the company scaled, the complexity of turning data into reporting for customers and internal stakeholders increased, with client data scattered across 30 unconnected MySQL databases. The engineering team lacked a central repository for efficient reporting generation. The existing data transformation process using stored procedures in Snowflake became increasingly complex and resource-intensive, with over 2,000 lines of code behind a single table. Changes were not automatically monitored or logged without version control, making quality assurance time-consuming and scaling required writing code from scratch for each new use case. This resulted in high costs, resource-intensive processes, and suboptimal results, impacting the company's ability to scale quickly to meet growing customer needs. Read More
About Customer	SpotOn is one of the fastest-growing software and payment companies, offering comprehensive, cloud-based technology for businesses of all types and sizes. With the acquisition of Appetize, SpotOn’s client base grew to include enterprise venues like Madison Square Garden, Fenway Park, and MetLife Stadium, all with unique needs and complex data. The company's product team is tasked with efficiently turning captured customer transaction data into fast, reliable, informative reporting for their clients, while their internal data team harnesses data to optimize internal operations. Read More
Solution	To address these challenges, SpotOn turned to Fivetran, Snowflake, and dbt. Fivetran was used to seamlessly move all of their clients’ customer data from 30 disparate MySQL databases into Snowflake, providing a secure foundation of data that could then be transformed at scale to meet their various analytical needs. With Fivetran Transformations for dbt Core, SpotOn was able to automate faster, more reliable reporting for their clients, while saving time and cost. dbt Core modularized the 2,000 lines of transformation code, making data models more readable, easier to debug, and scalable with jinja templates. By integrating their dbt project into Fivetran, Fivetran Transformations for dbt Core could orchestrate those model runs automatically post-Fivetran connector load, eliminating the need for custom scripting, third-party tools, or DevOps. SpotOn's data engineering team also used dbt Cloud to turn large volumes of data from multiple databases into powerful internal analytics and BI, enabling collaborative, data-driven growth. Read More Log in to view content
Contents

Technology Category

Infrastructure as a Service (IaaS) - Cloud Databases

Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Electrical Grids

Equipment & Machinery

Applicable Functions

Product Research & Development

Use Cases

Leasing Finance Automation

Time Sensitive Networking

Services

Cloud Planning, Design & Implementation Services

Challenge

SpotOn, a rapidly growing software and payment company, faced significant challenges in efficiently transforming their captured customer transaction data into fast, reliable, and informative reporting for their clients. As the company scaled, the complexity of turning data into reporting for customers and internal stakeholders increased, with client data scattered across 30 unconnected MySQL databases. The engineering team lacked a central repository for efficient reporting generation. The existing data transformation process using stored procedures in Snowflake became increasingly complex and resource-intensive, with over 2,000 lines of code behind a single table. Changes were not automatically monitored or logged without version control, making quality assurance time-consuming and scaling required writing code from scratch for each new use case. This resulted in high costs, resource-intensive processes, and suboptimal results, impacting the company's ability to scale quickly to meet growing customer needs.

About Customer

SpotOn is one of the fastest-growing software and payment companies, offering comprehensive, cloud-based technology for businesses of all types and sizes. With the acquisition of Appetize, SpotOn’s client base grew to include enterprise venues like Madison Square Garden, Fenway Park, and MetLife Stadium, all with unique needs and complex data. The company's product team is tasked with efficiently turning captured customer transaction data into fast, reliable, informative reporting for their clients, while their internal data team harnesses data to optimize internal operations.

Solution

To address these challenges, SpotOn turned to Fivetran, Snowflake, and dbt. Fivetran was used to seamlessly move all of their clients’ customer data from 30 disparate MySQL databases into Snowflake, providing a secure foundation of data that could then be transformed at scale to meet their various analytical needs. With Fivetran Transformations for dbt Core, SpotOn was able to automate faster, more reliable reporting for their clients, while saving time and cost. dbt Core modularized the 2,000 lines of transformation code, making data models more readable, easier to debug, and scalable with jinja templates. By integrating their dbt project into Fivetran, Fivetran Transformations for dbt Core could orchestrate those model runs automatically post-Fivetran connector load, eliminating the need for custom scripting, third-party tools, or DevOps. SpotOn's data engineering team also used dbt Cloud to turn large volumes of data from multiple databases into powerful internal analytics and BI, enabling collaborative, data-driven growth.

Impact #1	The implementation of Fivetran Transformations for dbt Core resulted in significant operational improvements for SpotOn. The company was able to scale with a lean team as their clients, and their data needs, grew. Automated version control, data lineage graphs, and documentation ensured data integrity. The synchronization of connector load and model runs reduced computational costs and the complexity of the tech stack was significantly reduced. Client-facing reporting was generated faster, ensuring clients had always-on and reliable access to their data, and no opportunities or optimizations were missed. The internal team also benefited, with the ability to collaboratively produce internal analytics and BI faster, expediting the time to insight.

Impact #1

The implementation of Fivetran Transformations for dbt Core resulted in significant operational improvements for SpotOn. The company was able to scale with a lean team as their clients, and their data needs, grew. Automated version control, data lineage graphs, and documentation ensured data integrity. The synchronization of connector load and model runs reduced computational costs and the complexity of the tech stack was significantly reduced. Client-facing reporting was generated faster, ensuring clients had always-on and reliable access to their data, and no opportunities or optimizations were missed. The internal team also benefited, with the ability to collaboratively produce internal analytics and BI faster, expediting the time to insight.

Benefit #1	Fivetran helped SpotOn’s team centralize 30+ databases into Snowflake
Benefit #2	dbt Core helped them reduce thousands of lines of code into scalable data models
Benefit #3	Fivetran Transformations for dbt Core decreased reporting development time by weeks, while increasing automation

Benefit #1

Fivetran helped SpotOn’s team centralize 30+ databases into Snowflake

Benefit #2

dbt Core helped them reduce thousands of lines of code into scalable data models

Benefit #3

Fivetran Transformations for dbt Core decreased reporting development time by weeks, while increasing automation

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Overview

SpotOn Accelerates Reporting with Fivetran Transformations for dbt Core

Operational Impact

Quantitative Benefit