- Reports that took three to four days to generate before board meetings are now available immediately.
- Fivetran saves Skuid an estimated six months of time for initial pipeline and transformations setup.
- With Fivetran, Skuid can quickly generate comprehensive lists of customer tickets and metrics from Freshdesk, something support had been unable to achieve for years.
- Skuid is currently building out more than 100 new dashboards and reports.
- After realizing its current data warehouse approach was not scalable, Skuid used Fivetran transformations to easily and rapidly modify its warehousing strategy.
- Pipeline & Transformations: Fivetran
- Sources: Freshdesk, HubSpot, PostgreSQL, Salesforce, CSVs
- Destination: Redshift
- BI Tool: Internal with Skuid platform
Skuid offers a digital experience toolkit that enables anyone to design, develop and deploy applications to fit their business needs. As the company expanded, Skuid outgrew its existing reporting methods. The company embarked on a data warehousing project to mature its operational data management and develop a verified single source of truth for all company data.
Manual Reporting With No Single Source of Truth
As Skuid tried to integrate multiple systems, internal teams did not establish a single source of truth. People were pulling reports out of their applications and exporting them into spreadsheets. “The biggest danger with people looking at the data in different systems or in Excel is that they either pull the incorrect fields or interpret the data incorrectly without the broader picture factored in,” explains Javid Igani, Manager of Internal Solutions at Skuid. “We wanted to give people the data they needed in a more self-service reporting model, without any choke points.”
As a consequence of the reporting challenges, the team was spending hours formatting data that should have been readily available. Skuid’s financial director had to ensure that the numbers reported to stakeholders were correct by going through each team’s reports. “Before these meetings, managers had to hole up for three to four days to manually generate these reports,” says Igani. “Our CEO should be able to click a button to load the data and make decisions off of it.”
Building a Data Stack With No Engineering Involved
Igani led the warehousing project and came across Fivetran: “I read through the entire documentation and I realized it was exactly what we needed. It had connectors to all of the systems we were trying to integrate into a data warehouse.”
Having the data centralized into Amazon Redshift, Skuid’s data warehouse of choice, enables the business to take advantage of the Redshift data source type available on the Skuid platform. “Within 24 hours I was able to turn on Fivetran, get the data into Redshift and format it in one place, then view the data on a webpage that I could give to leadership,” Igani says.
Igani would have been responsible for the data engineering himself since his team was needed on other projects, and he estimates that it would have taken six months to build out pipelines and set up transformations. Using Fivetran allowed him to reallocate that time to other strategic projects during the same time frame.
Leveraging Fivetran Transformations
With Fivetran Transformations, Igani easily set up powerful and automated in-warehouse transformations. “We have over 60 transformations right now,” he says. “They’re an extremely approachable way for someone to add that layer to their data pipeline. With Fivetran doing the ELT, all of our raw data is in the warehouse and untouched.”
Here's how Ignani describes the range of transformations Fivetran enables:
Pretty much anything you can write in SQL you can put through a transformation and benefit from it because it runs in the same way it would if you were to take that code and run it in your database client. It allows us to keep reports up to date and take snapshots of critical daily data, such as our sales pipeline, so we can understand the state of today and tomorrow through a really simple transformation. We don’t have to worry about how we’re going to get the data anymore and we can focus on delivering the types of reports that executives want. It is a really big game-changer.
More Relevant, Reliable Report Data
Before Fivetran, Skuid was able to generate some reports on large data sets manually. The Freshdesk API, for example, has a 30-row limit per request that made it difficult to get a timely overview of data for client requests without writing more code. Additionally, the reports that Freshdesk offers out-of-the-box aren’t relevant for Skuid. With Fivetran, Igani and his team can quickly build a Skuid page to interact with the data, providing a comprehensive list of tickets and metrics joined with Salesforce data per client to the Manager of Technical Support within minutes.
Having the data has increased the enthusiasm of the support team. Skuid plans to build 100 new reports and dashboards in the next few months that address broad company goals and additional departmental metrics. “Really anything that we need to report on is going to be solved this year as a direct result of how Fivetran has helped,” Igani explains. “We’re off to a great start and there are plenty of other projects that have been opened up as a result.”
Ready to see the benefits of fully automated data pipelines and centralized data on your organization? Sign up for a personalized demo of Fivetran or start your free trial today.
About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.
About Redshift: Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse solution that makes it simple and cost-effective to efficiently analyse all of your data using your existing business intelligence tools.