Reliant Funding Case Study
Reliant Funding Lowers Data Engineering Time by 5x and Produces Just-in-Time Insights with Datameer
Significantly faster time to insight with "just in time" analytics and data refreshed on-demand.
500% reduction in data engineering project time and faster data engineering projects: from 5 weeks to 2 days with Datameer.
A simpler, consolidated data stack and entire cloud-first architecture that reduced costs, management overhead, and data movement.
Use Case
Data Integration, Data Analytics
Reliant Funding is a leading provider of alternative funding for small businesses. Since 2008, Reliant Funding has provided over $2B in funding to over 10,000 small businesses throughout the US. Merchants choose Reliant Funding as a trusted source for working capital thanks to speedy application process and personalized.
A critical aspect of Reliant Funding’s business model and key to its success is speed. Reliant Funding provides approvals within hours and funding within twenty-four hours. Therefore, the entire business and operations must be agile.
Datameer lowered our data engineering time by 500% and helped us produce just-in-time analytics that drove business agility.
Ryan Goodman, VP of Data and Analytics, Reliant FundingDatameer helped us simplify our data stack to reduce our overall cloud costs, management overhead, and data governance risks.
Ryan Goodman, VP of Data and Analytics, Reliant Funding
Solution Requirements
The Reliant Funding data and analytics teams provide operational and predictive models as well as insights to the entire business. This includes insights in the marketing and sales funnels, the originations funnel, and the entire portfolio management.
To keep up with the agile business model, the operational systems (including loan originations) and analytics need to be agile as well. Without up to the minute and in-depth insights, the business teams would not be able to keep up the pace of business.
An important solution requirement for Reliant Funding is for the data stack to be cloud-native. In 20xx (need to validate the year), Reliant Funding converted its entire data stack to the cloud and converged all its analytics into a Snowflake cloud data warehouse. Data from Salesforce.com (their new cloud loan origination system) and their portfolio and cash management systems is pipelined into Snowflake for analytics.
Business Challenges
A major challenge for Reliant Funding is speed. Analytics need to be up to the moment for the business teams to execute their unique, agile business and processing model. Previous approaches the company has used took too much time to process data and required overnight jobs, which would leave the business teams with “day old” analytics.
A second challenge is really an opportunity – to find ways to leverage their existing SQL skills while also eliminating their “data engineering gap.” Ryan Goodman, VP of Data and Analytics at Reliant, had already consolidated the data engineering and analytics teams into one group to get them working together effectively. Their solution now required tools that both data and analytics personnel could use, regardless of skills, and where the teams could share information and collaborate.
A final challenge was to eliminate as many data silos as possible. Reliant’s previous systems and approaches left data scattered, which made it difficult to manage and govern. The new approach required all data to reside in Snowflake.
When Reliant Funding made its’ move to the cloud and Snowflake, it was successfully able to pipeline the necessary data into Snowflake, but its tools and approaches for data modeling and transformation slowed them down. Transformations were performed in two places: SQL, which would run on Snowflake, and Tableau Prep. This presented two problems:
- The SQL projects would take a long time to write and took a long time to execute, leaving business teams with stale analytics, and
- Tableau Prep, while it enabled faster projects, moved the final data out of Snowflake, creating another data silo and the management and governance overhead that comes with it, and was not cloud-native.
The Datameer Solution
Reliant Funding chose Datameer as their new data modeling and transformation platform to replace Tableau Prep, consolidate all their data transformations, and simplify their data stack. Reliant Funding choose Datameer because:
Hybrid UI
The hybrid UI allowed their data engineers to leverage their existing deep SQL skills while also allowing less programming-oriented analysts to use a no-code approach to model and transform data.
Snowflake Native
The platform is Snowflake-native, keeping all the data in Snowflake and executing jobs in a fraction of the time.
Data Catalog
The built-in catalog allowed the data and analytics teams to better document and share knowledge about the data.
Reusable Building Blocks
Teams could create reusable building blocks, making projects faster and the data pipelines more reliable.
The Results
Reliant Funding saw significant improvements and benefits from its’ implementation of Datameer. One project that took five weeks in SQL and two weeks in Tableau Prep took only two days with Datameer. In addition, change management processes to adjust and re-deploy data models for new analytics went from multiple days to minutes.
Other results we gathered for this Reliant Funding case study include:
500%
Lower Data Engineering Time
- Faster time to insight – Prior to Datameer, users would have to wait a day to get fresh data and reports. With Datameer, the business teams have “just in time” analytics, with data models constantly refreshed as new data arrives. This was transformational to the business and essential for Reliant Funding to execute its unique business model.
- Faster loading of reports – Previously, the loading of some Tableau reports would take 3 minutes or more. With Datameer’s optimizations for Snowflake data models, these same reports would take only 10 seconds to load.
- Simpler data stack – With Datameer, Reliant’s data stack became significantly simpler and easier to manage with all data consolidated in Snowflake and all data transformations in Datameer (which managed them in Snowflake). This led to cost savings, lower management overhead, and less data movement.
- Leveraged existing skills – With Datameer’s hybrid SQL and no-code tools, Reliant Funding was able to leverage its significant skills and investment in SQL.
- Entire cloud-first architecture – With the combined Datameer and Snowflake architecture being cloud-first, Reliant Funding could leverage all the benefits of the cloud and reduce their architectural overhead and costs.
- Easier discovery and higher data literacy – Prior to Datameer, Reliant Funding did not have a catalog of data models. By using Datameer’s built-in data catalog, analysts are able to easily discover data models, can add additional metadata such as descriptions, custom properties, tags, classifications, and business semantics, and can more easily understand what the data is and how to use it.
- Easier data governance – with the elimination of the extra data silos and consolidation of data in Snowflake, Reliant’s data governance became much easier, and their cost and risks around data governance were lower.