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When Byrider, a national automotive sales and service company, decided to modernize and transform its analytics, it chose to use Amazon Redshift and Looker for its modern data and analytics platform. They knew this combination would enable the scalability, performance and insights they needed as their company grew.

Beyond this powerful technology combination, Byrider’s CIO knew that for long-term success, they would need a team to help them model their source data and design custom dashboards based on their unique goals and KPIs. The team they chose was Ollion.



Byrider needed help optimizing their modern data and analytics platform to create user-friendly dashboards for their sales team.


Ollion modeled and integrated Byrider’s data into Amazon Redshift before building robust sales dashboards in Looker.


The new sales dashboards provided near real-time sales reporting in Looker and enabled Byrider’s sales team to drill into metrics and track their performance against their budget.

The challenge

The goal of this project was to create a user-friendly sales dashboard in Looker powered by near real-time data from sources throughout the organization. To make this happen, the Ollion team needed to complete these tasks:

  • Create a data model that would yield performant and scalable analytics in Looker.
  • Build out the data model in Amazon Redshift.
  • Develop a dashboard in Looker that highlights KPIs for Byrider’s sales funnel and tracks how they're performing against their budget.
  • Provide training and support to Byrider’s reporting and analytics team to ensure long-term success and increase user adoption for both Redshift and Looker.

Making an impact

Byrider's CIO wanted to ensure his internal team received training and documentation for ongoing success. They turned to Ollion, an experienced data consulting partner, to do the following:

  • Model their source data to support advanced analytics.
  • Determine a performant, near real-time data update process.
  • Consolidate and optimize multiple reports.
  • Modernize their dashboards and fully leverage Looker.
  • Provide technical training and documentation.

Step 1: Data modeling and restructuring

Ollion began by creating a dimensional model to restructure Byrider’s data into a form that supports advanced analytics. We then built that model and implemented complicated business logic using materialized views in AWS Redshift.

Step 2: Data ingestion

Once we restructured the data, it was brought into Looker using LookML with the goal of reimagining Byrider’s sales funnel reports. To combine sales data with budget data, Ollion created a persistent derived table (PDT) that would merge data at different levels of granularity.

Step 3: Custom sales dashboard creation in Looker

Ollion created a customized Looker dashboard based on business user requirements that incorporated liquid parameters, customized drill-in fields and built-out measures with logic for KPIs. Additionally, Ollion implemented row-level security (RLS) in Looker so end users could only view data associated with their franchise.

In addition to the steps above, training was provided throughout to ensure Byrider’s internal team would be able to easily manage the tech stack moving forward and create additional dashboards for other functional areas across the company.

The end product provided a single dashboard that communicates the entire story of Byrider’s sales funnel. It enables business users to take actionable steps by clearly visualizing their performance against budgeted goals and previous years.

The underlying data model enabled Byrider to easily filter to the correct information in Looker. By implementing liquid parameters and adding drill-in fields, Ollion was able to communicate the big picture, while also empowering users to dive into the data further when a more granular level of detail is needed.

In addition to the near real-time sales reporting in Looker, the Ollion team provided training and documentation around best practices to support future development and enable autonomy.

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