CASE STUDY // TREK BICYCLE

Trek Bicycle Accelerates Retail Analytics

Global bicycle leader uses Qlik and Databricks Data Intelligence Platform to unify data.

80-90%

Acceleration in run-time.

Analytics results are now available in six to eight hours, instead of 48 hours previously.

3x

Increase in daily data refreshes.

Business analytics data is now refreshed three times a day, ensuring accurate and actionable results.

1 week

Reduction in ERP data replication.

ERP data is now replicated in near-real time, instead of weekly using bulk copies.

CHALLENGE

Slow data processing hinders retail analytics.

The business has achieved impressive global growth, but the core values that made Trek Bicycle successful haven’t changed: it aims to provide an outstanding experience to customers and staff. To achieve this, it needs quick and reliable access to high-quality data.

However, as Trek grew it became increasingly affected by the rising costs and decreasing performance of its data warehouse. Specifically, running analytics on retail data was challenging as Trek relied on a platform that was not scaling cost-effectively, which impacted processing speeds.

APPROACH

Qlik unifies retail data from around the globe.

As the business grew, Trek needed an agile data ingestion and transformation solution for its lakehouse. The solution needed to keep pace with growth and integrate with Databricks to deliver a global view of its performance and allow it to process data more quickly and regularly.

Trek now uses Qlik and Databricks to collect sales data from nearly 500 stores worldwide. All computation happens on top of the lakehouse in a new data warehouse, with a semantic layer powering everything from strategic high-level reporting to daily store sales reports.


RESULTS

New platform accelerates analytics by up to 90%.

By moving its data processing to the lakehouse and integrating data with Qlik, Trek has dramatically increased processing speeds and overall data availability. Instead of replicating enterprise resource planning (ERP) data once a week using bulk copies, Qlik helps to facilitate the process in near-real time.

Trek’s retail analytics solution used to take 48 hours to produce meaningful results. Today, Trek gets results in six to eight hours — an 80 to 90% improvement — with refreshes running three times a day, compared to only once a day previously.

WHAT THIS MEANS FOR YOU

Turbocharge your retail analytics capability.

Databricks Lakehouse has been a game-changer for Trek. With Qlik Cloud® Data Integration, the business can replicate transactional data in real time from hundreds of stores and digital sources worldwide and take some impressive steps toward achieving its cloud-first vision.

With the quick and reliable access to accurate data that this enables, businesses can cut costs, meet critical needs and focus on delivering world-class engagements with customers — whether online or in person at retail stores.



Here’s what other customers are saying.

We needed to consolidate data in one place, from heterogenous sources, updated in almost real-time. That's what Qlik Data Integration enables for us.

Cédric Brignol

Project Manager
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