Jade helped Backcountry on their platform modernization journey by migrating reports from the legacy BI (OBI) to Google’s cloud-based visualization platform Looker. As part of the migration efforts, we have built several explorers to enable self-serve BI capabilities, migrated over 400+ reports/looks, and built several dashboards in Looker.
This effort wasn’t just about technology. It is also about business processes and people working together to do what suits our customers as an organization. The theme was to ensure that the modern business intelligence capabilities platform supports legacy functions as far as possible, empowers businesses with more analytical capabilities and switching to the modern business intelligence platform doesn’t interrupt business.
About the Client
Backcountry.com is an online specialty retailer that sells clothing and outdoor recreation gear for hiking, camping, road biking, mountain biking, rock climbing, winter sports, fly fishing, kayaking, rafting, road and trail running, and more.
Backcountry’s roots may be in the cloud, but people’s lifestyle revolves around shared adventures in the real world. With their new collection of stores, one can get personalized outdoor advice—and swap trail stories—with their Gearheads and get help with everything from custom bike builds and camp kits to mountain town-style pointers.
- Being on the legacy BI platform for a while, user adoption of cloud BI solutions was challenging.
- Newer tools missing some key user intuitive features, a couple to name are Period Rolling and Analysis as filters in another analysis.
- These key OBI features that don’t exist in Looker were to be re-engineered & resolved per business need with custom solutions.
- OBIEE Reports to be converted were very complex than expected & requires a lot of LookML effort.
- Looker business intelligence Support mentioned that unavailable features would be implemented in future releases, delaying the project deliverables and hence requiring custom solutions.
- There is no fiscal period feature under month level to support fiscal weeks; hence had to implement custom 4-5-4 Date tools.
- Lack of AGO function in BigQuery made YoY comparison a tuff challenge to perform business’s day-to-day analyses.