Introduction
SIL Global partners with local communities to develop language solutions: supporting literacy, education, development and engagement with biblical scripture. The organization and its partners run 1,500 active language projects in 100+ countries and have long been associated with their language database Ethnologue, which provides a comprehensive catalogue of all known living languages on earth. To coordinate efforts and steward donor funds effectively, SIL Global needed a single source of truth that hundreds of independent collaborative organizations could fully trust.
Pre-WhereScape Challenges
- No central collaboration hub: 300+ organizations working in parallel with overlapping projects and no easy way to see who was doing what, where.
- Messy, heterogeneous inputs: emailed spreadsheets, Google Sheets, assorted APIs— all with little standardization.
- Minimal integration: an ASP-based reporting system over isolated databases; virtually no cross-org analytics.
- Stewardship at risk: without consolidated insight, donation resources and people resources were hard to allocate optimally, and demonstrating progress to funders was difficult.
Why WhereScape?
SIL Global needed a way to move fast with messy data and stand up a proper star-schema warehouse on Microsoft SQL Server: all without hand-coding thousands of lines of ETL. WhereScape RED’s low-code automation, built-in best-practice patterns and metadata-driven design were a natural fit. WhereScape’s platform-agnostic approach also supports future flexibility as stacks evolve.
“We were brand new to data warehousing: we first tried out SSIS and got nowhere… so tried out custom code but got nowhere with that either.“
– Dwayne Emberson, Data Warehouse Specialist, SIL Global
The Solution
Normalized ‘Messy’ Sources Up-Front
A lightweight Python pre-processing layer standardizes partner inputs (spreadsheets, Google Sheets & API data) into CSV and JSON.
Model & Build with WhereScape RED
Dwayne’s data team used WhereScape to design a traditional star schema on SQL Server and generate ELT while also managing deployment & documentation.
Enable Analytics for Everyone
Business Intelligence (BI) at the organization originally started on Tableau but now runs primarily on Amazon QuickSight, giving staff and partner-org users role-appropriate access to dashboards that provide insights to daily decisions and strategic funding choices.
Train Once, Then Scale-Up Skillsets
WhereScape training was delivered by a third-party in the form of a one week course. The SIL Global team were fast learners and began building production-ready ELT within a few months. One more recent skillset success story that stands out: a web developer with little database experience, this time being trained by Dwayne himself, became productive quickly on WhereScape.
“We were developing some of our first ELT processes within a few months of completing a course”
– Dwayne Emberson, Data Warehouse Specialist, SIL Global
Results
🚀 Building from Zero, To a Shared Data Backbone
- A central data warehouse now serves 300+ organizations with a single, shared view of progress.
- 389 active users consume dashboards and reports across the ecosystem.
- Just a 3-person core team was able to deliver the first warehouse and BI dashboards, all in under 2 years.
🚀 Skills & Sustainability
- WhereScape’s UX and templates reduced reliance on niche Data Warehouse expertise; new developers can get productive fast.
- Processes are documented and repeatable, supporting turnover and volunteer engagement.
🚀 Improved Stewardship & Transparency
- Dashboards now guide millions of dollars in donations, aligning funding according to need and avoiding overlap.
- Unified metrics power public statistics across many organizations’ sites, improving transparency to both donors and communities.
🚀 Day-to-Day Impact at SIL Global
- Speed: the data team moved from ad-hoc reports to repeatable ELT with governed data models.
- Confidence: stakeholders can now trace metrics back to sources, while teams align together on one clear version of the truth.
- Collaboration: funders and operational teams review the same dashboards, enabling them to efficiently prioritize work.
Architecture: Fact File
- Automation: WhereScape RED (metadata-driven ELT, deployment, documentation)
- Pre-processing: Python (standardizes multi-format inputs → CSV/JSON)
- Warehouse: Microsoft SQL Server (star schema)
- BI: Amazon QuickSight (primary), Tableau (earlier dashboards)
- Users: 389 active report consumers
- Scale: 300+ organizations contributing data; global footprint
Why It Matters
SIL Global’s mission spans 100+ countries and thousands of staff and partners. Establishing a shared data foundation ensures that donor funds are targeted, progress is visible and overlapping effort is minimized.And all of this isn’t simply theoretical: it actively accelerates real-world outcomes for language communities worldwide. Especially to speakers of minority languages that don’t have their language represented in many aspects of their lives; something that most majority language speakers take for granted.
Looking Ahead
WhereScape has been proud to count SIL Global as a customer for close to a decade and while they’ve come a long way, they report that their current stack is working well and the team isn’t planning any immediate changes. However, armed with WhereScape’s platform-agnostic approach and 25 year heritage, SIL Global’s data warehouse can continue to evolve at the pace that they define, alongside the cloud and analytics platforms that they choose.
