The client is a global software and technology company that sells simulation products to enterprise clients and tracks their entire client and opportunity lifecycle inside Salesforce. Despite having meaningful data across multiple systems, they had never been able to successfully consolidate it into a single place. Previous attempts to unify data across platforms had failed, leaving the business reliant on siloed, hard-to-trust reports.

The impact was felt most acutely in management meetings, where even fundamental business questions — such as the number of products sold in a Fiscal Year or the count of clients who repurchased new simulators — could not be answered with accuracy or confidence. Different reports gave different numbers, and there was no authoritative source to reconcile them. The lack of a unified analytics platform also meant that advanced analysis, cross-source comparisons, and forward-looking reporting were simply out of reach.

No Single Source of Truth Across Multiple Data Sources

The client's data lived in disconnected silos. Salesforce held CRM and opportunity lifecycle data, while product performance metrics were tracked separately in Grafana. Because there was no integration layer between these systems, reports could never be compared or reconciled side-by-side. Different stakeholders working from different tools consistently arrived at different numbers, eroding trust in the data and slowing decision-making.

Inaccessible and Unreliable Key Business Metrics

Even straightforward questions, "How many products did we sell this fiscal year?" or "How many clients came back for a second purchase?", required significant manual effort to answer, and the answers still weren't reliable. The business lacked a self-service reporting layer where non-technical stakeholders could quickly access accurate, up-to-date metrics without relying on ad-hoc data pulls or conflicting Salesforce reports.

No Platform for Advanced Analytics

Without a centralized, scalable data infrastructure, the client had no path toward more sophisticated analysis. There was no place to combine CRM and product data, run segment-level analysis, track cohorts over time, or explore trends across fiscal periods. The absence of a proper analytics platform meant the business was effectively making strategic decisions blind, reacting to incomplete information rather than proactively using data to drive growth.

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Compass built end-to-end data engineering pipelines on Databricks, hosted on AWS, bringing together the client's Salesforce CRM data and Grafana product metrics into a single, governed analytics platform. The architecture follows the Medallion pattern — ingesting raw data into Bronze, cleaning and conforming it in Silver, and exposing a business-ready Gold layer for reporting. Infrastructure was provisioned entirely through Terraform for repeatability and consistency, and CI/CD pipelines were established using GitHub and GitHub Actions with Databricks Asset Bundles to ensure reliable, version-controlled deployments.

Data ingestion was handled through a combination of the native Salesforce Connector on Databricks and custom Python scripts written to pull product metrics from Grafana. The Gold data model aggregates and joins these sources into a unified view of the business. Six purpose-built Tableau dashboard pages were developed on top of the Gold layer, each tailored to a specific reporting need, giving the client's team a clear, consistent, and authoritative window into their business for the first time.

Compass delivered a production-grade, unified analytics platform that replaced fragmented Salesforce reports and disconnected product metrics with a single source of truth. By combining best-in-class data engineering tools with a scalable architecture, the client now has reliable, self-service reporting today and a strong foundation for advanced analytics in the future.

Medallion Architecture on Databricks (AWS)

The core of the solution is a Medallion Architecture deployed on Databricks, hosted on AWS and provisioned with Terraform. Data flows from raw Bronze ingestion through Silver transformation and into a curated Gold data model that serves all reporting. This architecture ensures data quality, traceability, and consistency across every report. CI/CD pipelines via GitHub and GitHub Actions with Databricks Asset Bundles keep deployments reliable and version-controlled, reducing operational risk and enabling the team to iterate quickly.

Benefit: The client now has a scalable, best-in-class data platform purpose-built for growth, one that can accommodate new data sources, additional use cases, and more advanced analytics workloads without requiring a rebuild.

Unified Data Ingestion (Salesforce + Grafana)

Data from Salesforce was ingested using the native Databricks Salesforce Connector, while product metrics from Grafana were pulled in via custom Python ingestion scripts developed by Compass. Both sources are standardized and joined within the Medallion layers into a single Gold data model that serves as the authoritative record for the business.

Benefit: For the first time, the client can compare CRM data and product metrics side-by-side in one place, eliminating the inconsistencies between reports and giving management a single, trusted answer to key business questions.

Tableau Reporting Layer (6 Dashboards)

Six Tableau dashboard pages were built directly on the Gold data model, each designed to surface the metrics that matter most to the client's business: sales performance, client activity, product adoption, and more. The dashboards are built on clean, governed data, meaning every number is consistent, reconcilable, and up to date.

Benefit: Management now walks into meetings with a shared, reliable view of the business. Basic questions about fiscal year sales, client repurchase rates, and product performance can be answered instantly — and the team has a self-service reporting layer that reduces reliance on ad-hoc data pulls and one-off analysis.