Project Name
How Ksolves Enabled Unified Data Reporting with Databricks Lakehouse
The client is North America’s largest oilfield-only fueling solutions provider. They operate across multiple departments, tools, and data systems. As the business scaled, their data landscape grew increasingly fragmented, making reliable reporting a serious challenge.
The client was running operations that generated data from a wide range of sources. These included TKO, Smart Tank (FTP files), Samsara, Enverus, QuickBooks, Lightship, Stream, APIs, and various PARQUET and CSV files. Despite having rich data, the business had no central place to bring it all together. This created serious bottlenecks. Here is what the client was dealing with:
- Scattered, Department-Specific Reports: Each department relied on its own tools and generated its own reports. There was no single source of truth across the organization.
- Fully Manual Data Retrieval: Fetching and consolidating data was done manually. This made turnaround time extremely slow and left room for errors at every step.
- No Central Data Repository: The client had no data warehouse or central data storage system. Every query or report required pulling from multiple disconnected systems.
- Departments Left Out of Reporting: Key departments like HR, Accounting, and Recruitment had no real integration into the reporting framework. Their data was simply not accounted for in any structured way.
Ksolves stepped in with a clear plan: build a centralized, scalable data platform that could handle all data sources, support near real-time reporting, and serve every department effectively. Our team designed and implemented a Databricks Lakehouse (Data Warehouse) architecture on Microsoft Azure, using a structured Bronze, Silver, and Gold layer approach. Azure Data Factory (ADF) was used for ETL orchestration across the pipeline. Here is how Ksolves solved each problem:
- Built a Central Data Lake on Azure Data Lake Storage: Instead of letting data live in isolated systems, Ksolves set up Azure Data Lake Storage as the foundation. All source data from TKO, Samsara, QuickBooks, APIs, and other systems now flows into one secure, centralized location.
- Integrated Data Pipelines Across All Sources: Our experts built data pipelines using ADF ETL Orchestration to pull data from every system, tool, and department. This removed manual extraction entirely. Data now flows in automatically and consistently.
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Implemented the Databricks Medallion Architecture: Data moves through three structured layers inside Databricks. which ensures that data quality improves at each stage. The three layers are.
- Bronze Layer: Raw ingestion of all incoming data
- Silver Layer: Filtered, cleaned, and augmented data ready for processing
- Gold Layer: Business-level aggregates prepared for reporting and analytics
- Created an ODS Layer for Near Real-Time Reporting: Ksolves built an Operational Data Store (ODS) layer on top of the Silver and Gold layers. This enables near real-time reporting, which was completely absent before. Business teams can now access fresh data without waiting for manual consolidation.
- Developed a BI Suite Using Power BI: A full Power BI reporting suite was developed and deployed. Ksolves also ran onboarding sessions to help end users get comfortable with the new dashboards and reports. Both real-time and non-real-time reports were managed separately for clarity and performance.
- Enabled ML Models for Route Optimization: The Gold layer data also feeds into machine learning models designed to optimize delivery routes and improve operational productivity. This adds a forward-looking intelligence layer on top of the reporting infrastructure.
- Secured the Environment with Azure Key Vault and VNet: All data and pipeline activity runs within a secured Azure environment. Azure Key Vault manages secrets and credentials, while Azure VNet provides network-level isolation and protection.
- All departments, including HR, Accounting, and Recruitment, are now part of the reporting ecosystem
- Manual data retrieval was eliminated through automated pipelines
- Near real-time reporting is now available through the ODS layer
- Reports are clean, consistent, and drawn from a single source of truth
- Power BI dashboards give business leaders clear, actionable insights
- ML models are now running on reliable data for route and productivity optimization
Ksolves built a solution that brought everything together. The Databricks Lakehouse approach gave the client a scalable, secure, and modern data infrastructure. It replaced manual processes with automated pipelines and gave every department a seat at the reporting table. The client now has the data foundation they need to make faster, better decisions, and to grow without their data architecture holding them back.
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