About the client
The client is a regulated utility that distributes electricity across parts of Ontario, Canada. It serves residential and commercial customers in the City of Ottawa and the Village of Casselman. The company ensures reliable power delivery while adhering to strict regulatory standards and plays a key role in supporting local energy infrastructure and sustainability efforts.
Client challenges
The client faced several data management and analytics challenges that impeded timely insights and efficient decision-making. Key issues included:
- Transactional system limitations: The client’s Oracle database was optimized for transactional processing rather than analytical workloads, resulting in performance degradation during heavy reporting periods.
- Data duplication risks: Without a robust ETL framework, there was a risk of loading duplicate records into the data warehouse, which degraded data quality and report accuracy.
- Lack of centralized analytics: Analytical data was spread across multiple Oracle schemas without a unified data warehouse, making it difficult for business users to access a single source of truth.
- Manual data handling: The lack of automation in data extraction and transformation led to inconsistent processes, increased operational overhead, and a higher likelihood of human error.
- Limited scalability: The existing Oracle setup cannot scale cost-effectively to meet growing data volumes and reporting demands across departments.
- Delayed insights: Business users experienced delays in accessing up-to-date information due to nightly batch loads and the lack of real-time data processing.
- Semi-structured data challenges: Oracle’s limited support for JSON and other semi-structured formats restricted the organization’s ability to incorporate modern data sources into reporting.
Solution
To overcome the challenges, LevelShift modernized the client’s data ecosystem and unlocked the power of analytics. The team implemented a secure, scalable, and high-performance integration framework using Boomi and Snowflake to manage meter, account, customer, and outage data.
The transformation began by bridging Oracle/SQL Server and Snowflake. Using Amazon S3 for bulk data loading and the Boomi platform for integration, LevelShift created a cohesive data flow that eliminated silos and enabled real-time access.
Data from multiple sources, including outage details, customer profiles, meter information, and account records, was synchronized with Snowflake tables. The process ensured reliability and consistency at every stage. Raw data first landed in staging tables within Snowflake, where it was carefully transformed and deduplicated before being moved to refined tables. This structured flow ensured that business users had access to clean, trusted data for their reporting needs.
The result was empowering; business users could now build dashboards and generate insights independently, without relying on IT teams or manual data exports. What was once a fragmented, time-consuming process became a modern, automated, and insight-ready data environment, positioning the client for faster, smarter decision-making.
Benefits
With LevelShift’s Boomi expertise, integrating Oracle with Snowflake delivered measurable business benefits.
- Delivered faster deployments: Achieved 75% faster integration development using Boomi’s low-code platform, reducing deployment time.
- Enhanced operational reliability: Implemented robust error handling (100%), reduced failures by 96%, and achieved zero failure alerts.
- Ensured data quality: Ensured accurate and consistent data with validation with Boomi’s built-in checks.
- Streamlined data processing: 100% of deduplicated data moved to refined tables for advanced data analytics.
- Reduced manual effort: Automation minimized manual involvement in reporting and analytics, freeing valuable resources.
- Enabled informed decision-making: Unified data views improved reporting accuracy and enabled more informed business decisions.
- Delivered scalable performance: Enabled seamless updates with near-zero downtime, even during peak load periods, ensuring high availability and stability.