Data Warehousing for Energy: Modeled for Time-Series, Assets, and Regulatory Reporting

A utility modernizes its data warehouse and hits two problems simultaneously. First, the time-series data from SCADA and AMI doesn't fit naturally into the traditional dimensional model — the volume is enormous, the query patterns are different (time-range scans, not dimensional aggregation), and the storage cost becomes a budget issue if every interval reading gets loaded into a standard fact table. Second, the financial dimensional model doesn't encode the FERC Uniform System of Accounts, so the regulatory affairs team can't get the views they need for Form 1 without a separate reporting layer. The warehouse serves general analytics but fails at the two use cases that matter most: operational time-series and regulatory financial reporting.

Utility data warehousing done right separates the time-series and dimensional workloads. Time-series data (SCADA, AMI) stored in purpose-built formats with partitioning by time and asset, pre-aggregated views for common access patterns, and retention tiering that manages cost. Dimensional models for customer, outage, asset, and financial analytics with the FERC account structure and IEEE 1366 reliability methodology encoded in the semantic layer. Both share the asset and geographic master data. Both reconcile to source systems. With this dual design, the warehouse handles operational time-series and regulatory reporting without compromising on either.