solution: Real-Time Operational Data Lake for Energy Assets
One real-time foundation for every sensor, system, and site.
Operational insight depends on timely, trusted data. This solution provides a real-time data foundation that consolidates operational, sensor, and enterprise data into a single platform.
Frame delivers the solution through data engineering, analytics, and platform implementation services that support streaming ingestion, real-time analytics, and scalable access for operational teams.
Energy companies generate massive volumes of operational data from SCADA, historians, IoT sensors, and field applications, but these datasets are often isolated across incompatible systems. Without a real-time, unified data foundation, organizations struggle to support analytics, automation, and decision-making at scale.
Operational data silos across SCADA, historians, PLCs, and field mobility tools.
No standardized data model for integrating time-series, event, and asset data.
Latency and batch processing delays limit real-time visibility for operations teams.
Difficulty supporting AI, optimization, and predictive analytics due to inconsistent data quality.
High cost and complexity associated with legacy on-prem systems and manual ETL processes.
Frame delivers a modern operational data lakehouse built on Databricks that unifies time-series, event, and asset data into a high-performance, scalable environment. This architecture enables real-time streaming pipelines, standardized asset models, and AI-ready data structures to support digital operations across the enterprise.
Unified ingestion of SCADA, historian, IoT, and operational data streams into a Databricks lakehouse.
Real-time data pipelines using Delta Live Tables and streaming architectures.
Standardized asset and event models enabling cross-site analytics and enterprise reporting.
Automated data quality, validation, and enrichment workflows to improve reliability of operational data.
Foundational platform enabling advanced analytics such as predictive maintenance, OEE, emissions tracking, and optimization models.
By modernizing their operational data infrastructure, organizations gain real-time situational awareness, better decision-making capabilities, and a scalable foundation for AI-driven transformation. This improves operational efficiency and reduces both cost and risk.
Faster, more accurate decision-making enabled by real-time operational visibility.
Reduced system complexity and cost through consolidation into a unified lakehouse.
Improved data quality supporting analytics, automation, and AI initiatives.
• Stronger operational resilience through standardized asset and event models.
A scalable data platform that supports future digital and AI use cases across the enterprise.
Our Approach – Minimize risks and maximize return.
Frame delivers with confidence through proven, repeatable methods that reduce cost overruns, project delays, and operational uncertainty. Our AI-enhanced delivery model helps to ensure consistent execution across cloud-native, analytics-driven architectures—while hyper-local teams and nearshore scale drive efficiency without compromising quality. Frame’s prebuilt accelerators, reusable IP, and tight feedback loops fast-track speed-to-value while maintaining full transparency and shared accountability every step of the way.
Discover & Design
Start with business goals, identify the right opportunities, define the value and chart a clear plan.
Build & Modernize
Extend and modernize your data and architecture with scalable platforms and secure pipelines while complimenting your existing systems.
Scale & Evolve
Scale high-impact AI use cases, establish sustainable governance, and evolve with frameworks that support agility, adoption, and long-term value.
Value Delivery
We don’t just modernize—we deliver outcomes you can measure: faster cycles, smarter operations, and durable solutions that evolve with change.
