Data Tiles
← Back to Industry Use CasesEnergy · Latttice

Activating energy decisions with governed data products.

How an energy company could use Latttice, the AI-powered Data Product Workbench from Data Tiles, to turn fragmented operational, asset, and customer data into trusted, reusable data products that support generation, networks, trading, and retail.

Executive Summary

From Operational Silos to Trusted Energy Data

Energy companies operate at the intersection of physical assets, complex markets, and high public expectation. Decisions move quickly, and the cost of acting on inconsistent or unverified data is high — for safety, for compliance, and for customer trust.

This example illustrates how an energy company could use Latttice to activate its existing data ecosystem. Rather than rebuilding platforms, the company could use the Data Product Workbench to turn operational, asset, market, and customer data into governed, reusable data products consumed by operations, trading, customer, and AI use cases alike.

Key Outcomes

Four shifts in how the company used energy data.

01

A Shared View of Assets and Customers

Generation, network, trading, and retail teams worked from the same governed data products rather than locally prepared extracts and reports.

02

Faster Operational Response

Performance, outage, and demand questions were answered through reusable data products instead of new engineering tickets, compressing days of work into hours.

03

Safer Decisions Under Pressure

Operational, safety, and regulatory rules were embedded in each data product, so decisions made under time pressure stayed within approved boundaries.

04

Governance Built In

Definitions, access controls, and quality rules were embedded in each data product as it was created, not bolted on after the fact.

The Challenge

Assets, Markets, and Customers Defined Differently

Operational, market, and customer data lived in systems with different definitions and refresh cycles. Reconciling these views took engineering time the organization could not afford to lose, particularly during peak demand or operational events.

Fragmented Asset and Operational Data

SCADA, asset management, metering, trading, and customer systems each described the same assets, sites, and customers differently.

Slow Insight on Critical Decisions

Outage response, network planning, and trading decisions waited on engineering cycles, while operational risk and customer impact accumulated in the meantime.

Compliance Treated as a Separate Stream

Safety, environmental, and regulatory reporting were rebuilt for every audit cycle rather than being embedded into the data the business already used.

The Approach

Domain-Built, Governed Data Products in Latttice

Rather than commissioning another integration program, the company could use Latttice to let operations, trading, and customer teams design the data products they actually needed. Subject matter experts worked in the Workbench's guided, zero-code environment to combine sources, apply safety and compliance rules, and publish governed data products with clear ownership.

Access controls, quality rules, and regulatory logic were embedded into each data product as it was published. Approved teams could then consume those products through BI, operational systems, and conversational interfaces without reopening engineering tickets for every new question.

Organizational Impact

Trusted energy data across the business.

01

Generation and Network Operations

Operations teams accessed governed data products that combined asset health, performance, and demand signals in a single trusted view, supporting faster, safer response to events.

02

Trading and Portfolio Decisions

Trading and portfolio teams reused governed price, load, and generation data products, improving consistency between front office decisions and operational reality.

03

Customer and Retail Experience

Retail and customer experience teams worked from the same governed customer, consumption, and service data products, aligning offers, billing, and service decisions.

04

Foundation for AI

Governed operational, asset, and customer data products provided a reliable foundation for AI use cases such as predictive maintenance, demand forecasting, and assistive customer service.

Conclusion

Energy Decisions Depend on Trusted Data

From real-time operations to long-term planning, energy decisions depend on whether teams trust the data in front of them. By activating its existing data ecosystem through Latttice, the company could deliver consistent, governed data products to the people and processes that depend on them, without rebuilding the systems already in place.

Explore Latttice Industry Solutions

Latttice supports energy, financial services, telecommunications, insurance, retail, public sector, and more — helping teams turn governed data into trusted data products at the point of decision.

Industry solutions on Latttice →