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by Sam Lockshin
In complex wholesale energy markets the ability to work with information at scale is foundational. That’s why Yes Energy continues to evolve DataSignals® Cloud, our Snowflake-native data delivery platform, to support faster analysis, broader transparency, and AI-enabled workflows.
Explore how recent enhancements – both from Snowflake and Yes Energy – are reshaping what’s possible for energy analysts, traders, and utilities.
What Is DataSignals® Cloud?
DataSignals® Cloud is our fully managed, cloud-based data delivery platform that provides customers complete access to our power market data warehouse through Snowflake secure data sharing feature. It’s ideal for traders, utilities, developers, and analysts working with large, time-sensitive, or historical datasets.
Key capabilities of DataSignals® Cloud include:
- Comprehensive coverage of all US power markets, including market prices, transmission constraints and outages, generation, and weather data.
- Access to deep historical records, typically dating back to market inception, for backcasting, benchmarking, and long-term modeling.
- Zero replication – Information is shared directly into the customer’s Snowflake environment. No data downloads, manual transfers, or custom ingestion pipelines are required.
We organize our cleaned and standardized data into analytics-ready schemas featuring consistent naming, quality checks, and formats optimized for SQL, Python, Excel, Power Bi, Tableau, or however else you prefer to work with data. The familiar relational database structure reduces onboarding time, and cloud-native scalability enables compute to scale with data volumes and analytics intensity.
Yes Energy is a multi-year Snowflake Partner of the Year, recognized for supporting customers with large-scale complex analytical workloads across the energy sector. A sample dataset is available on the Snowflake Marketplace, and you can explore the platform on your own with a free Snowflake trial.
Unlocking New Value: How You Can Leverage the Latest Snowflake Innovations
Snowflake continues to evolve, introducing new features and capabilities that enhance usability, automation, and scalability. Our customers get strong value from Snowflake-powered solutions out of the box—but those who go deeper can unlock even more. We track Snowflake’s updates closely and share the most relevant opportunities as they arise.
We attended the Snowflake Summit 2025 in San Francisco, where we identified two major themes for future enhancements:
- Snowflake as a central analytics hub: Snowflake is positioning itself as an ecosystem for all stages of data processing and analysis.
- Artificial intelligence (AI) and machine learning (ML) integration: Recent enhancements reflect Snowflake’s commitment to embedding AI and ML across the platform.
Here’s a recap of the most valuable features we investigated at Summit.
Developer Productivity
Notebooks
Snowflake now supports integrated notebooks that combine the data fetching strengths of SQL and the analytics strengths of Python in a single environment – similar to Jupyter Notebooks. These are valuable for:
- Building and documenting information pipelines or recurring workflows.
- Scheduling workflows.
- Developing and sharing reusable assets.
For analysts and developers working with Yes Energy’s datasets, notebooks improve repeatability and documentation across common workflows.
Workspaces
Snowflake workspaces are a Visual Studio (VS) code-style interface with multi-tab SQL editors, an object browser, query history, and a built-in Copilot AI assistant for writing SQL and Python. This environment provides a centralized space to manage all Snowflake tasks.
Git Integration
Snowflake now allows native integration with GitHub, GitLab, Bitbucket, and other version control platforms. Users can:
- Pull version-controlled code directly into Snowflake objects.
- Execute stored code using EXECUTE IMMEDIATE FROM statements from a SQL prompt.
- Push updates back to Git via notebooks or Streamlit apps (coming soon).
Did you know that Yes Energyshares code samples and analytics accelerators on GitHub? The resources we share enable DataSignals users to quickly implement workflows that leverage power market data software, saving development time and enhancing reliability.
Smarter Cost Management and Scaling
As data workloads continue to grow in volume and complexity, Snowflake has introduced new features to help optimize performance and control costs.
Adaptive Compute
Adaptive compute allows users to scale warehouse size automatically based on workload. For example, a trading desk that sees usage spikes during market events can scale up temporarily without manual intervention. Customers can also set credit caps or define size limits to maintain budget control.
Budget Tagging and Anomaly Detection
Using tag-based budgeting, users can track compute usage by business unit and set alerts when usage nears defined thresholds. AI-driven anomaly detection also flags unusual spending patterns.
Query Optimization
Enhanced tools, such as Query Acceleration Services and Performance Explorer, provide deeper visibility into slow-running queries. And Yes Energy provides additional performance tuning guidance to DataSignals® Cloud Snowflake users.
Embedded AI for Self-Service and Advanced Analytics
Snowflake is embedding AI features that make insights more accessible.
Cortex AISQL: Users can perform classification, summarization, and aggregation tasks using SQL statements.
Cortex Analyst: This tool turns natural language questions into SQL using semantic models defined by teams. It enables self-service querying for less technical users.
Data Science Agent: This new feature supports data scientists by suggesting feature engineering, model tuning, and evaluation steps, accelerating machine learning workflows.
Cortex Search and Snowflake Intelligence: Users can query both structured data and unstructured documents (like market reports or regulatory PDFs) using a single prompt. For example, it could query Yes Energy’s nodal pricing information and simultaneously search a document archive for relevant policy details.
What’s New in DataSignals® Cloud
Yes Energy continues to invest in DataSignals® Cloud to improve transparency and usability, analytic depth, and AI readiness.
Data Catalog Module
The recently launched data catalog module addresses one of our most frequent customer requests: better visibility into how power market information is sourced, mapped, and represented within Yes Energy’s platform. This tool is available to all DataSignals® Cloud subscribers.
Key features include:
- Bidirectional Search: Start from a Yes Energy data type and trace it to its source Independent System Operator (ISO) report or begin with a known report and search for the data type.
- Metadata Visibility: View database table names, descriptions, and other contextual details directly in Snowflake.
- Self-Service Access: Users can now answer data lineage questions without needing to submit support tickets.
Expanded Support for Nodal Markets: Ontario Goes Live
With the Ontario Independent Electricity System Operator’s (IESO) transition to a nodal market, Yes Energy rapidly expanded coverage to support market participants and analysts, including:
- Real-time and day-ahead locational marginal prices (LMPs).
- Shadow prices and constraint types.
- Transmission topology, area load, and tie flow data.
- Full geospatial mapping (latitude/longitude) for all Ontario nodes.
Nodal information is essential for modeling congestion, assessing grid constraints, and building forward-looking trading strategies.
Calculated Data Types
The Yes Energy calculated data types feature includes derived datasets to fill critical gaps. Also known as functional or feature-engineered datasets, they are generated by combining multiple base data types to produce new, meaningful data. Users can join them seamlessly with existing market data, enabling richer modeling.
ERCOT’s 60-Day Disclosure Reports
Yes Energy now includes all twenty of ERCOT’s Security Constrained Economic Dispatch (SCED) and 60-Day Day-Ahead Market (DAM) disclosure reports in DataSignals® Cloud. These historical datasets provide are ideal for modeling market behavior, backcasting, or uncovering price drivers.
Complete Historical Visibility with Change Data Capture (Vintages)
We have added revision tracking for all major information types, not just forecasts. This functionality, which we call vintaging, eliminates the need to build custom pipelines to preserve information history. It supports model backcasting, financial audits, and a clearer understanding of how data quality evolves over time which is particularly useful when ISOs revise published information after the fact.
Key vintaging capabilities include:
- Storing every insert and update with precise timestamps.
- Enabling analysis by change time (not just event time).
- Analyzing changes to LMPs, constraint data, generation data, financial transmission rights (FTRs), and more.
Conclusion
In complex power markets where data-driven strategies have long been the norm, tools like DataSignals® Cloud,powered by Snowflake, are essential infrastructure. For power market stakeholders, staying ahead means investing not only in data but in how it’s delivered, structured, and utilized.
To learn more, watch this recent webinar or check out our material on getting started with DataSignals® Cloud and Snowflake.
About the author: Sam Lockshin is Technical Product Manager for Data Delivery products at Yes Energy. He has a passion for programmatically delivering Yes Energy’s high-quality data to customers so they can achieve their business goals. When he’s not talking to customers, refining the backlog, or writing code, you can catch him at karaoke, playing piano, or checking out the latest horror flick.
