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.
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:
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.
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:
Here’s a recap of the most valuable features we investigated at Summit.
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:
For analysts and developers working with Yes Energy’s datasets, notebooks improve repeatability and documentation across common workflows.
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.
Snowflake now allows native integration with GitHub, GitLab, Bitbucket, and other version control platforms. Users can:
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.
As data workloads continue to grow in volume and complexity, Snowflake has introduced new features to help optimize performance and control costs.
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.
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.
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.
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.
Yes Energy continues to invest in DataSignals® Cloud to improve transparency and usability, analytic depth, and AI readiness.
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:
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:
Nodal information is essential for modeling congestion, assessing grid constraints, and building forward-looking trading strategies.
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.
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.
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:
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.