The energy
lakehouse.
Your next edge.
Connect market history, grid fundamentals, weather and asset context through a data subscription around the models, analytics and applications your team is building.
The data foundation behind Ask the Grid.
Markets
Weather
Assets
Energy lakehouse
For data scientists & quantitative teams
For energy developers & operators
For your existing analytical environment
Models and market analysis
Your analytical edge starts after the data arrives. Work from the market publications, physical records and weather inputs behind Ask the Grid, with a package built around the question you need to answer.
Build better models.
Bring prices, load, generation and weather together. Inspect the history and forecast vintages your training and evaluation need.
Understand the market.
Investigate spreads, congestion and changing system conditions with source-attached data you can trace back to its publisher.
See the asset in context.
Connect market observations with generators, storage and development activity. Evaluate the geography and relationships that matter to your portfolio.
Energy datasets
Market prices
Study spreads, price formation and the locations where power settles.
LMP by Settlement Point
ercot.lmp_by_settlement_point
Source: ERCOT
Cadence: 5-minute (SCED)
LMP by Bus
ercot.lmp_by_bus
Source: ERCOT
Cadence: 5-minute (SCED)
DAM System Lambda
ercot.dam_system_lambda
Source: ERCOT
Cadence: hourly (DAM)
Open a dataset for its schema, sample and coverage. Subscription scope, history and permitted use are agreed during your evaluation.
Data provenance
A price, a forecast and a delayed disclosure tell different stories. Keep their source, timing and meaning in view as you build your analysis.
Source attached
Know the publisher, dataset and methodology behind the record.
Time made explicit
Keep observed conditions, publication times and forecast targets distinct.
Coverage you can inspect
Review history, cadence, schema and samples before choosing a package.
A defined data agreement
Agree the markets, delivery, revisions, support and permitted use your team needs.
Delivery options
Choose the datasets first. Then work with us on the history, update schedule, delivery path and use rights that fit your environment.
Your warehouse
Tell us your Snowflake or Databricks environment, cloud and region. We’ll scope the connection around your team's workflow.
Warehouse delivery planning
Your storage
Plan bulk historical access and recurring file delivery into your own lake or pipelines, with formats and update semantics agreed up front.
Bulk history + ongoing updates
Your application
Explore the existing API for targeted data access and applications. Use the developer console to inspect requests and integration examples.
Explore the developer platformQuestions about data services
A useful data service starts with a clear scope.
What data can we evaluate?
Start with market prices, load and generation, weather, or asset and infrastructure records in the public catalog. Tell us the markets and analytical task you need; we’ll identify the relevant datasets and confirm the subscription scope.
Can we use our existing warehouse?
Yes—bring your existing stack into the evaluation. Tell us whether you use Snowflake, Databricks, DuckDB or another environment, along with your cloud and region. We’ll agree a delivery approach and validate the connection with you.
How much history is included?
History varies by dataset and location. Each catalog listing lets you inspect its coverage. During evaluation we confirm the required date range, known gaps and whether historical and ongoing location coverage match your needs.
How often does the data update?
Each source has its own publication clock, from market intervals to monthly filings and delayed disclosures. Catalog entries name the cadence; the data agreement defines the delivery schedule for your selected package.
Can we backtest models with it?
We’ll review the temporal requirements of your backtest, including forecast issue times and source revisions. Vintage availability differs by dataset. Latest corrected facts, historical forecasts and reanalysis serve different purposes and should be selected accordingly.
How are subscriptions priced?
Subscriptions are scoped to your datasets, markets, history, delivery and support requirements. Request an evaluation so we can define the package and its price together. Customer compute and any managed services are addressed in the delivery plan.
Can we train models or redistribute the data?
Tell us how you intend to use the data. Internal analysis, model training and customer-facing redistribution require different rights. Your data agreement sets the permitted uses for the selected sources.
What happens after we request an evaluation?
A person from our team reviews your requirements. Together we select a useful set of data, confirm coverage and rights, and plan a sample or connection against a real analytical workflow.
What are
you building?
Tell us the market, the data and the question. We’ll help shape an evaluation around the work your team needs to do.
- 01Choose a market and analytical task.
- 02Confirm coverage, history and permitted use.
- 03Plan a sample or connection in your stack.
Request a data evaluation
Your note goes directly to our team.