Explore

When tasked with any data science project the first step is to locate and understand your data. Rasgo enables you to explore the entirety of your cloud data warehouse without having to export a bunch of datasets to your local laptop. Quickly and easily search, filter, and select tabular data from multiple tables and design custom data sets in minutes using our metadata catalog.

Goal: Locate and gather relevant data

Task: Search and group all relevant data in a tabular format to be cleaned.

Use Rasgo to quickly locate and select relevant data that will later be transformed into features. Easily select data from multiple sources/tables to create entirely new datasets without writing a bunch of custom SQL.

Rasgo UI

Try our Hands-on Demo

Pyrasgo

Read the Docs

Transform

Cleaning data can’t be avoided but, it doesn’t have to be such a slog. Whether you prefer
“code” or “no-code.” Rasgo empowers you to build powerful insights from raw data in just minutes directly from your cloud data warehouse. Easily chain multiple transforms together to perform complex data operations with just a few lines of Python or via a Rasgo’s powerful UI.

Goal: Create a relevant dataset

Task: Clean, join, and impute tabular data.

Rasgo’s open library of predefined data transformations gives you a quick and easy way to join columns together, impute missing values, and a lot more. Thanks to Rasgo, all of the compute required to complete your transforms happens directly in the Cloud Data Warehouse instead of your local machine.

Rasgo UI

Read the Docs

Pyrasgo

Check out Transforms on GitHub

Serve

Before a feature can be relied on in production, it must be accessible, declarative, repeatable, and explainable. With Rasgo, you can publish entire datasets of production-grade features and natively integrate them with whatever modeling or BI tool you prefer. All of which is fully versioned and can be done with a single line of python or a few clicks in the UI.

Goal: Publish a dataset and proceed to modeling

Task: create a dataset of informative features to train a model on

Using a single python function or click of a button in the Rasgo UI, you can publish, version, and serve your features at sub-second speeds to a number of different platforms. Effortlessly monitor the health of your features with Rasgo and be able to track their use over time.

Rasgo UI

Book a Private Demo

Pyrasgo

Our Resources

Explore our resources, curated to help you take your skills to the next level

Data Science

Third Times the Charm?

Time series feature engineering, three ways

Data Science

Refined Data is the New Fuel part 2

Best Practices For Transforming Dirty Data Into a Renewable Resource

Data Science

Refined Data is the New Fuel part 1

Best Practices For Transforming Dirty Data Into a Renewable Resource

Rasgo Raises $25M to Deliver the Feature Store for Cloud Native Databases and Introduce New Capabilities to the Data Science Community

Rasgo Product

Announcing PyRasgo

Rasgo Product

Rasgo's Native Integration with Snowpark

Rasgo's feature store, built on Snowflake, orchestrates feature engineering transformations programmatically for users directly on the data warehouse.

Broken Lifecycle

Making Accurate Predictions

Introducing Rasgo’s accelerated modeling preparation platform

We heard thousands of Data Scientists scream in frustration. “I went to school to be an expert in developing models and solving interesting problems. Instead, I’m spending the vast majority of my time extracting, exploring, cleansing, joining, and transforming raw data into a model training ready dataframe. ”

Rasgo Product

The Rasgo vision

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Feature Engineering for Modern Data Teams

Want something to share with your team that easily explains Rasgo?

Explore

Transform

Serve

Our Resources

Third Times the Charm?

Refined Data is the New Fuel part 2

Refined Data is the New Fuel part 1

Rasgo Raises $25M to Deliver the Feature Store for Cloud Native Databases and Introduce New Capabilities to the Data Science Community

Announcing PyRasgo

Rasgo's Native Integration with Snowpark

Making Accurate Predictions

Selecting the Right Data for Your ML Model

The Model Preparation Abyss

Our Perspective on the Prioritization of Data Science Investments: Part 2

Our Perspective on the Prioritization of Data Science Investments: Part 1

Data Science Failure Modes

The data science lifecycle and why projects fail

Introducing Rasgo’s accelerated modeling preparation platform

The Rasgo vision