Quick Start Guide

Step 1: Review the Workflow

Familiarize yourself with the FeatureByte workflow, from creating features to serving them and managing their lifecycle.

Step 2: Learn Through Tutorials

Explore FeatureByte’s capabilities with our interactive tutorial series. These tutorials will guide you through key concepts such as catalog creation, data modeling, and use case structuring. You'll also dive into Feature Ideation, which automatically suggests relevant features, and learn how to build feature lists, compute training data, and deploy features.

🚀 Hands-on Learning with Hosted Tutorials

For a hands-on learning experience, sign up for our Hosted Tutorials to acccess our hosted environment.

---

📚 Available Tutorials

1. Credit Default Dataset Tutorials

📌 Dataset Overview

The Credit Default Dataset consists of six tables:

• New_application – Records new loan applications.
• Loan_application_decisions – Contains data on prior loan applications.
• Consumer_loan_status – Tracks consumer loans status.
• Consumer_installments – Logs monthly installments for consumer loans at the time of payment.
• Cash_loan_status – Tracks cash loans status.
• Cash_installments – Logs monthly installments for cash loans at the time of payment.

The tutorials cover the first four tables, while the last two (Cash_loan_status and Cash_installments) are left for you to explore.

🔹 Start Here:

• Credit Default UI Tutorials
• Credit Default SDK Tutorials.

---

2. Grocery Dataset Tutorial

Walk through an end-to-end workflow using real-world data from a grocery store chain.

📌 Dataset Overview

The Grocery Dataset consists of four tables:

• GroceryCustomer – Contains customer details, including name, address, and date of birth.
• GroceryInvoice – Stores invoice details, including timestamp and total amounts.
• InvoiceItems – Lists items in each invoice, including quantity, total cost, applied discounts, and product IDs.
• GroceryProduct – Provides product group descriptions for grocery items.

🔹 Start Here:

• Grocery UI Tutorials
• Grocery SDK Tutorials

Tutorial Differences

Both datasets include Event Tables, Slowly Changing Dimension Tables, and Dimension Tables.

Dataset	Additional Table Type
Grocery Dataset	Item Table
Credit Default Dataset	Time Series Table

UI tutorials provide a comprehensive hands-on experience with Feature Ideation and the complete UI workflow, while SDK tutorials focus on advanced feature customization using FeatureByte's declarative framework in Python.

For a deeper understanding how to manage changes in source table availability and quality, check out the UI Grocery Tutorials.

Step 3: Install FeatureByte SDK

Refer to the Installation Guide for detailed instructions tailored to different operational environments.

Step 4: Connect to Your Data Warehouse

Ensure seamless integration with your existing data infrastructure by following our guides to connect with DataBricks, Snowflake, BigQuery and Spark.

Verify that you have Read Access for source tables and Write Access for the feature store.

Step 5: Implement Custom Transformers

Enhance your text processing and feature engineering capabilities by integrating custom transformer models. Visit our 'Bring Your Own Transformer' to learn how.

Step 6: Scale Your Enterprise AI Efforts with FeatureByte Enterprise

Contact us today for a demonstration or to learn more about how we can help you transform your AI aspirations into reality.