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Track 02 — Build intelligent applications

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Track Overview

Fields Details
Products watsonx.data
watsonx.data Intelligence
watsonx.data Integration
Target Persona Select-t growth partners, Application Developers/Technical Leaders and Select-t clients
Overview sessions 2
Lab sessions 4
Estimated Duration ~6–7 hrs (excluding breaks)

Learning Journey

flowchart LR
    theory["<strong>Overview</strong><br/>What & Why"] --> lab101["<strong>Lab 101</strong><br/>Basics"]
    lab101 --> lab201["<strong>Lab 201</strong><br/>Fundamentals"]
    lab201 --> lab301["<strong>Lab 301</strong><br/>Intermediate"]
    lab301 --> lab401["<strong>Lab 401</strong><br/>Advanced"]

Hands-on Labs

Before you begin

Make sure your lab environment is set up: Lab Environment Setup

Lab 101 - Basics lab

Goal

In this basic lab, you'll learn core concepts, explore the architecture overview, and complete the foundational setup. You'll understand the key products and why they exist through hands-on experience in your chosen domain.

  • Getting Started with Data Ingestion

    Domain: Finance

    Ingest financial CSV data into watsonx.data using local file upload and Cloud Object Storage.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Ingest structured data into watsonx.data using the Data Manager
  • Load data from both local file system and Cloud Object Storage
  • Register ingested data as a managed table in the watsonx.data catalog

Lab 201 - Fundamentals lab

Goal

In this foundational lab, you'll build upon the basics and dive deeper into core platform capabilities. You'll work with more advanced features and learn how to implement practical intelligent application solutions in your chosen domain.

  • Build CRUD-Capable Apache Iceberg Tables with Spark

    Domain: Data Engineering

    Turn flat CSV files in object storage into fully CRUD-capable SQL tables using Apache Spark and Apache Iceberg on watsonx.data.

    Start Lab

  • Unified Data Access Through Federation in watsonx.data

    Domain: Retail

    Use watsonx.data's federation capabilities to create a unified query layer across siloed retail data sources — without moving data.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Build CRUD-capable Apache Iceberg tables using Spark on watsonx.data
  • Run row-level INSERT, UPDATE, and DELETE operations on object storage data
  • Federate queries across multiple data sources without data movement

Lab related support: TBD