Enable AI-Driven Transformation with Agentic AI in Microsoft Foundry (DW-230)

Organizations today are moving beyond traditional automation toward Agentic AI, a paradigm where intelligent systems can reason, act, and collaborate autonomously. The DW-230 learning path focuses on enabling this transformation using Microsoft Foundry, helping professionals design, manage, and pitch enterprise-ready AI solutions.

Whether you are exploring a DW-230 course or enhancing your skills through DW-230 training, this structured journey provides both conceptual clarity and real-world application.

Course Overview

• Level: Intermediate
• Duration: 3 days (2 hours/day)

This concise yet impactful format ensures learners can quickly grasp concepts and apply them in real-world scenarios.

Day-1: Design with the Best Models for Your Use Case with AI Foundry

The first step in adopting Agentic AI is understanding the challenges of modern AI development and selecting the right tools and models.

1. AI Development Challenges and the Rise of Agentic AI

Organizations often struggle with:

• Model selection and scalability
• Integration with existing systems
• Managing data pipelines and governance

Agentic AI addresses these by enabling systems that can independently plan and execute tasks.

1. Agent tooling – Choosing the Right Tools for Agent Development

Selecting the right tooling is critical:

• Low-code tools for rapid prototyping
• Advanced frameworks for scalable solutions

These decisions often depend on your familiarity with concepts like data modeling, ETL process, and data pipeline design.

1. Microsoft Foundry – The AI app & agent factory

Microsoft Foundry serves as a unified platform to design, build, and scale AI applications and intelligent agents, enabling seamless integration, customization, and governance across enterprise-grade AI solutions.

1. Getting started with AI Foundry

Microsoft Foundry acts as a centralized platform to:

• Build AI-powered applications
• Develop intelligent agents
• Integrate enterprise data seamlessly

This aligns closely with foundational concepts like data engineering, where structured pipelines and workflows power intelligent systems.

1. Designing with the Best Models for your use case

Different use cases require different models:

• Conversational AI → Language models
• Analytics → Predictive models
• Automation → Task-oriented agents

A strong understanding of data warehouse basics and SQL tutorial concepts helps prepare and structure data effectively for these models.

1. Customizing with a Multi-Agent Toolchain

Modern AI systems often involve multiple agents working together:

• Data ingestion agents
• Processing agents
• Decision-making agents

This mirrors traditional data warehousing tutorial approaches, where data flows through multiple transformation layers.

Day-2: Managing Enterprise-Ready AI with Confidence

Fig 1: Enterprise AI Architecture.

Manage enterprise-ready AI with confidence – AI safety tooling

Once AI systems are built, managing them at scale becomes the priority.

AI Safety Tooling

Enterprise AI requires:

• Monitoring outputs
• Ensuring compliance
• Preventing bias and misuse

These practices are similar to maintaining data quality in a data pipeline.

AI innovation across landscapes – AI Foundry integrations

Microsoft Foundry integrates with:

• Enterprise applications
• APIs and external services
• Data platforms and warehouses

This enables seamless connectivity between AI systems and existing data engineering ecosystems.

Why Microsoft AI Foundry?

Key advantages include:

• Scalability for enterprise workloads
• Built-in governance and monitoring
• Flexibility in model selection

For professionals pursuing DW-230 certification, understanding these capabilities is essential.

Popular Customer Use Cases

Organizations are leveraging Foundry for:

• Intelligent customer support agents
• Automated document processing

These use cases rely heavily on structured data, often processed through ETL process pipelines and stored using data modeling best practices.

Customer Success Stories

Real-world implementations demonstrate:

• Reduced operational costs
• Faster decision-making
• Improved customer experiences

Getting Started

Getting started with Microsoft Foundry involves setting up your environment, exploring available AI models, and building your first intelligent agent using guided tools and templates.

• Set up the workspace and access the required resources
• Explore the model catalog and agent capabilities

Whether you’re aiming to advance in your current role or pivot to a new career in AI and Agentic AI, you should enroll in the Agentic AI Certification Training  Program.

Day 3: Responding to Customers and Building Your Pitch

Customer Case Study Approach

The final stage focuses on applying your knowledge to real-world business scenarios.

Business Scenario

You will analyze:

• Industry context
• Business goals
• Existing technical landscape

Technology Background

• Outline current systems, tools, and architecture
• Assess AI readiness, data sources, and integrations

Customer Challenges

Common challenges include:

• Legacy systems
• Data silos
• Inefficient workflows

Requirements

Solutions must address:

• Scalability
• Security
• Integration with existing data pipelines

Objections

Customers may raise concerns about:

• Cost
• Complexity
• ROI

A strong foundation in data warehouse basics and AI architecture helps in addressing these effectively.

B-Pitch Perfect

The highlight of Day 3 is crafting a compelling pitch.

Build a 3–5 Minute Pitch as your response to the customer

Your pitch should:

• Clearly define the problem
• Present an AI-driven solution
• Highlight business value

Present Your Pitch

Focus on:

• Clarity and structure
• Real-world impact
• Technical feasibility

Handle Objections

Use:

• Data-backed insights
• Scalable architecture explanations
• Practical examples

This stage bridges the gap between technical expertise and business communication, an essential skill for professionals completing a DW-230 course.

Driving AI Transformation Forward

In today’s rapidly evolving digital landscape, Agentic AI is transforming how enterprises innovate, automate, and scale intelligent operations. The DW-230 learning path with Microsoft Foundry equips professionals with the practical skills to design, manage, and confidently present enterprise-ready AI solutions. From AI model selection and multi-agent orchestration to governance and customer-focused solution pitching, this program bridges technical expertise with business value, empowering organizations and professionals to drive successful AI-driven transformation initiatives.