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Course Overview

Basic to Expert​

This course provides an end-to-end journey through DPL Studio --- from foundational metadata modelling to building MCP-based data packs, multi-source integrations, and AI-driven analytics visualizations. Learners advance from creating data structures to integrating enterprise systems (SAP B1, ECC, Salesforce) and automating insights with dynamic, version-aware dashboards.

Module 1: Foundations of Data Intelligence in DPL Studio​

Objective: Build a strong understanding of DPL Studio fundamentals and metadata-driven data modelling.

Topics Covered

  • Understanding Metadata Models

  • Designing Entities, Attributes, and Relationships

  • Visualizing Models with PlantUML

  • Version Control for Model Changes

Moodle Activities​

  • SCORM package walkthrough of metadata and visualization

  • Quiz and forum on modelling concepts

  • Assignment: Create and submit a sample metadata-driven model

Module 2: Building ETL/ELT Pipelines and Data Transformations​

Objective: Design, automate, and manage ETL/ELT processes in DPL Studio for migration and transformation use cases.

Topics Covered

  • ETL vs ELT

  • Transformation and Data Validation Rules

  • Data Migration Scenarios

  • Versioning ETL Pipelines

Moodle Activities

  • SCORM demo of ETL and ELT setup

  • Quiz on ETL vs ELT use cases

  • Assignment: Build an ETL/ELT workflow and document process

Module 3: Pack Generation and Multi-Connection Data Integration with MCP​

Objective: Learn to use MCP (Model Control Protocol) within DPL Studio to create intelligent DPL Packs that connect to multiple data sources and produce ready-to-use query results.

Topics Covered

  • Introduction to MCP in DPL Studio: How MCP manages models, packs, and runtime metadata.

  • Multi-Connection Setup: Configuring connections to different databases and APIs within a single pack.

  • Query Building: Writing and optimizing multi-source queries across connected systems.

  • Pack Generation: Generating deployable DPL Packs using MCP with reusable query logic.

  • Scenario: Creating a DPL Pack integrating SQL + API + File sources for unified querying.

Moodle Activities

  • SCORM Activity: Demonstration of MCP configuration and DPL Pack generation.

  • Interactivity: Learners connect multiple data sources and build reusable MCP-based packs.

  • Quiz Activity: Concept and scenario-based questions on MCP integration and pack generation.

  • Forum Activity: Discussion on challenges of multi-source integration and query optimization.

  • Assignment Activity: Create a DPL Pack using MCP with at least two data connections and submit the generated pack file or screenshots.

Module 4: Dynamic Visualization and Version-Aware Analytics​

Objective: Visualize data pack outputs dynamically, track versioned record changes, and analyse transformation results in real time.

Topics Covered

  • Connecting Packs to Visualizations: Feeding DPL Pack outputs into visualization dashboards.

  • Creating Dynamic Dashboards: Using DPL's Data Formulator to visualize query results.

  • Version-Aware Visualization: Displaying record-level version changes, updates, and transformations visually.

  • Scenario: Tracking schema or record changes over multiple pack versions and comparing differences.

  • Exporting Visual Dashboards: Delivering visualization results for external applications (MCP, Flowise, or analytics tools).

Moodle Activities

  • SCORM Activity: Guided visualization setup using DPL Pack outputs.

  • Interactivity: Learners visualize real-time version changes within DPL dashboards.

  • Quiz Activity: Questions on visualization logic and version-aware insights.

Forum Activity: Discussion on version tracking, delta visualization, and best dashboard practices.

Assignment Activity: Create a dynamic visualization that highlights version differences across records and submit visual output (dashboard screenshot or export).

Module 5: Data Integration and Analytics via MCP and Excel Integration​

Objective: Integrate enterprise systems (SAP B1, ECC, Salesforce) using MCP to generate packs and feed real-time analytics dashboards in DPL Studio.

Topics Covered

  • Enterprise Connectors Overview: Setting up MCP connections for SAP B1, ECC, and Salesforce.

  • Pack Design for Enterprise Data: Creating composite packs pulling data from multiple enterprise sources.

  • Data Harmonization: Normalizing fields and attributes across heterogeneous systems.

  • Feeding Data into Dynamic Visualization: Pushing enterprise data into AI-driven analytics dashboards.

  • Scenario: Unified analytics dashboard combining SAP B1 orders, ECC inventory, and Salesforce leads.

  • Version Control for Enterprise Data: Managing live updates and version tracking in large-scale integrations.

Moodle Activities

  • SCORM Activity: Simulation of enterprise data integration via MCP and DPL Studio.

  • Interactivity: Learners connect to sample enterprise systems, generate packs, and visualize analytics.

  • Quiz Activity: Multiple-choice and scenario-based questions on enterprise MCP connections and analytics output.

  • Forum Activity: Peer discussion on real-world enterprise integration challenges and visualization performance.

  • Assignment Activity: Create an MCP Pack integrating SAP/Salesforce/ECC data and generate a dynamic dashboard showing live analytics and version comparison.

Learning Progression Path​

Level Focus Outcome

Basic (Modules Metadata, ETL/ELT, Create models and transformation 1--2) Data Modelling workflows

Advanced (Module MCP, Build reusable, query-ready data 3) Multi-Connection packs Pack Building

Advanced (Module Visualization, Build dynamic dashboards showing 4) Version Tracking live data and version differences

Expect (Module 5) Multi-System Integrate SAP, ECC, and Salesforce Integration & for unified real-time analytics Analytics

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