# @mlatha_naidu on Instagram

- **Type:** Video
- **Original URL:** https://www.instagram.com/p/DbENnuyB4oX
- **Gondola URL:** https://gondola.cc/posts/68346226-mlatha-naidu-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/c9bf274490.jpg
- **Posted:** 2026-07-21T18:58:57.000+00:00
- **Account Owner:** Madhulatha Pelluri (@mlatha_naidu) — https://gondola.cc/mlatha_naidu

## Caption

📖 Story Book #877 | Day 40 – POC 4 | Building an Enterprise Business Intelligence Assistant on SAP BTP
🚀 Operation Self Learning (After Office Hours)
As IT professionals, continuous learning is essential to designing better enterprise solutions.
Today, I completed POC 4 of my SAP BTP Enterprise AI Lab by extending my Enterprise AI Assistant into a Business Intelligence Assistant capable of answering analytical business questions using SAP CAP.
Instead of simply retrieving records, the application now interprets business questions and generates analytical insights from enterprise data.
🎯 What did I build?
I enhanced the Enterprise AI Assistant to understand business questions such as:
📊 What is the average price?
📦 What is the total inventory stock?
💰 Which is the most expensive book?
💸 Which is the cheapest book?
📚 Show genre summary
📘 Show SAP books under 60
The assistant detects the business intent, executes the required business logic through SAP CAP, and presents structured insights together with matching business records.
🏗️ Enterprise Architecture
👤 User
⬇️
🖥️ Enterprise Business Intelligence Assistant
⬇️
🧠 Business Intent Detection
⬇️
⚙️ SAP CAP Action (ask)
⬇️
📊 Analytics & Business Logic
⬇️
🔗 OData V4 Service
⬇️
📘 CDS Data Model
⬇️
🗄️ SQLite Database (Current POC)
⬇️
📈 Business Insights & Records
✅ What I explored
✔ SAP CAP Custom Actions
✔ Business Intent Detection
✔ Analytical Business Responses
✔ Structured Response Objects
✔ Business Intelligence Dashboard
✔ Conversation-Based User Experience
✔ Enterprise Architecture Design
✔ GitHub Portfolio Enhancement

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## Tags

877

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