Zamunda Water
Study Note
This page brings together public scenario links and AI-assisted research notes for study use. Start with the scenario brief, make your own attempt, and open the spoiler section only when you are ready to compare.
Scenario Snapshot
Section titled “Scenario Snapshot”| Field | Detail |
|---|---|
| Start here | Discovery index |
| Scenario source | Community scenario |
| Current status | Live |
| First public date | 2021-01 |
| Primary source | Open primary source |
| Coverage available | Scenario brief + Video or presentation + Discussion or analysis |
Only Open If You Have Attempted the Scenario
Section titled “Only Open If You Have Attempted the Scenario”The section below contains public follow-up links, board-call material, and AI-assisted notes compiled from those public sources.
Open follow-up links, Q&A, and analysis
Follow-Up Links
Section titled “Follow-Up Links”Board Insights & Common Pitfalls
Section titled “Board Insights & Common Pitfalls”Generalized Judge Questions
Section titled “Generalized Judge Questions”- License Logic: “You chose Partner Licenses for Key Customers. Can you name three CRM features they need that justify the cost over Customer Community Plus?”
- LDV Usage Strategy: “With 3.6 million usage records created monthly, how will your solution perform in 2 years? What is your granular archiving policy?”
- ERP Decommissioning: “The legacy ERP is being retired for CRM. Which system is the Master for Billing Address vs. Service Address during the transition?”
- SSO Flow: “Explain the SSO flow between the LDAP directory and Salesforce. Is it SP-initiated or IdP-initiated? How are new customers provisioned?”
- City-Based Visibility: “How do you ensure a Team Lead in City A cannot see Wastewater Programs or Key Customers in City B?”
Common Mistakes
Section titled “Common Mistakes”- Usage Data Bloat: Storing all monthly usage data in standard objects without an off-platform (Snowflake/Heroku) or Big Object strategy.
- Over-Engineering Automation: Using Batch Apex for all usage calculations. Processing should happen at the integration layer or via Platform Events to avoid concurrency limits.
- Big Bang Migration: No phased decommissioning strategy for the legacy water ERP leads to data integrity risks.
- Flat Sharing Model: Relying on a flat role hierarchy or manual sharing for dynamic city-based management instead of Criteria-Based Sharing Rules.
Strong Patterns
Section titled “Strong Patterns”- Middleware-Driven Logic: Using the ESB/ETL layer to handle the heavy lifting of usage calculations before pushing results to Salesforce.
- Hot/Cold Data Tiering: Keeping recent usage data in standard objects for billing queries and moving history to Big Objects or External Objects.
- Skinny Tables: Mandating skinny tables for the usage object to handle high-volume list view performance.
Strategic Insights
Section titled “Strategic Insights”- The “Waste Program” Automation: Success often comes down to explaining when and where the heavy calculations happen (Salesforce vs. Middleware).
- Legacy Integrity: Success requires a clear System of Record (SoR) definition for each data element during the multi-year decommissioning phase.
Additional Notes
Section titled “Additional Notes”- Utility-themed scenario focusing on person accounts, billing history, and legacy ERP transformation.
Related Study Topics
Section titled “Related Study Topics”Always verify against official Salesforce documentation
This content is study material for CTA exam preparation. Content compiled and presented with AI assistance. Not affiliated with Salesforce.
Personal study notes for the Salesforce CTA exam. Content compiled from VJ's study notes, official Salesforce documentation, community sources, and online publicly available content, then organized and presented with AI assistance. Not affiliated with Salesforce. © 2025–2026 VJ Srivastava.