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datanalytix

Integrate and transform Salesforce, SAP, ERP, and PostgreSQL data into analytics-ready structures.

1|Updated Mar 10, 2026
Search Tags:#analytics#data#dashboard#pipeline#etl#data-quality#multisource
One-click install
npx skills add https://github.com/dduquenne/unanima-platform --skill datanalytix
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datanalytix
Source: https://github.com/dduquenne/unanima-platform/tree/main/.claude/skills/datanalytix
Command: npx skills add https://github.com/dduquenne/unanima-platform --skill datanalytix

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Data teams struggle to consolidate data from multiple enterprise sources, ensure data quality, and deliver reliable dashboards. This skill provides end-to-end data handling, ETL/ELT pipelines, and analytics-ready views.

Core Features & Use Cases

  • Multi-source data consolidation (Salesforce, SAP, PostgreSQL) with staging and transformation.
  • Materialized views and scheduled refresh for fast dashboards.
  • Data quality enforcement and auditability with validation, deduplication, and traceability.

Quick Start

Connect data sources, configure staging and transformation pipelines, and expose analytics via materialized views for dashboards.

Frequently Asked Questions about datanalytix

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I consolidate multi-source data from Salesforce, SAP, and PostgreSQL into analytics-ready structures?▼

Multi-source data consolidation integrates Salesforce, SAP, ERP, and PostgreSQL data through staging and transformation pipelines, producing analytics-ready structures to power reliable dashboards and KPIs.

What's the best way to enforce data quality and auditability in an ETL pipeline?▼

Enforcing data quality in an ETL pipeline requires validation, deduplication, audit trails, and upsert semantics to ensure idempotent, auditable data transformations across enterprise sources.

How do I build materialized views for scheduled batch reporting and real-time metrics?▼

Materialized views and scheduled refreshes transform integrated multi-source data into fast, analytics-ready structures, supporting both real-time metrics and batch reporting for dashboards.

Can I use this approach for cross-system data consolidation with enterprise ERP sources?▼

Cross-system consolidation applies to enterprise scenarios involving Salesforce, SAP, ERP, and PostgreSQL sources, handling staging, transformation, and data validation across disparate platforms.

Why does my dashboard show duplicate or inconsistent data from multi-source pipelines?▼

Duplicate or inconsistent dashboard data occurs when pipelines lack proper deduplication and validation, which this approach resolves through enforced data quality and upsert semantics for idempotent processing.

Do I need specific staging configurations to handle batch reporting and real-time metrics?▼

Staging configurations are required to transform raw multi-source data, enabling both scheduled batch reporting and real-time metrics exposure through materialized views for dashboards.

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