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Development of a Scalable ERP & BI System for Enhanced Decision-Making and Operational Efficiency

yalantis

Information technology

Current Challenges in Data Management and Decision-Making

The organization faces slow business insights due to disconnected systems and manual data collection, data silos preventing unified visibility, data overload from unstructured sources, and overburdened teams requiring self-service data access.

About the Client

A software development company providing IT services and solutions, seeking to optimize internal operations through a data-driven ERP & BI system.

Strategic Objectives for ERP & BI Implementation

Automate data consolidation from internal systems to eliminate inconsistencies
Provide real-time operational and HRM visibility via Tableau dashboards
Enhance decision-making speed and resource management efficiency
Establish a centralized data governance framework

Core System Functionalities and Features

Automated data pipelines using Apache Airflow for ETL workflows
Centralized PostgreSQL data warehouse with unified metadata repository
Self-service Tableau dashboards for HR, finance, and project management
API integrations for QuickBooks, Pipedrive, Jira, Slack, and email

Technologies and Tools

Apache Airflow

Python (Pandas)

Tableau Prep and Tableau Desktop

PostgreSQL

REST APIs

External System Integrations

QuickBooks (finance)
Pipedrive (CRM)
Jira (project management)
Slack (communication)
Email systems

Non-Functional Requirements

Scalable data warehousing for growing datasets
High availability and fault-tolerant pipeline monitoring
Data security and governance compliance
Low-latency data synchronization across systems

Expected Business Impact of ERP & BI Implementation

The solution will reduce decision-making delays by 40%, eliminate manual data reconciliation, enable cross-departmental process visibility, and support AI-driven predictions through a unified data lake, driving operational efficiency and strategic growth.