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Development of an Advanced Business Intelligence and Reporting Platform for Data-Driven Decision Making
  1. case
  2. Development of an Advanced Business Intelligence and Reporting Platform for Data-Driven Decision Making

Development of an Advanced Business Intelligence and Reporting Platform for Data-Driven Decision Making

scalosoft.com
Information technology

Business Challenges in Achieving Real-Time, Accurate Operational Insights

The client faces increasing complexity in managing diverse operational data across multiple divisions and global locations. Existing reporting methods rely heavily on manual, static Excel reports, which are insufficient for real-time monitoring of KPIs. This hampers timely decision-making and operational optimization, risking decreased competitiveness and growth limitations. The client needs a centralized, automated BI solution that enables precise, real-time insights into financials, sales pipelines, and service delivery processes.

About the Client

A mid to large-sized software solutions provider managing multiple divisions and services, requiring real-time operational insights to support growth and strategic planning.

Goals for Implementing a Robust Data-Driven Reporting System

  • Establish a centralized, cloud-based data environment integrating multiple data sources for comprehensive analysis.
  • Automate data collection, cleaning, and standardization processes to ensure consistent, accurate, and timely reporting.
  • Enable real-time KPI monitoring to facilitate proactive decision-making across business functions.
  • Develop an internal analytics dashboard providing users with customizable reports on financials, sales, and operational metrics.
  • Improve data governance by documenting and standardizing data processing and measurement processes to support sustainable scaling.

Core Functional Features for the Business Intelligence Solution

  • Integration with diverse internal and external data sources via APIs into a centralized cloud data warehouse.
  • Data cleaning and standardization workflows to prepare data for analysis.
  • Definition and documentation of key business metrics such as headcount measurement and attrition rate with configurable parameters.
  • An internal analytics dashboard for real-time KPI visualization and customizable reporting.
  • Automated data refresh mechanisms to ensure up-to-date insights.
  • Role-based access control to secure sensitive data and ensure compliance.

Technologies and Architecture Preferences for the BI System

Azure cloud platform (Azure Data Factory, Azure SQL, Azure App Service, Azure Key Vault, Azure App Config)
Power BI for visualization
Python for data processing scripts

Necessary External and Internal System Integrations

  • APIs for data ingestion from operational systems and external sources
  • Authentication and security integrations to manage data access
  • Data storage solutions via cloud data warehouse

Essential Non-Functional System Requirements

  • System scalability to support data growth and increasing user demands
  • High performance to deliver near real-time reporting with minimal latency
  • Robust data security, including encryption at rest and in transit
  • Reliability with minimal downtime and regular backup procedures
  • User-friendly interface for both technical and non-technical users

Projected Business Benefits and Success Metrics

The implementation of the advanced BI solution is expected to enable precise, real-time operational insights, significantly enhance decision-making agility, and support scaling efforts. It aims to reduce reliance on manual reporting, increase data accuracy, and improve KPI visibility, ultimately fostering faster strategic responses and operational excellence.

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