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Development of an Internal Analytics Dashboard for Enhanced Data Visibility
  1. case
  2. Development of an Internal Analytics Dashboard for Enhanced Data Visibility

Development of an Internal Analytics Dashboard for Enhanced Data Visibility

elinext.com
Information technology

Understanding Challenges Faced by Technology Firms in Data Management

The client faces difficulties in aggregating, visualizing, and analyzing operational data across multiple platforms, leading to inefficiencies in decision-making processes and limited data-driven insights.

About the Client

A mid-sized technology company specializing in software solutions, seeking to improve internal data analysis and reporting capabilities.

Goals for Improving Data Accessibility and Analytical Capabilities

  • Implement an internal analytics dashboard that consolidates data from various sources.
  • Enhance real-time data visualization to support quick decision-making.
  • Improve data accuracy and consistency across reporting modules.
  • Reduce manual report generation time by 50%.
  • Increase data-driven decision speed and accuracy, aiming for a 30% reduction in decision cycle times.

Core Functionalities for the Data Analytics System

  • Data aggregation interface integrating multiple data sources such as databases, APIs, and cloud services.
  • Interactive dashboards with customizable widgets and real-time updates.
  • Role-based user access control to ensure data security and appropriate data visibility.
  • Automated report generation with scheduling options.
  • Data export functionalities in various formats (CSV, PDF, XLS).

Preferred Technologies and Architectural Approaches

Modern web framework (e.g., React, Angular) for dynamic front-end experience.
Backend data processing using scalable cloud platforms (e.g., AWS, Azure).
Use of data visualization libraries such as D3.js or Chart.js.
Implementation of microservices architecture for modularity and scalability.

External Systems and Data Source Integrations Needed

  • ERP and CRM systems for operational data access.
  • Cloud storage services for report archiving and retrieval.
  • Authentication systems for secure access control.

Key Non-Functional Requirements and Performance Metrics

  • System should handle data loads of up to 10 million records with latency under 2 seconds for dashboard updates.
  • Ensure 99.9% uptime with disaster recovery plan.
  • Secure data in transit and at rest with industry-standard encryption.
  • Scalable architecture to support user growth from 50 to 500 concurrent users.

Projected Business and Operational Impacts

The implementation of the analytics dashboard is expected to reduce manual reporting time by 50%, accelerate decision-making cycles by 30%, and improve data accuracy, thereby enhancing overall operational efficiency and supporting strategic initiatives.

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