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Development of an Internal Analytics Dashboard for Enhanced Data Accessibility and Decision-Making
  1. case
  2. Development of an Internal Analytics Dashboard for Enhanced Data Accessibility and Decision-Making

Development of an Internal Analytics Dashboard for Enhanced Data Accessibility and Decision-Making

elinext.com
Information technology

Client Data Management Challenges Hindering Decision-Making

The client faces significant difficulties in accessing, analyzing, and visualizing dispersed data across multiple systems. This hampers timely decision-making and limits operational efficiency, especially in managing complex data flows for diverse service operations.

About the Client

A mid-sized technology firm with an extensive service portfolio seeking to streamline its data analysis and reporting capabilities.

Goals for Building a Centralized Data Analytics Platform

  • Implement a comprehensive internal analytics dashboard that consolidates data from various sources for real-time insights.
  • Improve data accessibility and visualization to support strategic and operational decision-making.
  • Reduce data retrieval time to under 2 seconds for key metrics.
  • Enhance data security and compliance with industry standards.
  • Increase user engagement with data reports and dashboards by 40% within the first six months.

Core Functionalities for the Analytics Dashboard

  • Secure login and role-based access controls to ensure data privacy.
  • Real-time data ingestion from multiple internal systems and external data sources.
  • Customizable dashboards with drag-and-drop widgets for various data visualizations.
  • Advanced filtering and drill-down capabilities for detailed data analysis.
  • Automated report generation and scheduling for recurring insights delivery.
  • Data export options in multiple formats (CSV, PDF, Excel).
  • Alerts and notifications for key data threshold breaches.

Technology Stack and Architectural Preferences

Cloud-based data warehousing solutions (e.g., AWS Redshift, Google BigQuery) for scalable storage.
Modern front-end frameworks (e.g., React.js or Angular) for dynamic user interfaces.
Backend services leveraging Node.js or Python for data processing and API development.
Data visualization libraries like D3.js or Chart.js.

Essential External System Integrations

  • Internal databases and data sources for comprehensive data aggregation.
  • Third-party analytics or BI tools for extended capabilities.
  • User authentication providers for secure login.
  • Notification services for alert distribution (e.g., email, SMS).

Performance, Security, and Scalability Standards

  • System should support up to 500 simultaneous users with minimal latency.
  • Dashboard data refresh rate within 2 seconds for critical metrics.
  • Compliance with industry security standards such as ISO/IEC 27001.
  • System uptime of at least 99.9%.
  • Data encryption at rest and in transit.

Projected Business Benefits and Efficiency Gains

The implementation of the analytics dashboard is expected to significantly improve data-driven decision-making efficiency, reducing data retrieval and report generation times. The platform aims to boost user engagement with analytics by 40%, support faster strategic decisions, and enhance data security. Overall, the project is anticipated to generate measurable operational improvements and support scalable data growth.

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