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Development of a Scalable Data Analytics Platform for Enhanced Business Insights
  1. case
  2. Development of a Scalable Data Analytics Platform for Enhanced Business Insights

Development of a Scalable Data Analytics Platform for Enhanced Business Insights

unosquare.com
Business services

Client Data Challenges Limiting Business Growth

The client faces difficulties in managing and analyzing large volumes of data efficiently, with existing systems causing delays and inaccuracies in reporting. This hampers timely decision-making and reduces overall operational agility.

About the Client

A mid-sized enterprise providing specialized consulting services, seeking to optimize data processing and reporting capabilities to improve decision-making and operational efficiency.

Key Goals for the Data Analytics Enhancement Initiative

  • Implement a robust, scalable data processing infrastructure capable of handling increasing data volumes.
  • Develop an internal analytics dashboard to provide real-time insights into key operational metrics.
  • Improve data accuracy and reporting speed to enable faster decision-making.
  • Ensure secure data management and compliance with relevant standards.
  • Contribute to measurable business improvements, including enhanced operational efficiency and data-driven strategic planning.

Core Functionalities for the New Analytics System

  • Automated data ingestion pipelines from diverse sources, including databases, APIs, and external feeds.
  • Data cleaning, transformation, and normalization components to ensure data quality.
  • A centralized data warehouse or data lake architecture for scalable storage.
  • An internal analytics dashboard with customizable reports and KPIs.
  • Role-based access control to secure sensitive information.
  • Automated alert and notification system for critical data anomalies or thresholds.
  • Mobile and web access for on-the-go data insights.
  • Audit trails and versioning for data change management.

Preferred Technologies and Architectural Approaches

Cloud-based scalable infrastructure (e.g., AWS, Azure, or GCP)
Data processing frameworks such as Apache Spark or similar for large-scale data handling
Modern frontend frameworks for dashboard development (e.g., React, Angular)
Secure authentication and authorization protocols (OAuth, LDAP)

External System Integration Needs

  • Connectors to existing databases and ERP systems for seamless data flow
  • APIs with third-party data sources for external insights
  • Security and identity management solutions

Critical Non-Functional System Requirements

  • System scalability to support data growth, targeting at least 10x increase over 3 years
  • High system availability with 99.9% uptime
  • Data security compliance aligned with industry standards (e.g., GDPR, ISO 27001)
  • Fast data processing with real-time or near real-time reporting capabilities
  • User-friendly interface with minimal learning curve

Projected Business Impact and Expected Outcomes

The new data analytics platform is expected to significantly improve reporting speed and accuracy, enabling faster strategic decisions. Anticipated results include at least 30% improvements in operational efficiency, enhanced data accuracy, and better alignment of business strategies with real-time insights, ultimately driving growth and competitive advantage.

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