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Development of an Advanced Data Analytics Platform for E-Commerce Service Expansion
  1. case
  2. Development of an Advanced Data Analytics Platform for E-Commerce Service Expansion

Development of an Advanced Data Analytics Platform for E-Commerce Service Expansion

n-ix.com
eCommerce
Financial services

Identifying Challenges in Enhancing Data Reporting for E-Commerce Platforms

The client aims to deliver more precise, visually engaging data analytics reports for their largest customer, addressing limitations in existing reporting tools, and seeks to expand their service offerings with comprehensive data insights to improve internal decision-making and customer satisfaction.

About the Client

A large-scale provider of cloud-based eCommerce and subscription management solutions, focusing on monetizing digital goods and SaaS platforms across diverse industries.

Goals for Developing a Robust Data Analytics Infrastructure

  • Develop a modern, scalable data platform capable of aggregating real-time and batch data sources.
  • Implement an advanced reporting solution that provides detailed, visually informative analytics tailored for client needs.
  • Enhance internal analytics capabilities to improve business decision-making processes.
  • Establish strong data governance, security, and compliance mechanisms within the platform.
  • Enable the client to extend data reporting services to attract additional customers and increase value proposition.

Core Functional Requirements for the Data Analytics and Reporting System

  • Data ingestion pipelines capable of extracting data from on-premise databases (e.g., Oracle) and cloud-based systems via CDC (Change Data Capture).
  • Data transformation processes to filter, clean, and structure raw data for analysis.
  • Multi-tiered data storage architecture comprising raw, processed, and aggregated datasets.
  • Integration with data warehouse solutions to support complex analytics and reporting.
  • User-friendly, interactive dashboards and reports utilizing business intelligence tools such as Power BI or equivalent.
  • Role-based access controls and security measures to ensure data protection and compliance.

Preferred Technologies and Architectural Frameworks

Cloud platform: AWS (including DMS, S3, EMR, Glue, Lake Formation, KMS, IAM)
Data processing: Apache Spark
Data warehousing: Snowflake
BI Tools: Power BI or equivalent
Automation and infrastructure as code: Terraform, GitLab

External System Integrations for Data Aggregation

  • On-premise Oracle databases using CDC for real-time data capture
  • Cloud-based enterprise systems via REST API (e.g., ERP, CRM)
  • Data storage in cloud object storage and data warehouse solutions

Key Non-Functional System Requirements

  • Scalability to handle increasing data volumes and user load
  • High data security and compliance with data governance policies
  • Near-real-time data processing and reporting capabilities
  • System reliability and high availability for continuous operations
  • Performance optimization for complex queries and dashboard responsiveness

Projected Business Benefits from Implementing the Data Analytics Solution

The new data analytics platform is expected to significantly enhance the client’s service offering by providing comprehensive, real-time insights, facilitating better business decisions internally, and enabling the client to attract additional customers by offering advanced reporting capabilities. Key metrics include improved data processing efficiency, stronger data security, and expanded analytical reach, ultimately driving growth in customer base and revenue.

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