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Development of a Real-Time Big Data Analytics Platform with Automated Market Research Capabilities
  1. case
  2. Development of a Real-Time Big Data Analytics Platform with Automated Market Research Capabilities

Development of a Real-Time Big Data Analytics Platform with Automated Market Research Capabilities

netguru.com
Information technology
Business services

Challenges Faced by a Market Research Enterprise in Handling Big Data

The client requires a reliable, scalable, and high-performance tool to ensure top-tier service quality for their prestigious corporate clients. They face difficulties in collecting, processing, and delivering insights from massive datasets swiftly, with a need for real-time reporting via a web-based interface. Existing systems lack automation and integration capabilities needed for comprehensive analysis and engaging client interactions.

About the Client

A large enterprise specializing in market research and data analytics, requiring an advanced platform for processing vast datasets and delivering real-time insights to premium clients.

Goals for Developing a Next-Generation Data Analytics Platform

  • Implement a high-speed data engine capable of collecting and processing large-scale data streams in real time.
  • Deliver real-time, interactive reports accessible through a web-based interface with intuitive visualizations.
  • Automate complex data analyses, including the generation of comprehensive insights and visualizations from Big Data sources.
  • Integrate data seamlessly from multiple external sources and internal systems to provide unified analytics.
  • Develop a modular backend system for efficient data modeling and processing, ensuring scalability and performance.
  • Create a frontend interface utilizing dynamic charting libraries to facilitate various data visualizations and analytics.

Core Functional Specifications for the Data Analytics Platform

  • A robust data engine capable of ingesting and processing large volumes of data instantly from diverse sources.
  • A front-end framework designed to generate and display multiple types of dynamic visualizations and reports.
  • A backend data modeling module implemented in a scalable programming language to manage data transformation and analysis.
  • Support for automated analysis workflows to generate insights without manual intervention.
  • An intuitive, web-based dashboard delivering real-time updates and engaging interactions for end-users.

Preferred Technologies and Architectural Approaches

JavaScript frontend frameworks for dynamic charting
Ruby or equivalent backend language for data modeling
scalable data processing architecture for real-time analytics

External System and Data Source Integrations

  • Various data sources and APIs for data ingestion
  • Internal corporate systems for data synchronization

Performance, Scalability, and Security Considerations

  • System should support processing and visualizing thousands of visualizations per month.
  • Real-time data processing with minimal latency.
  • High reliability and uptime to ensure continuous analytics availability.
  • Secure data handling and access controls to protect sensitive client data.

Projected Business Benefits and Performance Metrics

The platform aims to become a leading solution for premium market research, enabling real-time data processing and delivery. It is expected to increase data visualization output by over 4.9 million visualizations, improve report turnaround times, and enhance client satisfaction by providing timely, engaging insights, thereby solidifying the company's position as a top-tier market research provider.

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