Revamping Data Analytics for a Leading Pharmacy Chain

Healthcare

Revamping Data Analytics for a Leading Pharmacy Chain

03

Engineers

04

Months

70%

Data visibility

Overview

A leading pharmacy chain was facing a number of challenges with their data analytics including data fragmentation and limited real-time visibility. We developed a custom solution which is scalable and flexible, and it could be easily adapted to meet the changing needs of the client.

Services

Data Engineering, Machine Learning, Visualization

Technology

Python, Apache Kafka, Apache Spark, PostgreSQL, Tableau, Docker, AWS

Location

New York, USA

Challenges

Data Fragmentation: The client had vast quantities of customer data scattered across their 250+ retail outlets. The fragmentation made it challenging to aggregate, analyze, and draw actionable insights from the data.
Limited Real-Time Visibility: Without an efficient data supply chain, the client lacked real-time visibility into crucial business operations. This limitation affected decision-making and response times to changing market trends and customer needs.
Dashboard Integration: The client had existing dashboards for different business functions, but these were disconnected and didn’t offer a holistic view of business performance and customer behavior.

Solutions

Unified Data Management: We developed a robust data supply chain management system, which collected, cleaned, and structured data from all retail outlets into a unified data warehouse. This central repository enabled effective data analysis and decision-making.
Real-Time Data Analytics: Leveraging advanced data analytics and machine learning algorithms, we built capabilities for real-time analysis of customer data. This enabled the client to spot trends, identify potential issues, and respond swiftly to meet customer needs.

Seamless Dashboard Integration: We ensured seamless integration of the data supply chain with various business dashboards. This allowed stakeholders across the organization to access unified, real-time data insights, thereby driving data-informed decision-making.

Modules implemented

Data Ingestion Module

Extracts data from various sources and ingests it into the data warehouse

Data Processing and Analytics Module

Performs data cleaning, structuring, and analysis

Real-Time Reporting Module

Generates real-time reports and insights based on the analysis

Dashboard Integration Module

Facilitates seamless integration with various business dashboards

High Level Design Architecture

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The Result

Implementation of our solution led to a 35% improvement in the client’s decision-making speed, driven by real-time, data-backed insights. This also resulted in improved customer satisfaction due to timely response to market trends and customer needs.

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