Skip to content

Kfredericha/Project-Based-Internship---Big-Data-Analytics

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 

Repository files navigation

Project Based Internship - Kimia Farma Big Data Analytics

Project Overview

This project analyzes the sales performance of Kimia Farma from 2020 to 2023 by integrating multiple datasets, including transaction, product, branch, and inventory data. Using Google BigQuery for data processing and Looker Studio for visualization, the project builds an interactive dashboard to explore key business metrics such as total sales, profit, transaction volume, regional performance, and customer ratings.

The goal of this project is to generate actionable insights that help evaluate business performance and support data-driven decision making.

Business Problem

Kimia Farma operates many branches across Indonesia and generates large volumes of transactional data. However, the data is stored across multiple datasets, making it difficult to analyze overall business performance.

Without a consolidated dataset, it becomes challenging to evaluate:

  1. Overall sales and profit performance
  2. Branch-level operational performance
  3. Regional sales distribution
  4. Customer satisfaction based on transaction ratings

This project aims to integrate these datasets into a unified analytical table to enable efficient analysis and visualization.

Dataset

Download Dataset

The analysis uses four main datasets:

  1. Final Transaction Contains transactional sales data including:
  • transaction_id
  • date
  • branch_id
  • product_id
  • discount_percentage
  • rating_transaksi
  1. Product Contains product information:
  • product_id
  • product_name
  • price
  1. Branch Office Contains branch information:
  • branch_id
  • branch_name
  • kota
  • provinsi
  • rating_cabang
  1. Inventory Contains product inventory information per branch.

Dashboard

Full Dashboard

An interactive dashboard was created in Looker Studio to visualize business performance. The dashboard includes:

  • Total Sales
  • Total Profit
  • Total Transactions
  • Average Transaction Rating
  • Revenue Trends (2020–2023)
  • Top Provinces by Transactions
  • Top Provinces by Net Sales
  • Branch Rating vs Transaction Rating Analysis
  • Profit Distribution by Province

Key Insights

  • Kimia Farma generated approximately Rp346.96B in sales and Rp98.54B in profit from 672K transactions between 2020 and 2023.
  • Sales and transaction volumes are concentrated in Jawa Barat, Jawa Tengah, Jawa Timur, and Sumatera Utara.
  • Revenue trends show relatively stable performance across the analyzed years.
  • Several branches show high branch ratings but lower transaction ratings, indicating potential issues in transaction service quality.
  • Profit contribution varies significantly across provinces, highlighting opportunities for regional optimization.

Business Recommendation

  1. Improve Transaction Experience Branches with high branch ratings but lower transaction ratings should improve:
  • service efficiency
  • cashier workflow
  • queue management
  1. Expand in High Performing Regions Regions such as Jawa Barat and Jawa Timur show strong demand and could benefit from:
  • additional branches
  • expanded healthcare services
  • increased marketing investment
  1. Strengthen Sales in Low Performing Regions To improve performance in lower sales regions:
  • implement targeted marketing campaigns
  • introduce promotional programs
  • collaborate with local healthcare providers
  1. Optimize Product Strategy Profitability can be improved by:
  • promoting higher-margin products
  • introducing product bundles
  • optimizing pricing strategies

About

This project analyzes Kimia Farma’s sales performance from 2020 to 2023 by integrating multiple datasets, including transactions, products, inventory, and branch information. Using BigQuery for data processing and Looker Studio for visualization, the analysis provides insights into revenue trends, regional performance, and customer satisfaction.

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors