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Big Data Analytics Project gives challenges to create data mart design and dashboard on Kimia Farma

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Big Data Analytics Project Salicyl Sales Dashboad on Kimia Farma

Project Description

Challenges :

  • Create a datamart design (Consisting of base tables and aggregate tables)
  • Create a salicycl sales data visualization dashboard
  • Create insights and provide additional complementary data

Project Goal

The project aims to empower the pharmaceutical company with a robust analytical infrastructure and actionable insights to drive informed decision-making in the realm of salicylic acid sales

Tools & Library Used

python-logo   jupyter-logo  

Project Result

Click here to get dashboard link

Base Table

A base table is a fundamental table that stores raw or detailed data at the most granular level.

Aggregate Table

An aggregate table is a summary table that stores precomputed results of aggregations or calculations based on the data in base tables.

Sales per date

Sales per customer

Sales per product

Sales per branch

Dashboard Visualization

Insight

All Kimia Farma Brand Sales

  • The highest revenue based on product category is Ampicillin with 13 M and total quantity 1.3K
  • The highest revenue based on brand category is Marcks with 30.3%, followed by VNS 24.8%, and SLCYL 24.5%.
  • The highest revenue based on sales branch category is Jakarta with 12.2 M.
  • Sales of Kimia Farma are fluctuating with the highest revenue is happened on January 2022 with 20.1 M, while the lowest revenue is happened on March 2022 with 2.5 M
  • The highest revenue based on customer category is Klinik GM 12.2 M with total quantity 1.8K.

Salicyl Brand Sales

  • The highest revenue based on product category is Paracetamol with 5.7 M and total quantity 840.
  • The highest revenue based on sales branch category is Jakarta with 5.6 M.
  • Total revenue of sales Salicyl product is 12 M with total quantity 1,892.
  • The highest revenue based on customer category is Klinik GM 5.6 M with total quantity 880.

Additional Complementary Data

Geographic Information:

  • Latitude and longitude of each distributor’s and brach location
  • City, state, or region where distributors and brach are located.

Promotional Activities:

  • Promotion Type, example discounts, bundle offers, seasonal promotions.
  • Promotion Duration : Start and end dates for each promotional activity.
  • Promotion Channels: Where the promotions are advertised or offered (in-store, online, specific platforms).

Competitor Data:

  • Competitor Product Information
  • Competitor Pricing
  • Market Share
  • Promotional Strategies
  • Customer Reviews and Feedback

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