Data Management for Global Techify

File Handling Made Easy, Data Management Done Right!!!

Problem Statement for Global Techify's E-commerce Data Management Project

Global Techify, an electronics retail company, is facing challenges in efficiently managing and utilizing its vast array of product information. Effective data management is crucial for optimizing marketing strategies and making informed business decisions. As part of their initiative to streamline their data handling processes, Global Techify has embarked on a project to enhance their ability to load, modify, and save product data across various file formats. This capability will enable the company to maintain accurate and up-to-date product information, leading to improved operational efficiency and customer satisfaction.

The primary objective of this project is to develop a robust system using Python that allows for the efficient handling of multiple file formats containing crucial product data. The system will enable the loading, modification, and saving of data in CSV, JSON, and TXT formats, which are integral to the company's operations.

Data Description

The data for this project is provided on this which includes detailed sales data and product information. The structure of this dataset is as follows:

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Sales Data: This CSV file contains the sales figures for various products over a 14-day period, where each row represents a product identified by its SKU. The columns Day1 to Day14 provide daily sales figures.

Product Descriptions: This directory holds TXT files named after product SKUs (e.g., description_ELEC1234STU.txt). Each file contains a textual description of the respective product.

Product Details: This directory contains JSON files, named similarly by product SKUs (e.g., details_ELEC1234STU.json). These files include detailed attributes such as specifications, categories, and pricing of the products.

Stage 1: Setup and Data Loading

The initial stage focuses on setting up the project environment and loading existing data files.

Task 1: Import Required Modules

Import Python libraries necessary for file handling and data manipulation, such as pandas for handling CSV files and json for JSON files.

Task 2: Load Data

Load the existing data from the provided CSV, JSON, and TXT files into appropriate data structures for further processing.

Stage 2: Data Creation and Updates

This stage involves the creation of new entries or updating existing product information.

Task 3: Add or Update Sales Data

Implement functions to add new sales records to the CSV file or update existing sales information based on product SKU.

Task 4: Add or Update Product Details

Create or modify entries in JSON files that store product details such as specifications, pricing, and category.

Task 5: Add or Update Product Description

Update or add new product descriptions in the corresponding TXT files, ensuring each description aligns with its respective SKU.

Task 6: Update Function

Develop a unified function that accepts product SKUs and data, checks for existing entries, and updates or adds data across all file types as necessary.

Stage 3: Data Persistence

The final stage focuses on saving the updated data back to the disk.

Task 7: Save Data to Disk

Implement a method to safely write modified data back to their respective file formats. Ensure data integrity and consistency across files, with proper handling of file access and errors to prevent data loss.

By efficiently executing these tasks, the system will streamline the management of product information, thereby enhancing the ability to swiftly update and retrieve product data, which is essential for maintaining a dynamic and responsive e-commerce platform.