Inventory Dataset Cleaning & Structuring
Budget: $10 – $30 USD
We are looking for a freelancer to clean, categorize, and structure our inventory dataset in a way that makes it easy for reporting, dashboard visualization, and searchability. The dataset includes assets, equipment, and consumables (e.g., medications, lab supplies, office items, etc.).
At this stage, we have not yet chosen the system we will use for inventory management, but we are preparing a master sheet that will serve as the foundation for any future system implementation.
1. Data Cleaning & Categorization
- Remove duplicates, inconsistencies, and errors.
- Categorize items into Assets (A), Equipment (Q), and Consumables (C).
- Ensure that items are named in a way that is easy to search (e.g., instead of Female Doctor Uniform Size L, rename as Uniform, Scrubs, Doctor, Female, L).
- Add missing details where possible by researching online sources (e.g., official product descriptions, standard UoM).
2. Develop an Inventory Data Collection Template
- Create a separate sheet for different inventory types, specifying what data needs to be collected for each type:
- Assets (A):
- General Details: Purchase date, quantity, location, department, supplier.
- Equipment (Q - a subset of assets):
- Additional Tracking Details: Serial number, calibration date, maintenance schedule, warranty, model number, manufacturer, assigned department, etc.
- Medications:
Unit of Measurement (UoM) (tablet, ampoule, box, vial, etc.), expiration date, batch number, manufacturer.
- Lab Items:
Unit of Measurement, storage conditions, supplier, specifications (if relevant).
- Office Items:
Stock tracking but minimal details required.
3. Research & Data Enrichment
- For some items, research online sources to fill in missing attributes, including:
- UoM (Unit of Measurement): If missing, research whether the product is measured in mL, g, pcs, etc.
- Technical specifications for specialized equipment (if available).
- Alternative product names (if applicable) to improve searchability.
4. Standardized Naming Convention
- Rename items to be consistent and easy to search.
- Ensure items follow a logical structure with Type, Sub-Type, and Attributes for better filtering.
Example renaming:
• Leica DM 1000 Light Microscope → Microscope, Light, Leica DM 1000
• Surgical Gloves Free Powder 7 → Gloves, Surgical, Free Powder, Size 7
• One Step Glucocheck Device → Glucose Meter, One Step
5. Prepare Data for Dashboard & System Integration
- Ensure categories and subcategories are clearly defined to allow filtering in Power BI or Excel dashboards.
- Design the master sheet in a flexible format to allow for future integration into any chosen inventory system.
Skills Required:
*Experience in Excel data cleaning, structuring, and categorization.
*Familiarity with inventory management best practices.
*Experience in dashboard preparation (Power BI, Excel, etc.) is a plus.
At this stage, we have not yet chosen the system we will use for inventory management, but we are preparing a master sheet that will serve as the foundation for any future system implementation.
1. Data Cleaning & Categorization
- Remove duplicates, inconsistencies, and errors.
- Categorize items into Assets (A), Equipment (Q), and Consumables (C).
- Ensure that items are named in a way that is easy to search (e.g., instead of Female Doctor Uniform Size L, rename as Uniform, Scrubs, Doctor, Female, L).
- Add missing details where possible by researching online sources (e.g., official product descriptions, standard UoM).
2. Develop an Inventory Data Collection Template
- Create a separate sheet for different inventory types, specifying what data needs to be collected for each type:
- Assets (A):
- General Details: Purchase date, quantity, location, department, supplier.
- Equipment (Q - a subset of assets):
- Additional Tracking Details: Serial number, calibration date, maintenance schedule, warranty, model number, manufacturer, assigned department, etc.
- Medications:
Unit of Measurement (UoM) (tablet, ampoule, box, vial, etc.), expiration date, batch number, manufacturer.
- Lab Items:
Unit of Measurement, storage conditions, supplier, specifications (if relevant).
- Office Items:
Stock tracking but minimal details required.
3. Research & Data Enrichment
- For some items, research online sources to fill in missing attributes, including:
- UoM (Unit of Measurement): If missing, research whether the product is measured in mL, g, pcs, etc.
- Technical specifications for specialized equipment (if available).
- Alternative product names (if applicable) to improve searchability.
4. Standardized Naming Convention
- Rename items to be consistent and easy to search.
- Ensure items follow a logical structure with Type, Sub-Type, and Attributes for better filtering.
Example renaming:
• Leica DM 1000 Light Microscope → Microscope, Light, Leica DM 1000
• Surgical Gloves Free Powder 7 → Gloves, Surgical, Free Powder, Size 7
• One Step Glucocheck Device → Glucose Meter, One Step
5. Prepare Data for Dashboard & System Integration
- Ensure categories and subcategories are clearly defined to allow filtering in Power BI or Excel dashboards.
- Design the master sheet in a flexible format to allow for future integration into any chosen inventory system.
Skills Required:
*Experience in Excel data cleaning, structuring, and categorization.
*Familiarity with inventory management best practices.
*Experience in dashboard preparation (Power BI, Excel, etc.) is a plus.