Quick! Transform Raw Data 688 page flip-book into Organized Google Sheet

WHEN YOU BID, PLEASE BID FOR THE ENTIRE PROJECT - NOT PER PAGE!!



URGENT DATA CONVERSION PROJECT: 24-HOUR DEADLINE
WHO IS SUITABLE FOR THIS JOB (CRITICAL CRITERIA):
Expert in Advanced Data Cleaning: You must have extensive experience using regular expressions (Regex), text-parsing tools, or advanced scripting to split messy addresses. If you plan to type this out manually row-by-row, do not apply. You will not finish in time.

Flawless Attention to Detail: You must know how to cleanly isolate data fields without leaving broken lines, trailing commas, or raw code formatting artifacts inside cells.

High Availability: You must be able to start immediately upon hiring and dedicate the necessary hours to deliver the complete file on time.

Proven Track Record: You must show past proof of managing massive data scrubbing/extraction projects (thousands of lines) with high accuracy ratings.

TIMELINE & DELIVERY:
Strict Deadline: Exactly 24 Hours from project award.

Mandatory Milestone Check: You must submit a sample test of the first 3 converted pages within 2 hours of starting. We will check your column formatting. If the formatting is correct, you will be cleared to finish the project. If it is wrong, the project will be canceled immediately.

PROJECT OVERVIEW & INSTRUCTIONS
You are required to extract raw text profiles from a 688-page FMM Directory flipbook and convert them into a clean, highly structured Google Sheet.

THE DATA CONSTRAINT:
Total Factory Count: The finalized Google Sheet across all tabs must contain a total count of exactly 4,200 factories. Every single company must be accounted for. Do not skip entries to rush the deadline.

1. Structure of the Google Sheet (Tabs by State)
The Google Sheet must be split into tabs. Each tab must contain data for only one specific state. Sort each company into its respective tab based on where its physical Factory is located.

Create these exact tabs:

Selangor

Johor

Pulau Pinang

Perak

Negeri Sembilan

Melaka

Kuala Lumpur

Kedah

Pahang

Terengganu

Kelantan

Perlis

Sarawak

Sabah

2. Exact Columns Required
Every company entry must be on a single row, cleanly separated into these exact columns. Do not combine information into a single cell.

Column A: Company Name (Full registered name)

Column B: Office Address (Street address only; do not include city or state here)

Column C: Office City (The city/town of the office only)

Column D: Office State (The state of the office only)

Column E: Factory Address (Street address of the actual factory; do not include city or state here)

Column F: Factory City (The city/town where the factory is physically located)

Column G: Factory State (The state where the factory is located—this must match the tab name)

Column H: Number of Employees in Factory (The workforce count at the factory site)

Column I: Number of Employees in Office (The corporate/administrative staff count)

Column J: Product Manufactured (Brief description of products made)

Column K: Phone Number (Primary contact number)

Column L: Email (Primary corporate contact email)

Column M: Key Executive Name (CEO / Managing Director / Factory Director)

Column N: Key Executive Title (Their exact role title)

Column O: Business Enquiry Details (Any secondary contact names, extra lines, or commercial notes)

3. Absolute Data Quality Rules
Perfect Address Splitting: You must extract and separate the street addresses from the City and State columns. Full, un-separated block addresses inside a single cell will be rejected.

Missing Information: If an entry lacks a specific field (like an email or employee count), leave that cell blank, but do not skip the company. We need the row entry to maintain our target total count.

Clean Layout: Capitalization must be consistent (e.g., "Sdn Bhd", not "SDN BHD"). Remove all raw code fragments, awkward text wrapping, or extra spaces.