Step-by-Step Guide to Convert PDF to Google Sheets

Converting PDF files to Google Sheets offers businesses greater flexibility in analyzing data, performing calculations, visualizing, and gaining insights. These hidden insights drive operational efficiency and maximize business growth. 

This article discusses the importance of converting PDF files to Sheets, preparation techniques to optimize data for conversion, a step-by-step process to extract data to Sheets using Docsumo, and best practices for managing extracted data.  

Importance of converting PDF Files to Google Sheets 

a. Data visualization

Extracting data from PDF files and converting them into Google Sheets enables organizations to present large sets of raw data in an organized form using charts and share data easily with stakeholders and investors. 

For instance, businesses can use various graphs, charts, tables, and maps to present product sales performance over a specific period and unlock hidden insights to increase revenue.  

b. Seamless integration 

Accurate data extraction from PDF files to Google Sheets helps businesses integrate data seamlessly with other Google applications, such as Google Forms, Slides, and Finance. 

Businesses can also integrate Google Sheets with third-party applications such as Zapier and Salesforce for data transfer and automated workflows. 

c. Real-time collaboration 

Google Sheets allows real-time collaboration between users and employees. You can edit the sheet simultaneously with other team members and changes are saved automatically to Google servers. The sidebar chat is where employees can discuss the changes made. 

d. Automate calculations 

Data conversion from PDF to Google Sheets helps businesses perform complex calculations using formulas within Google Sheets. From basic operations to advanced functions such as IF, AND, OR, NOT, VLOOKUP, INDEX, and MATCH, businesses can automate calculations and analyze huge volumes of data easily. 

f. Security and accessibility 

Google Sheets allows users to set up access controls for who can view, edit, or comment on files. Plus, when multiple people work on spreadsheets, version control (or the lack thereof) becomes a huge challenge. 

Google Sheets solves this shortcoming with built-in version tracking. Everyone can view the edits made (whether by a single person or multiple participants), and you can rewind to any previous point in the file’s life. Moreover, you can also enable two-factor authentication to add an extra layer of security. 

5 common challenges of data extraction from PDF Files to Google Sheets

1. Scanned documents 

Challenge

Most PDF files are scanned copies of physical documents, making it difficult for basic OCR technology tools to convert PDFs to Sheets accurately. Poor lighting, low-resolution images, skew, noise, low contrast, and density of scanned documents affect accuracy, which is a severe challenge for businesses. 

Solution

To combat this, invest in tools that perform advanced pre-processing techniques such as skew correction and noise removal to extract highly accurate data from PDFs and convert them to Sheets.

2. Complex tables

Challenge 

PDF documents with complex tables hinder organizations, as manual data extraction methods increase costs, time, and errors. Moreover, traditional OCR software tools may need to be more reliable in extracting data from intricate tables because of the high number of errors and inconsistencies. 

Solution 

To avoid this challenge, consider using robust data extraction tools that employ deep learning algorithms to detect tables and capture accurate data. Additionally, the tool must offer effective validation processes to ensure high accuracy while converting PDFs to Sheets.  

3. Scalability 

Challenge

Converting huge volumes of PDF files to Sheets, especially with their complex layouts and formats, can be daunting for employees. Additionally, an overwhelming volume of data demands more time, leading to delayed decision-making and decreased efficiency. 

Solution

To overcome scaling issues, consider implementing intelligent document processing (IDP) software with AI algorithms that learn from your data. The software can be trained to process PDF files in batches, saving both time and cost. 

4. Inconsistent format

Challenge 

PDF files have no specific format and layout, as they can contain tables, charts, texts, and paragraphs spanning multiple pages. Template-based OCR tools can find it difficult to extract data from varying formats, leading to inaccuracy and increased processing time.

Solution 

Train employees to adapt to different PDF formats and create templates for standard layouts and formats in advance to save time while converting PDFs to Sheets.

5. Security and compliance 

Challenge 

Manual and non-standardized data extraction processes while converting PDFs to Sheets involve multiple human touchpoints, which can lead to data leaks and privilege misuse. Moreover, organizations must comply with global and industry regulations such as GDPR, SOC-2, HIPAA, and The HITECH Act to protect sensitive data against breaches and avoid regulatory fines.

Solution 

Choosing a data extraction tool that offers enterprise-grade security, cloud storage, encryption, access controls, and compliance with industry-specific laws. 

Preparing your PDF Files for sheet conversion

Preparation processes are mainly for PDF files, and here are some steps that optimize PDF files for greater accuracy while converting them to Google Sheets: 

1. Organize documents

Collect PDF files that require extraction from different sources and organize them in a single folder to ensure quick access and easier ingestion into the data extraction tool. If your PDF files are large, split them into smaller ones to avoid complexity while converting them to Sheets and extracting data with fewer errors. 

2. Data cleaning 

Your employees can analyze the data manually for errors, redundancies, missing values, and discrepancies. Resolve mistakes and fill values to prevent errors and improve the efficiency of the data extraction. 

3. Template creation 

Create templates for standard layouts and formats of different PDFs. This helps standalone OCR tools focus on specific areas and extract accurate data, saving time and effort in the data extraction process. 

4. Pre-process documents

Pre-processing files before extraction helps OCR to distinguish and recognize characters from the background. Skew correction, noise removal, merging and splitting pages, and contrast and density adjustments are advanced techniques that enhance data clarity.

Step-by-step guide to data extraction from PDF Files to sheets 

Automated data extraction software solutions automatically convert data from PDF files to Google Sheets. You can have humans in the loop for final review and data approval, saving time and costs and reducing errors. 

A detailed step-by-step process to help you automate end-to-end data extraction from PDF files to Google Sheets: 

1. Identify your conversion technique 

Analyze the PDF files for charts, images, graphs, complex tables, paragraphs, and scanned texts to decide on the conversion technique and data extraction tool. Depending on the combination of these formats, you can finalize between manual and automated data extraction processes and choose the data extraction tool if needed. 

2. Choosing the right data extraction tool 

Choose a data capture solution to extract data with a high accuracy rate. Although standalone OCR technology tools capture data from PDFs, they have limitations such as inaccuracy, template creation for varying formats, and increased time when extracting data from complex documents with tables.

Unlike traditional OCR tools, the best automated data capture solutions, like Docsumo, overcome these bottlenecks by integrating OCR with AI and ML technologies. The software automatically learns and adapts to different layouts and templates of PDFs and converts data to Google Sheets with a 99% accuracy rate. 

Use Docsumo’s pre-trained API models to train your APIs according to the document type and data requirements. Moreover, Docsumo automatically validates the extracted data with existing databases using Excel-like formulas to ensure accuracy. 

Now, let's use Docsumo as an example to understand how data extraction from PDF files to Sheets works.

3. Sign up on the Docsumo platform

Visit Docsumo's website and click ‘Start a 14-day free trial’. Submit details such as name, company, work email address, mobile number, and document type, and set a strong password. Docsumo allows you to process 50 documents for free and upgrade to paid plans for data extraction at scale. 

4. Upload and organize documents

After signing up, go to ‘Document Type’ and choose the particular document type to upload PDFs. Click ‘Upload’ and ingest PDF files from your local computer. 

You can also auto-import documents from your mail or Zapier to save time. Ensure that PDF files are decrypted before uploading to capture data without interruptions.  

5. Data extraction 

Once you upload the files, Docsumo starts extracting data with its pre-trained API models. It first captures key-value pairs (a set of two data items) from files. For instance, if you're extracting data from PDF bank statements, Docsumo would extract the bank name, address, date, customer’s name, address, and account number. 

It then proceeds to capture line items from tables using deep learning algorithms and neural networks such as table detection and feature recognition algorithms. In this case, it captures particular transactions or income from tables within bank statements.  

6. Customizing extraction settings

Though Docsumo captures data automatically, you can customize the fields to meet business requirements. Click ‘Edit field’ to add or remove fields and extract only critical data from PDF files. 

7. Reviewing extracted data 

After data extraction, Docsumo automatically validates the extracted data with existing databases and internal computations. You can also review the data manually to train the model to yield a 100% accuracy rate in the new documents. This validation process ensures high accuracy of more than 99.9%, and you can use this data directly for business operations. 

8. Automating data extraction for large document sets

Once you understand how Docsumo works, you can extract data simultaneously from huge volumes of PDF files and convert them to Google Sheets. Docsumo is designed and trained to process documents in batches, helping you automate end-to-end document processing workflows. 

Here are some benefits that reinforce the importance of automated data capture tools like Docsumo:

• Increased efficiency and productivity
• Over 99.9% accuracy rate 
• Reduce processing time to 30-60 seconds 
• 95% straight-through processing (STP) rate
• Operational costs reduced by 60-70% 
• Compliance with HIPAA, SOC-2, and GDPR 
• Robust security features such as role-based access and cloud storage

9. Integration into workflow

Download the extracted data in your preferred format (Google Sheets) and integrate it with your industry-specific CRMs, ERPs, and accounting software solutions. The data flows across different systems, reducing data transfer errors. 

Best practices for managing extracted Data from PDF to Sheets

a. Data validation

Data validation is critical to ensuring the integrity and completeness of the extracted data. Validate the captured data with its source PDFs and resolve discrepancies, errors, and missing values. Additionally, data validation functions in Google Sheets, such as VLOOKUP, IF, and COUNTIF, can be used to compare values and correct errors. 

b. Access controls 

Set up access controls to decide who can edit, view, comment, and download Sheets. You can control permissions for the entire folder, Sheets, or specific cells to prevent data breaches and leaks. Additionally, you can encrypt these files with deciphered texts to add an extra layer of security. 

c. Backup data 

Backup your data regularly and maintain at least three copies on different storage types, including cloud, external hard drive, and USB flash drive. This prevents data loss in accidental file deletion, malware and ransomware infections, and computer crashes. You can retrieve the data files, restore them, and run business operations without hindrance. 

d. Security and Compliance

Maintain compliance with industry-specific legal regulations such as GDPR, HIPAA, The HITECH Act, and SOC-2. Adhere to standard security protocols, including encryption, two-factor authentication, and access controls, to protect data against cyberattacks and avoid regulatory fines. 

e. Employee training

Invest in training your employees on using advanced tools for data extraction and the best practices related to data handling to ensure accuracy and security. 

f. Data analysis and reporting 

Analyze the extracted data using Google Sheets’ intuitive data analysis and visualization features, such as charts, graphs, pivot tables, and dashboards. Derive insights, create reports, and share them with stakeholders to finalize business operations that maximize sales and revenue. 

g. Integration 

Integrate the extracted data with accounting software solutions, ERPs, CRMs, and other applications your business uses for error-free data transfer.

Conclusion: How automated data extraction from PDF Files to Google Sheets help? 

Converting PDF files to Google Sheets helps organizations with accurate data analysis, reporting, and visualization. Automating this conversion using data extraction tools saves time, reduces errors and operational costs, and improves efficiency. 

Docsumo helps you capture data from PDF files and other documents using Intelligent Document Processing technology (IDP) and extracts data with a high accuracy rate of over 99.9%.

Sign up for a free trial of Docsumo to start extracting data from PDF files into Google Sheets.