Table Extraction – What It Is and How to Automate It

If you struggle with keeping tabs on your financial documents or feel absolute resentment just at the thought of manually extracting information from tables, fear not. Many more businesses, just like yours, have to deal with processing tabular layouts daily.  

While this task is a recurring practice, there hasn’t been a solution to efficiently improve the process of extracting and processing tables and tabular layouts. Or so you thought. 

Thankfully, there is a more efficient solution available. By utilizing OCR and AI technology, businesses can extract information from tabular layouts in record time, whether it’s from paper documents or digital files. In this blog, you will learn about table extraction and the challenges of undergoing this process manually. We’ll walk you through how to overcome these issues in just a few steps, using an Intelligent Document Processing (IDP) platform from Klippa. Let us begin!

What is Table Extraction?

Table extraction is the detection and extraction of table information from a document. It involves scanning through the document, detecting and then recognizing the table’s logical structure and content.

Very often, table extraction is done by manually typing its contents into various applications, such as Excel, accounting software, or an organization’s database. While this process doesn’t sound like too much trouble, it can cause great bottlenecks for companies.

Challenges of Manual Table Extraction

Tables are not necessarily an easy format to understand, as they can take many forms and shapes. It might not always be an Excel-looking table with numbers and values, as a table can also contain definitions and full paragraphs, without the presence of bounding boxes. Take a look at the example below.

Tabular layouts can be found in a multitude of documents, for instance, invoices, credit card and bank statements, as well as salary slips. Usually, they are overcrowded with important business information, which can prove difficult to extract at times. 

However, the table might be structured and manually extracting information from tables proves to be a time-consuming and repetitive process. If not carried out meticulously, it can lead to many errors and misinterpretations, damaging the accuracy of your data. Not to mention, it also means additional time and resources spent on correcting these mistakes.

Extracting Table Information

Extracting information from tables, especially from the ones with the bounding-box format, is essentially key-value pair extraction. Oftentimes, tables contain a key and a value, for instance, “Total amount – €100”. This makes table extraction a fairly straightforward process.

However, having one of your employees carefully capture all information from required tables can take hours on end, adding to unnecessary workload and overhead costs. And even then, it doesn’t guarantee high precision. 

IDP software, on the other hand, does not need to go through all these preparatory tasks. The OCR technology embedded in it, immediately recognizes the layout of the table, no matter the placement on the document, and extracts it swiftly and accurately.

Converting Table Information

Even if you manage to manually extract all necessary information from tables, the real challenge is converting it to a suitable format or exporting it to a relevant application, such as Excel, Google Sheets, or any ERP and accounting software. As of now, many organizations struggle to copy and paste information from one Excel sheet to another or by using unsecured applications to extract data from PDFs to Excel.

To simplify manual table extraction and shorten the processing times, users employ automation. Regardless of your organization’s industry, table extraction is a task that is more than likely to occur in data capturing and document processing. The document is read and converted to JSON format by default, leaving you with the option to further convert it to XLSX, CSV, or other machine-readable formats.

Scaling Extraction Processes

Let’s say your financial year was more than great and all this important data you need to transfer to your business’s balance sheets or ledgers is still trapped in a tabular format within your financial documents. Your financial department is now sitting in front of tens or even hundreds of thousands of invoices or financial statements, trying to make sense of it all. In this case, manual processing is not going to cut it. 

With the IDP solution, however, you can do it all within hours. The IDP software can read, classify, extract, and convert all your tabular data from a variety of documents in seconds, making it possible for you and your employees to face any number of documents in a much shorter time.

Use Cases of Table Extraction

Table extraction holds much more importance than it may seem. Important information, such as names, total amounts, dates, and document numbers are most commonly found in a table section of a document.

Salary Slip Processing

Whether you need to extract an overview of your employees’ hours or total amounts paid before the year-end closing, table extraction for salary slips is the most efficient way to get this data extracted in an instant.

Accounts Payable Processing 

In the accounts payable process, table extraction is instrumental in efficiently handling a high volume of documents.  Automatically extracting information from tables minimizes manual effort and errors in receipt capturing and invoice processing. By streamlining accounts payable, your AP team doesn’t need to manually process expense-related documents for hours on end.   

Bookkeeping

To make sure that your business is abiding by regulatory practices and that you don’t lose any financial resources, your books must be balanced. Table extraction of balance sheets and budget reports gives a clear overview of the cash flow and keeps information in a clear and structured way. 

Inventory Management

Logistics documents can take a large amount of time to cross-check. Since most of these documents come in a paper or digital format, PDF table extraction helps any supply chain department capture information from invoices, purchase orders, or bills of lading. This ensures that inventory levels are accurate and payments or deliveries are up to date.

To be able to accurately carry out table extraction and get qualitative results, a well-performing IDP solution is a must. Klippa IDP platform can offer your business all the modes necessary to get your important business information extracted in an instant.

How to Extract Data from Tables with Klippa

Klippa DocHorizon is an Intelligent Document Processing platform that enables you to completely automate the workflow of extracting information from tabular layouts. By integrating various Klippa DocHorizon modules and your preferred applications, you can create an effortless and unique workflow: 

• Data extraction – Get data extracted automatically from all documents containing tables
• Document conversion – Convert documents into a number of business-ready data formats, such as JSON, XLSX, CSV, TXT, XML, and many more
• Document classification – Classifies documents accordingly, so you can organize your documents in a logical manner
• Document verification – Automatically verify documents in numerous ways and detect document fraud

With our intuitive flow builder, you can create your own table extraction workflow, in just 4 easy steps: 

Curious to see how you can get started? Don’t hesitate to contact our experts or book a demo down below!