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Data is the backbone of every business organization. If businesses want to enhance their performance and make a good profit, then having precise data is a must because data gives a clear understanding of the market trends, target audience and all other fields related to the business such as operations, marketing and sales.

But have you ever wondered how business organizations extract useful data from massive data sources? Or are you, as a business owner, struggling to find the correct data extraction technique?

Then, you are on the right page because this article will talk about the top 5 data extraction techniques in detail, along with some modern tools. 

Before diving into the topic, let’s understand what data extraction means.

What is Data Extraction?

Data Extraction is the process of pulling the data from one or more sources to analyze it. It also includes structuring the extracted data in a systematic way and integrating it with other tools to derive valuable information from it.

Now that you have a clear understanding of data extraction, let’s delve into the top 5 techniques of data extraction. This is where your active learning begins.

Types of Data Extraction Techniques – 

There are various techniques that people and business organizations use to extract data, including template methods, OCR and manual extraction; let’s understand all of them in detail. 

1. Optical Character Recognition (OCR) – 

Optical Character Recognition is a modern technology that can easily read text from images, scanned documents, and PDFs and convert text into machine-readable data. It is one of the most powerful technologies that not only capture the image of documents but also understand the text. This makes the data extraction process error-free, which eventually helps business owners like you make better business decisions. 

There are mainly 3 types of OCR technology: Simple OCR, Intelligent OCR and Optical Mark Recognition. In simple OCR, you have to provide different font and text images for the OCR system. After this, OCR  matches the text with the input you have given. On the other hand, in Intelligent OCR technology, you don’t need to provide any kind of information to the system. Intelligent OCR completely automates the data extraction process for you. 

OCR uses machine learning technology to recognise characters and extract data from files. This method is more efficient and effective than a simple OCR method.

2. Natural Language Processing (NLP) – 

Natural language processing methods can take you one step further than OCR technology. This is because NLP is all about teaching human language to the computer. With NLP technology, you can extract and analyse data from various sources such as emails, social media posts, or reports. 

Many business organizations use this NLP technology to understand their customers’ opinions from online reviews. You can also use NLP to understand new market trends and make business strategies accordingly.

3. Template Based Extraction – 

Template-based extraction is one of the most effective ways to extract data from various types of invoices, student or employee ID cards, or any document with certain types of structure. To use template-based extraction methods, you must first create a template based on the type of structure of the document from which you want to extract data. 

Once you create templates, you can reuse them for future documents, but only if they have a similar format and structure. 

4. Pattern Recognition – 

This is a very simple and effective data extraction method. Pattern recognition is used by business organizations to identify regularities and patterns within the provided dataset. Pattern Recognition is very useful and effective if you want to extract data from email addresses, phone numbers, or dates. This will automate the process of data extraction, allowing you to save time and financial resources. 

This is effective but a very complicated and time-consuming process. This method divides the data extraction process into 4 phases. The first phase is known as Data Processing. In this process, the system processes the data. It skips the data if it finds it unclear or unclear. 

Then, Pattern Detection starts to extract data such as phone numbers or email addresses. In the third phase, it tries to match symbols, for example, @ or #. This phase is known as Data Matching. After this, in the last phase, it starts to extract data from the document.

5. Manual Data Extraction

Yes, manual data extraction is still a thing! There are a lot of people and business organizations that are using manual data extraction methods. This is because it is tough for other data extraction techniques to extract data from some highly complex documents. 

Manual data extraction is highly time-consuming and error-prone as well. This also required manpower and financial resources to extract useful data from huge amounts of data files. There is very little chance that manual data extraction will help you or your organisation in an effective data extraction process. 

Streamline Your Data Extraction Process with KlearStack – 

KlearStack is one of the top globally recognised data extraction tools. It has built-in OCR technology powered by machine learning (ML) and artificial intelligence (AR). This makes the data extraction process faster and more accurate with minimal effort. You can easily automate the extraction process with just a few clicks.  KlearStack is highly user-friendly, so you don’t need to have any special technical knowledge to use it. 

The best thing about KlearStack is you can integrate your existing management system or tools with KlearStack without any issues.

Other features of KlearStack include – 

• Multi-language support
• Bulk Document Processing
• Multi-page data extraction
• Document Classification
• Automated document splitting
• Self-learning AI Support

If you also want to improve the data extraction process by reducing errors, time, and manual efforts, look no further than KlearStack. You can also book a demo before making your purchase. 

Conclusion

As per the above discussion, you can see that there are various options available for data extraction. You have to see your demands and the type of document you will use to extract the data. Each type of data extraction technique discussed above has its own benefits and drawbacks. Therefore, you must choose a data extraction method that suits your needs. 

It’s best to steer clear of manual data extraction methods, as they often prove to be ineffective. Instead, consider KlearStack, a highly efficient and accurate solution that also comes at an affordable cost. With KlearStack, you can easily extract data from multiple pages simultaneously, without any errors. This not only saves time but also provides a clear and comprehensive view of your business and market. By leveraging KlearStack, you can significantly enhance your decision-making speed and confidence, all while making a cost-effective choice.