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  • Les Elby

Data Extraction

Data extraction is the process of automatic identification and extraction of frequently recurring patterns from raw data, such as any form of data records or data sets to produce a copy of structured data in a flat file or relational database management system format. The result of this conversion process is much more convenient to store, access and manipulate by computer programs than their corresponding sources.

The need to extract sometimes-repetitive information from unstructured data has grown with the increasing volume of digital records]

Manual extraction is:

  • costly;

  • time-consuming and;

  • error-prone.

The alternative is to use automated data extraction (ADE) tools to transform the unstructured text into structured content.

Why is data extraction important?

Data extraction plays two important roles in any kind of automated document processing project:

1. It provides the basis for other data formatting processes like DocFormatting. Think about it as getting your building blocks ready before starting with construction work. Here at Arcoda we call these building blocks 'segments'. The more segments you have, the more varied are the kinds of analysis that are possible later on - from simple keyword search or a list of all 'customer' names to building a customer segment based on purchase history.

2. It provides the basis for what we call NLP tasks, i.e., finding entities or keywords that are relevant in relation to your business or project. Again, more information is always better and can help you create powerful analysis later on.

Automating Data Extraction

When you automate data extraction the quality of your extracted data should always be under control since you can monitor that process in real time. No more manual work! Besides, it reduces the risk of human errors, which may lead to costs for rectifications or fines by authorities like local supervisory authorities or financial supervisors if they are missed...We have listed a few more benefits of automated data extraction below:

  • Reduces manual efforts and the risk of human errors

  • Increases accuracy, availability and timeliness

  • Speeds up processes, reduces costs and errors

First Steps?

The first step to automated document processing is data extraction. Automated document processing allows you to automate the process of structuring, preparing and enriching documents for further analysis. You can automate all steps of this process or just some of them, depending on your use case.

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