The dramatic increase in the volume of unstructured and semi structured data has made data extraction vital since businesses need to convert all data into machine-readable formats for analysis. While the need for data extraction grows, it enables businesses to save time and improve their decision-making processes. With such benefits, data extraction software now helps users to automatically pull data from various sources by applying suitable layouts and export structured data to the target destination.

What is data extraction?

Data extraction is the process of turning unstructured or semi-structured data into structured data. In other words, this process enables unstructured or semi-structured data to become meaningful insights that will be available for reporting and analytics.

For example, data extraction can automate invoice processing, so payments and record-keeping can be automated. With this automation, businesses can directly make further analysis and use these insights for their reports.

Source: Data Entry Export

Why do we need to auto-extract data?

Data extraction is a vital process to automate structured data collection for using them in further analysis. The process provides necessary data from various sources like invoices, emails, or contracts. These data help to provide valuable insights and analytics for decision making. Top benefits associated with data extraction are as follows:

  • Better Decision Making: Data extraction allows users to extract meaningful information hidden inside unstructured data sources, such as customer churn rate.
  • Reduction of manual errors: Many businesses still rely on their employees to manually enter the information stored in documents in their systems. This results in errors due to incomplete records, missing/incorrect information, and duplicates. By automating the data extraction process, structured data collected will include fewer errors, and business reports will be more accurate. Irislink estimates that automated data extraction can prevent 80% of these errors by providing more accurate data.
  • Faster processes: Manual data entry takes more time and prone to errors. Auto-extracting data would prevent companies from spending extra time on re-entering data and ensure them to extract data faster.
  • Employee motivation: While the volume of unstructured data rapidly increases, manual data extraction is a tiring task for employees. This repetitive process doesn’t require any high-level skills, and it demotivates employees during their work-time. Data extraction automation would save employees from this demotivating task and help them to focus on their main duties. This also improves their productivity by preventing distractions.

What are the key features for a data extraction solution?

If your business is looking for data extraction software, it should be able to possess certain functions to have a higher impact on the workflow. While choosing a data extraction vendor, you should consider the following factors:

  • Ability to extract structured data from General Document Formats: Semi-structured or unstructured data can come in various forms. An ideal data extraction software should support general unstructured document formats like DOCX, PDF, or TXT to handle faster data extraction. By recognizing popular document formats, businesses will be able to make use of all the data they receive.
  • Exporting Data into Widely Used Applications: Users should be able to export the extracted data to other applications that are commonly used, such as SQL Server, Oracle, or Tableau in a variety of formats such as XML or JSON. This enables businesses to access meaningful information faster and provides time-saving.
  • Improving Data Quality: The data extraction software should be able to clean the data automatically according to the rules defined by its users for data improvement. For example, if there are any negative quantity values extracted from invoices, the software needs to detect and delete them. 
  • Advanced processing/enrichment capabilities: Extracted data can be enriched using company’s own data or public data. Additionally, advanced processing allows data extraction vendor to add further value. For example, Hypatos is capable of performing automated VAT compliance checks on the invoices that they process, enabling companies to identify compliance risks during extraction without any additional effort.
  • Real-Time Extraction: Having real-time data is essential for companies. If the data is not up-to-date, businesses can make wrong decisions that may cause severe costs. Thus, data extraction software should be able to extract real-time data with the help of automated workflows. Businesses can have more accurate information and prepare data faster for business intelligence in this way. For example, to analyze the current inventory levels, businesses need real-time extraction of structured information like order ID, items sold, quantity, amount from the sales invoices.
  • User-Friendly Interface: The data extraction software should have an intuitive interface where users can easily adjust various data extraction templates. It shouldn’t require a high level of technical skills to handle data, and users should use it with little to no coding involved.

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