We understand the importance of data quality. In this article we will explain more about the basic principles we use at Clappform to guarantee high data quality and we will elaborate on how you can achieve more with several data sources. If you have any questions or comments with regards to this article, feel free to reach out to us.
Data quality is one of the most important aspects for decision making. Why? Having correct data at your fingertips ensures that you can make informed decisions (based on actual data) and ultimately reduce risks. At Clappform we are always looking for ways to ensure that our clients have access to high quality data. How do we do this?
Within Clappform we help our clients to ensure a higher data quality
Data quality challenges
It often happens that large volumes of unstructured data are not complete. Companies have a lot of data, but often this data is incomplete or incorrectly entered. For example: someone who makes a typo in his Excel or PDF document. You may think that the impact of such a minor mistake (such as a typo) does not really impact any real business decisions. However, if this information ends up being missing or excluded from data analytics models, decisions can be impacted by it. Next to typos and other mistakes people can make when they manually insert information, is the challenge of using PDFs as data input. The standard PDF that is created from a Word document is easy to read, but in reality, companies often print, sign and scan a document. After all those steps, some information may not be that easy to extract from the PDF document any longer. Especially when the document has been folded, coffee has been spilled on it or there is some other damage done to the document, just to name a few examples.
One way to correctly extract data from PDF documents that have been damaged (to a greater or lesser extent) is by using optical character recognition (“OCR”). With OCR you can convert an image into (or back in) a machine-readable text document. Today, we still need to do a final check of the mechanically restored data as the data is often still incomplete or incorrect. These challenges remain as long as companies use PDF documents as their final document for contracts, especially because these PDF files are damaged from time to time (throughout the process). Creating and maintaining contracts in a structured format from cradle to grave will ultimately accelerate the use of artificial intelligence and reduce the number of mistakes that are made.
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