A barrier in successful Data structure is the range of formats in which data is kept.
This has a particularly big influence on industries with a lot of Unstructured Data and a lot of bureaucratic laws and processes, like:
Here are a few things to think about while Automating your Data structure operations
A Data lake collects and stores data from paper-based and Unstructured digital documents (emails, presentations, PDFs).
The Data is converted into a format that may be used to train a model. Data annotation, cleansing, and organizing are examples of pre-processing.
A model is taught to recognize certain keywords associated with a particular use case. (e.g., medical and financial) and learns standard formatting as an output.
The model can take Unstructured Data and organise it into a consistent and ordered format.
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