What is data extraction? And how to automate the process

**Data extraction is the process of pulling usable, targeted information from larger, unrefined sources, similar to crabbing for crabs in a bay, where a tool sifts through vast amounts of data to extract specific morsels. Data extraction allows businesses to distill big datasets into actionable resources like targeted leads and financial numbers. The purpose of extracting data is to make it usable, often beyond the intended purpose of the data. Data extraction can be categorized as either structured or unstructured, with structured data being easily searchable and crawlable, while unstructured data requires additional categorization like keyword tagging and metadata. There are two main methods of data extraction: incremental and full, where incremental extraction pulls only altered data and full extraction indiscriminately pulls data from a source at once. Data extraction tools can be categorized as cloud-based, batch processing, on-premise, or open-source, with automation being a key benefit of using such software, improving decision-making, enhancing visibility, increasing accuracy, and saving time.

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