Data extraction

What is meant by Data extraction?

Data extraction refers to the process of capturing and extracting data from various sources or databases to make it available for further analysis, reporting, or processing purposes. This process may involve structured or unstructured data and is commonly used in businesses to collect and consolidate information from heterogeneous data sources.

Typical functions of software in the area of "data extraction" include:

1. Connection to Data Sources: Establishing connections to various data sources such as databases, files, websites, APIs, etc.
2. Data Selection: Selecting specific data or records to be extracted based on defined criteria or queries.
3. Extraction of Structured Data: Extracting structured data from relational databases or table-based file formats such as CSV or Excel.
4. Extraction of Unstructured Data: Extracting unstructured data from text documents, PDFs, web pages, emails, etc., often using text recognition technologies.
5. Data Transformation and Processing: Applying transformations or formatting to extracted data to prepare it for further processing.
6. Automation of Extraction Processes: Automating recurring extraction processes through scheduled timings or event triggers.
7. Data Preview and Validation: Previewing the extracted data and validating it against defined rules or patterns to ensure data quality.
8. Scalability and Performance: Supporting large volumes of data and fast extraction speeds to meet enterprise demands.
9. Security and Privacy: Implementing security measures to protect confidential data during the extraction process.
10. Integration with Other Systems: Ability to integrate with other data processing or analytics tools for seamless further processing of the extracted data.