Data Entry
Data entry refers to the process of manually or digitally inputting information into a database, spreadsheet, or other structured system. It typically involves capturing and organizing raw data for easy access and analysis.
Key Features of Data Entry
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Manual or Automated:
- Manual: Involves human input, often via keyboards, scanners, or voice recognition systems.
- Automated: Includes using technologies like OCR (Optical Character Recognition) or data entry software.
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Common Sources:
- Paper documents (forms, invoices, surveys)
- Digital documents (emails, spreadsheets)
- Direct system input (e.g., web forms, online applications)
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Skills and Tools Required:
- Attention to detail and accuracy.
- Proficiency in data management tools (e.g., Excel, database software).
- Speed and familiarity with typing or scanning tools.
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Applications:
- Updating customer databases.
- Inputting sales or inventory records.
- Digitizing handwritten forms.
Data Extraction
Data extraction refers to the process of retrieving specific information from various sources, such as databases, files, or systems, for further processing or analysis.
Key Features of Data Entry
- Manual or Automated:
- Manual: Reading and retrieving information manually from documents or systems. o
- Automated: Utilizing software or scripts (e.g., web scraping tools, APIs) to extract data.
- Common Data Sources:
- Databases or spreadsheets.
- Web pages or APIs.
- PDFs, scanned images, or email messages.
- Techniques and Tools:
- SQL queries for structured database extraction.
- ETL (Extract, Transform, Load) tools for large-scale data processes.
- Machine learning and natural language processing (NLP) for extracting information from unstructured data.
- Applications:
- Generating reports from stored data.
- Extracting insights from customer feedback or reviews.
- Collecting data for market research or competitor analysis.
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