When we talk about data management it’s primarily focused around extracting valuable and constructive information from data. Data mining is what delivers useful information to organizations. Before data is mined, it must go through the various stages of data processing. At a basic level, data processing is the examination and manipulation of raw data to generate new information, but it’s really about far more.
Businesses use big data to make big decisions. Whether it’s to aide in inventory forecasting, conduct target market research or improve marketing efforts, businesses want to make the most out of their data. However, anyone familiar with data processing understands that useful and insightful data doesn’t come instantly. It must undergo specific processes in order to be considered meaningful enough for use in making important business decisions.
Five Stages of Data Processing
1. Gather—Quality of data is all about the reliability and accuracy of the methods used to collect it. While no collection method is 100% accurate from the start, this step screens data and pinpoints areas in the method requiring improvement. Collection methods vary based on the organization’s objectives for future use of the data.
2. Prepare—Physical copies and electronic versions are both prone to errors and omissions; it’s inevitable. Preparation is where mistakes are caught and minimized before they affect data quality. Raw data must be edited, coded and transcribed prior to being processed.
3. Input—Data is converted to a readable format type before being processed. Whether it’s in paper or electronic form, double-keyed or OCR, data must be standardized before processed by a computer. Input methods include scanning, digitizing and other forms of data capture.
4. Process & Store—Data is examined, analyzed and processed via computer software programs. Results are oftentimes electronically stored during this step. Indexing becomes important here because it sets the foundation for how easily searchable and retrievable information is during future use.
5. Output—Dissemination of processed data in a clear, readable format. This may be by means of a report, graphic, audio or video recording, among others depending on the type of data. Output of data is essentially the final result of a data processing project.
To learn more about custom data capture, data processing and data entry solutions, contact ILM today!