Data Processing Flashcards
What is Data Processing?
The extraction of useful information from collected raw data.
Why is Data Processing important?
It transforms raw data into meaningful and reliable information for decision-making.
What are the key properties of processed data?
Reliability, relevance, completeness, conciseness, understandability, presentability, and error-free nature.
What are the six stages of Data Processing?
Data Collection, Data Preparation, Data Input, Data Analysis, Data Interpretation, Data Storage.
What happens during Data Collection?
Raw data is collected from sources and converted into a computer-friendly format.
What are common data collection methods?
Statistical populations, research experiments, sample surveys, and byproduct operations.
What happens during Data Preparation?
Raw data is cleaned, organized, standardized, and checked for errors.
Why is domain knowledge important in Data Preparation?
Ensures data accuracy and prevents misleading information.
What happens during Data Input?
Processed data is entered into its destination (e.g., a data warehouse) for analysis.
Why is speed and accuracy important in Data Input?
Because incorrect input can lead to misinterpretation and flawed decision-making.
What happens during Data Analysis?
Data is processed using machine learning and AI algorithms to extract insights.
What happens during Data Interpretation?
The outcomes of data analysis are translated into actionable insights.
What is the final stage of Data Processing?
Data Storage – storing processed data for future use and quick retrieval.
What are some real-world applications of Data Processing?
Automating office environments, managing reservations, monitoring billable hours, and optimizing resource allocation.
What are common use case questions in Data Processing?
What was the best sales month? Which product sold the most? What is the best time to advertise?
