Micro 9 Flashcards
Data Processing Cycle Stages
- Data Collection
- Preparation
- Input
- Processing
- Output / Result
- Storage
This is the first stage of the cycle, and is very crucial, since the quality of data collected will impact heavily on the output
Data Collection
The collection process needs to ensure that the data gathered are both defined and accurate, so that subsequent decisions based on the findings are valid
Data Collection
Some people consider this as a part of processing but does not involve any processing
Preparation
It is the manipulation of data into a form suitable for further analysis and processing
Preparation
This is the feeding of collected data, raw and sieved data for processing
Input
It is the task where verified data is coded or converted into machine readable form so that it can be processed through an application
Input
This is the step where data is processed by electronic data processing, mechanical processing, processing system or other means
Processing
The processed data is delivered in the form of information/ results in this step. Once the result or output is received, it may further be processed or interpreted
Output / Result
is the stage where processed information is now transmitted and displayed to the user
Output and interpretation
is the last stage in the data processing cycle, where data, and metadata (information about data) are held for future use
Storage
is term used to explain the sequence of steps or process used to process the raw data and turn it into readable form and generate meaningful information
Data Processing Cycle
This continuous use and processing of data follow a
cycle
is simply the conversion of raw data to meaningful information through a process
Data processing
suggests a sequence of steps or operations for processing
data i.e., processing raw data to the usable and readable form
Data processing cycle
This stage provides both the baseline from which to measure, and a target on what to improve.
Data Collection
identification of datasets and data items is done at this stage
Data Collection
includes sorting and filtering of data which will finally be used as input
Preparation
This stage required you to remove the extra or unusable data to make processing faster and better
Preparation
This is a broad step in reducing the quantity of data to yield in a better result
Preparation
Preparation is sometime referred as
data cleaning
is about constructing a data set from one or more data sources to be used for further exploration and processing
Preparation
If the inputs is not given properly or entered wrong, then the result will be adversely affected. This is because software follows the rule of
“Garbage in – garbage out”
It is when the data is subjected to various means and methods of powerful technical manipulations using Machine Learning and Artificial Intelligence algorithms to generate an output or interpretation about the data
Processing