Things to Consider Before Data Extraction
If you are going to perform data extraction, you will need to prepare. As a result, you will have to make certain considerations before starting the data extraction process. You do this because you want the entire process to go as planned. Additionally, you will not want to extract every single data point. Therefore, at the end of the process, you will only want to extract a handful of data. Below are some of the basic considerations you are to make before starting data extraction.
Define the Reason for Data Extraction
Before starting a data extraction, it is always advisable you clearly define the purpose of the extraction. Doing this helps you make better decisions when assigning tasks and resources. Effectively defining the reason for extracting data involves the following.
- Specify what the data will do. The purpose of the data can be to measure performance, answer questions, or help in decision making
- Itemize data points to be collected.
- Ensure each data point is useful to the main purpose. Finally, you will need to create a statement that defines the entire data collection procedure.
Outline the Data Extraction Scope
The reason for data collection determines the scope of the process. Therefore, all the characteristics of the data points to be collected must be defined. Such characteristics may include age, class, and much more. Next, you will need to outline where each type of data will be extracted from. For example, you will need to specify the division, location, or space. The scope of your data extraction process determines your population.
Define the Sample
Defining a sample involves specifying reliability. This part determines the sensitivity of your extraction process. Next, you will need to select the tool for analysis. This tool will determine how your data appears. Examples of tools for analysis include percentages and averages. These classifications help define the outcome of data extraction. However, you will need to set limits for each tool for it to make sense. You can also include other constraints to create a balanced outcome.
Select the Desired Instrument for Data Extraction
This step refers to how your data will be collected. Data collection instruments can include interviews, documents research, automated data scraping, and much more. Whatever instrument you decide to use, you must define it in its entirety. You should also test it before including it in the data extraction process.
Develop a Flow Diagram of the Process
You will want to create a flow diagram that contains all the steps involved in the data extraction. Doing this helps you and the members of your team. A functional flow diagram for data extraction should include all the information required for the process. It should highlight forward, feedback, and feedforward processes within an extraction cycle.
Run a Test
Before you begin data extraction, you will want to test run the scheme you have developed. During this process, you can either use fictitious data or real data. From the outcome of the extraction process, you can make changes to the scheme before deploying it for continuous use.
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