What Does Data Extraction Mean?
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When you’re conducting research, the first critical step is to gather all of the necessary data relevant to your study. The process of obtaining research data is commonly referred to as data extraction. It’s also important when you’re performing systematic reviews because it explains to the reviewer how the evidence on the specific question or topic of the study was gathered.
In short, data extraction specifically refers to the stage when experimental data is imported into your system using available data extraction software for systematic reviews.
This article will help you further understand the nuances of data extraction as it relates to research and systematic reviews and the available tools to help you efficiently extract the right data from various sources.
Meaning of Data Extraction in Research
In research and systematic reviews, data extraction refers to the process of retrieving data from unstructured and unorganized sources for further analysis and processing before it is used as evidence. The importation of this data to a transitional extracting system normally precedes data transformation (which includes the addition of metadata) before it moves to the next stages in the information workflow.
If you are doing data extraction for your healthcare business, you may want to look into using any of the available data extraction tools in healthcare research. A data extraction tool for qualitative research can also help you gather insights and viewpoints to supplement the hard data in your study. Examine tools available to make sure that the one you choose supports quality-assurance in the form of dual reviewers and the collection of repeating data sets.
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Data Extraction for Research and Systematic Reviews
There are many data extraction tools available that can be used for qualitative and quantitative research as well as systematic reviews. However, not every available tool can help you accomplish your data extraction tasks easily, quickly, and effectively. When you need to choose your data extraction tool, do so carefully to ensure that you understand the pros and cons of each.
Make sure that the data extraction software you choose for this process is designed to support quality-assurance in the form of dual reviewers and the collection of repeating data sets for systematic reviews, quantitative research, and qualitative research. It should help you gather accurate and useful data that will produce an accurate evidence-based review in less time.
Ideally, the right program will help you manage your data extraction tasks, and other systematic review stages such as screening and evaluating the collected data using artificial intelligence and intelligent workflows to ensure accuracy and impartiality. Whether you’re extracting data for your qualitative research, quantitative research, or systematic review, this tool will make the project simpler to manage and organize for transparency, compliance, and audit-ready results.
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