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The document US 2004/0254924 A1 describes an innovative system and method for accessing data through a logical framework that abstracts the physical representation of data. It introduces a data repository abstraction layer and a query abstraction layer, allowing users to perform iterative data analysis by augmenting queries with additional result fields. This approach enhances flexibility in querying diverse data sources, facilitating knowledge discovery and correlation of results across different datasets.
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They are: Plan. The iterative process often begins with a planning and requirement research phase. Design. In the second phase of this model, consider focusing on your design and analysis. Implement. The third phase is implementation. Test. For the testing phase, gather feedback on your offerings. Review.
Organizing and Preparing the Data. Reading Through All the Data. Coding the Data. Identifying Themes (Grouping the Codes Into Themes) Developing a Story Line Interpretation (Interconnecting the Themes) Adding an Analytic Framework. Representing/Interpreting the Data. 7 thoughts on The 7 Steps of Qualitative Data Analysis
An iterative means one has to repeatedly revisiting the data or going back and forth repeatedly on the data. This whole process involves moving back and forth between concrete bits of data and abstract concepts, between inductive and deductive reasoning, between description and interpretation (Merriam, 1998, p.
Iterative Thematic Inquiry builds on the researchers dual role of both developing themes as patterns in the data and communicating those patterns to an audience.
Phronetic iterative qualitative data analysis is a qualitative method that tags between grounded analysis of qualitative data (such as interviews, participant observation field notes, documents, and visuals) on the one hand, and existing literature and theory on the other.

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People also ask

Receiving an education is a common example of an iterative process. With each class that a student takes, they complete another iterative process. Students apply trial and error during their time studying since it allows them to discover which techniques work for them when trying to absorb knowledge.
Teams that use the iterative development process create, test, and revise until theyre satisfied with the end result.
An iterative means one has to repeatedly revisiting the data or going back and forth repeatedly on the data. This whole process involves moving back and forth between concrete bits of data and abstract concepts, between inductive and deductive reasoning, between description and interpretation (Merriam, 1998, p. 178).

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Interactive Data Analysis: The Control Project

by M Joseph Cited by 280 We focus on systems that iteratively refine answers to queries and give users online control of processing, thereby tightening the data analysis process loop.

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Data Quality Analysis: Profiling and beyond

Also, iterative approaches happen often where the same procedure is repeated multiple times to deepen prior analyses or update them to recent context changes.

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Iterative categorization (IC): a systematic technique for

by J Neale 2016 Cited by 724 A simple but rigorous and transparent technique for analysing qualitative textual data, developed within the field of addiction, is described.

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