coding and levels of codig

• Data cleaning is meant to transform your data into manageable formats. 
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  Data Cleaning

  Raw data is managed by converting audio or video files into transcripts, and images into photos or charts.
• Data Cleaning:This step is focused on identifying which data is relevant and usable.
• Data exploration is divided into four (4) repetitive steps:

  Chunking, clustering, coding, and memoing. Proper data exploration should have at least two (2) or three (3) cycles.
• data exploration is to categorize and refine your data to identify themes and trends to be used in making discussions/conclusions.
• Chunking is the act of breaking down your cleaned data and determining which parts are for what purpose (e.g., is this about participant information, background, examples provided, etc.).
• Clustering is the act of taking these chunks and classifying them according to labels or basic codes
• Coding is focused on creating labels and categories that represent the data accurately.
• Descriptive to Interpretative to Pattern:move from summary to meaning.
• Open to Axial to Selective - moves from initial theory to developing relationships between codes for the emerging theory
• First to the second cycle: moves from describing the data units to inferring meaning
• Memoing is the act of taking these codes and clusters and then adding notes that help explain or define them.