Data wrangling is the unglamorous work that makes raw data consistently machine-readable before analysis. Think of it as getting a chaotic spreadsheet—or a 90-minute recording—into a form that tools can actually interrogate without shrugging. section 8.1
A practical workflow can begin by turning audio into a transcript, exporting it as a PDF, and uploading that file to a query tool for topic-specific summaries. The same general problem appears with large business datasets: parse the data, make its structure consistent, then apply analysis to find useful insights. section 8.1
Figure 8.1 Using data analytics to derive insights from raw data
Use this overview to place wrangling before the analysis step that derives insights from raw data. section 8.1
Querying prepared customer data
After data is loaded and indexed, a focused query can ask which five regions have the highest average household net wealth, returning only region codes. Another query can identify ten likely product investors from age, location, branch visits, and current investments, returning customer IDs only. section 8.1
