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Emma learned that LinkedIn wasn’t just for boasting—it was for teaching. And SPSS wasn’t just for academic tests—it was a practical tool for turning chaos into clarity, one bar chart at a time.
#SPSS #DataWrangling #DataVisualization #Analytics #EntryLevelAnalyst She added a carousel of her SPSS charts (exported via ), tagged her professor and college, and clicked post. The Unexpected Result Within 24 hours, her post got 5,000+ impressions. A senior data scientist from a tech company commented, “Love seeing SPSS get love for wrangling, not just stats. Small multiples for the win.” A recruiter messaged her about a senior analyst role.
Last week, I faced 10K rows of chaos: missing values, duplicate IDs, and inconsistent dates. Here’s my 3-step SPSS workflow for data wrangling + visualizing:
Emma had just landed her first data analyst role at a midsize retail company. She was excited—until her manager handed her a messy Excel file of customer feedback and said, “I need insights by Friday. Use whatever you want, but make it look professional. Oh, and post a summary on LinkedIn.”
Then came the trickier part: creating a new “Customer Sentiment” variable from open-ended text responses. She used to turn categories (“very unhappy” to “very happy”) into numbers 1–5. A quick Frequencies check showed the distribution looked plausible.
Whether you’re a student or a new analyst, combining data wrangling, thoughtful visualization, and a generous LinkedIn post can open doors you didn’t even know existed. And it all starts with a single, clean dataset.
