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October

<p>The Spotify charts show you what millions of people are listening to on a daily basis, but not everyone listens to the same music. Some songs conquer the entire planet at once while others become local legends, dominating one country's charts. Your task is to build a KNIME workflow that uncovers both kinds of stories: the streaming champion. Find the single most-streamed song in every region for each year covered by the data, and then see how these champions compare to one another.</p><p>Your workflow should answer:</p><ul><li><p><strong>Which song was the streaming champion in each region and each year?</strong> Implement a <strong>loop </strong>to process each region and year automatically.</p></li><li><p><strong>Which regional champions had the highest total stream counts overall, and where (and when) did they top the charts?</strong> Rank the champions against each other, not just by song name, but the region and the year they won are just as important.</p></li><li><p><strong>How does the world's taste compare to a single country's taste?</strong> Are the global chart-toppers the same songs that also win locally, or does each region march to its own beat?</p></li><li><p><strong>Is there a song that topped the charts in more than one region or in more than one year?</strong> A true hit that was successful in multiple regions tells a different story than a song that dominates just once.</p></li></ul>
Load the Spotify Dataset

Reads the raw Spotify charts CSV file into KNIME as a table, creating the starting dataset for all later steps. At this point, the data is simply being brought in so it can be cleaned, grouped by region and year, and analyzed for top-streamed songs.

Prepare Regional Yearly Winners

This step turns the raw Spotify chart records into a much smaller analysis table that identifies the top-streamed song for each region and year. In other words, it cleans and reshapes the daily chart data so you can compare the yearly champions across markets instead of working with millions of individual rows.

Visualize the Regional Winners

This component takes the prepared table of yearly top songs by region and turns it into an interactive visual summary. Instead of inspecting rows manually, you can quickly compare which songs became champions across different regions and years, making patterns and standout winners easier to spot.

Data Prep
DatasetSportify
CSV Reader
Data Viz

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