Summary
In this chapter, we started by introducing Trifacta Wrangler as a means to profile and manipulate your raw big data into a format that can be easily consumed and visualized. In addition, we explored the concept of using a secondary data source to provide context to a primary data source.
Next, we presented Tableau as a tool to consume prepared data and create valuable visualizations as individual components of interactive dashboards.
In the next chapter, we will cover outliers and provide working example solutions to deal with outliers and other data anomalies using Python.
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