Introduction
Data analysis is choosing the right approach to answer a question with data. You already do this instinctively: when your monthly spending is high, you check the category breakdown, investigate why, project the trend, and decide what to change. At work, the same thinking applies but at a scale where choosing the wrong approach produces output that looks right but answers the wrong question.
At Tailwind Traders, an outdoor equipment retailer, the VP of Sales reviews the past year's numbers and notices that total sales didn't grow despite running campaigns across every channel. Each of her questions calls for a different analytical approach:
- What happened with sales across channels and products?
- Why do some products and channels outperform others?
- What comes next if the current revenue trend continues?
- What should we do about pricing to balance revenue and profit?
Checking your total spending without breaking it down by category doesn't tell you why costs increased. Just like delivering a sales trend report when the VP needs to understand what's driving results leaves her with data but no answers.
In this module, you learn the different types of analytics, the different roles in data teams, and a data analyst's workflow. By the end, you should understand how to apply the different analytic approaches in your organization.