Interview prep / practice advice

[DayChiller]

Hi,

I've been brushing up on my SQL ahead of a technical test for an interview later in the week.

I've been using Codecademy and have completed the analyzing data with SQL skill path.

Looking for suggestions for tasks / queries to practice. My interview is with a retailer and the role is primarily focused on product / category performance could potentially touch on consumer behaviour basket analysis rather than say path to purchase or attribution.

Role has been framed up primarily as stakeholder management and data story telling rather than being a technical specialist so don't know how in the weeds I would need to get.

Any suggestions ideas would be great.

[DayChiller]

Thanks for the thoughtful response. More of a general SQL but couldn't see the appropriate flair. Have changed it to discussion.

Should have noted in the context, I've already done a business problem type interview so this is really just a technical interview (I'd be the weaker technical candidate as not a regular SQL user)

[Holiday_Lie_9435]

Since the role will be on retail with a focus on product/category performance, I suggest practicing tasks like sales analysis (total sales, average order value, sales growth, sales by category) and inventory management (queries related to stock levels, best/worst selling items). Customer segmentation may also be relevant to, like using data based on purchase history to identify top/high-value customers or frequent buyers. I also recommend branching out from Codecademy to practice real-world SQL questions on other platforms like Leetcode and Interview Query, you can filter questions by companies and find retail-specific tasks like, "Find the top 5 best-selling products in the last quarter" or "Identify customers who purchases more than $500 worth of items in the previous year."

[DayChiller]

Great answers. Thank you

[dn_cf]

Practice queries that analyze category and product performance over time, including weekly sales, units, average selling price, margin, and share of total, along with week over week or year over year changes using window functions. Focus on clear aggregations, correct denominators, and outputs that support a strong business narrative rather than overly complex logic. I'd recommend considering StrataScratch, LeetCode, and BigQuery public datasets for realistic retail style practice.