I still require help. The previously answers providing the breakdowns were unclear to me.

My SQL Workbench

Project Part 2- AD HOC REPORTS

Request #2: Leveling Off Of Member Growth

The next request in your inbox is from a member of the LetsMeet Growth team. They are part of the Sales team that is responsible for growing the membership of LetsMeet year-over-year.

Hey there,

I'm working on a report on membership growth to date for Cat and after scanning the latest numbers noticed that it appears membership growth might be leveling off.

I'm wondering if you can dig into the year-over-year membership growth for the whole organization. I'm worried there might be some errors in our data collection.

Engineering has already informed me of at least one error regarding the city information in our grp_member table. It looks like you might need to amalgamate some smaller suburbs into into their wider geographic area (i.e. East Chicago and West Chicago should just be Chicago). I'll send you an attachment with our required breakdown.

Please include any insights into why membership doesn't seem to be growing like it used to.

Let me know if you can get to this by end of day.

Cheers,

Sammy

In their follow up e-mail Sammy included a helpful reminder that the joined column in the grp_member table represents the date a member joined a specific group, not the date they joined LetsMeet. They suggest instead that you use the date a member joined their first group as a proxy for when they joined the site.

To get started, follow these steps:

1.Navigate to the SQL file named 3_growth.sql.

2. Write a query that shows the growth of LetsMeet over the years based on the number of members who joined each year.

HINT

Consider using a subquery to find the YEAR(MIN(joined)) and grouping them by member_id.

3. In the grp_member table, use the appropriate DML to rename the smaller cities to the name of their larger urban areas. Based on the attachment from Sammy, they should be combined as follows:

Chicago - East Chicago, West Chicago, North Chicago, Chicago Heights, Chicago Ridge, Chicago

San Francisco - San Francisco, South San Francisco

New York - New York, West New York

HINT

Don't forget to SET SQL_SAFE_UPDATES = 0;

Use UPDATE, SET, WHERE. These changes should be permanent.

4. Time to see if there are any differences in year over year growth by city! Write three new queries that show the annual growth of LetsMeet for the larger geographical areas of Chicago, San Francisco, and New York.

HINT

You can reuse your query from Step 2 here by adding a WHERE clause.

5. You decide you want to dig deeper into membership growth specifically in 2017, the year when growth in membership seems to slow the most. Write a query to examine the month by month growth for LetsMeet in 2017. What do you notice about the resulting table?

HINT

This query will be similar to your previous queries. Instead of looking at YEAR a member joined, you will need to look at MONTH. You will also need to use a WHERE clause to filter your results to the YEAR 2017.

Consider how you need to group these results if you are examining month by month instead of year by year.

6. Return to 1_summary_report.sql and summarize your findings for the Growth Team in a few bullet points. This should include your overall findings on year-over-year growth and insights into why membership growth appears to be leveling off, including any potential data anomalies.

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