The Query (aka Kyle and Cody) here 👋

Here’s what we have for you today:

• A tip for writing faster SELECT statements 💻

• Help preparing for SQL interviews ⌨️

• Freshly posted data jobs for you 💼

• A meme that will be my future 🤣

Looking to become a Data Analyst? START HERE.

new data analyst job board 💼

What did you think about last week’s announcement?

Have you checked out our brand new data analyst job board yet?

We felt the job search process for data analysts was not good enough.

So we created a job board tailored specifically for data analyst roles.

Check it out and please let us know if you have any feedback here.

We greatly appreciate any thoughts you have to make this the best job board possible for our data community!

select * from data-jobs

remote, data jobs

Because who likes writing SQL from a busy office?

Check out this week’s 3 featured jobs here.

1. Data Analyst Intern @ Autodesk — $72-118k per year

2. Business Analyst @ Silo — $130-160k per year

3. Senior Data Analyst @ Rocket Money — $125-150k per year

freelance gigs

Need work experience? Get real experience with real projects.

1. Analyze sales trends — $15 per hour (apply here)

2. Spreadsheets Data Analyst — $25-60 per hour (apply here)

3. Marketing Data Analyst — $100 fixed price (apply here)

def content_spotlight(🔦):

SQL interviews can be nerve racking, especially for newer analysts.

But it’s helpful to know what they might ask in advance.

I found this Reddit thread to be a solid resource for preparing you for what to expect in a SQL interview.

There are a lot of comments from different peoples’ experiencing conducting SQL interviews for data roles.

If you’re currently interviewing or thinking of apply to new roles this year, I think you’ll find it useful!

class MiniLesson:

Write Faster SELECT Statements with EXCEPT

Kyle here 👋 — Ever find yourself typing out way too many column names in your SELECT statement?

SELECT statements can be brutal.

Save yourself from carpel tunnel and try SELECT EXCEPT.

SELECT EXCEPT is a useful feature in many SQL dialects that lets you select all columns in a table except for the ones you choose.

This can be super helpful when working with large datasets containing many columns.

Here's a brief example of how to use SELECT EXCEPT.

Consider a table called bike_sharing_rides with the following columns:

trip_id, subscriber_type, bikeid, start_time, start_station_id, start_station_name, end_station_id, end_station_name, duration_minutes + 20 more…

That's a lot of columns.

What if you don't need them all?

Instead of typing out all the columns except for the ones you don’t need you can use SELECT EXCEPT.

For example, if you want to query all columns except start_station_name and end_station_name, you can use SELECT EXCEPT as follows:

This will return a result with all columns except for the specified ones.

Next time your table has more columns than you’d care to type…

Breathe a sigh of relief and remember SELECT EXCEPT.

import memes as 😂 

content & resources 🤓 

1. Become a Data Analyst Guide: Our full guide on what it takes to land a job as a data analyst.

2. Open Data Analyst Jobs: Find your next data job here!

3. Download our SQL Cheatsheet as a PDF and desktop wallpaper here. 

4. LinkedIn: We create content on LinkedIn daily. You can follow Cody here and Kyle here.

That’s it for today.

Stay crunchin’ folks and see you next week!

— Kyle & Cody

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