The Query (aka Kyle and Cody) here 👋

Here’s what we have for you today:

• Cool sounding remote data jobs 😎

• Freelance work you can knock out in no time 💪

• 40 free datasets to build your portfolio 🧵

• A quick SQL tip to save you time ⏳

Looking to become a Data Analyst? START HERE.

select * from data-jobs

remote, data jobs

Because who likes writing SQL from a busy office?

1. Data Analyst @ Gannett — $60-94k per year (apply here)

2. Data Analyst @ iSpot.tv — $68-79k per year (apply here)

3. Data Analyst, Product @ AllTrails — $130-140k per year (apply here)

freelance gigs

Need work experience? Get real experience with real projects.

1. Convert CSV to PDF — $8-25 per hour (apply here)

2. Fix Google Sheet — $100 fixed price (apply here)

3. NBA & NHL Data — $30 fixed price (apply here)

def content_spotlight(🔦):

This week, we’re featuring a blog post from DataQuest showing over 40 Free Datasets for Building Your Portfolio.

Scroll through these and see if any of them seem interesting to you.

I personally think Identify Customers Likely to Churn dataset in the Business Analysis section sounds like a good one.

If you do an analysis of any of these make sure to share it on Linkedin and tag Cody and Kyle in your post!

class SQLMiniLesson:

A Quick SQL Tip to Save You Time

Kyle here 👋 — Here’s a quick SQL tip to save you time.

Sometimes you will have to work with tables that have A LOT of columns.

And let’s say you only want half of them.

You either have to manually type out each column you want in the SELECT statement. Or you can manually type out the columns you don’t want with a SELECT * EXCEPT statement.

Whenever I came across this scenario it used to take me forever.

But here’s a quick tip I learned to help prevent this…

You can write a SQL statement that outputs the column names for you!

Here's how to do this using BigQuery:

SELECT column_name
FROM project_id.dataset_id.INFORMATION_SCHEMA.COLUMNS
WHERE table_name = 'mytable'

Most Other Relational Databases (MySQL, Postgres, SQL Server):

SELECT column_name
FROM information_schema.columns
WHERE table_schema = 'schema name'
   AND table_name = 'table name'

These queries will output the column names in the SQL results.

Then you can copy/paste them all at once and just delete the ones you don’t want.

I find it’s much faster to do it this way.

I hope this comes in handy for you in your SQL journey.

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content & resources 🤓 

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

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

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

4. Courses: Our course on showcasing your data portfolio is live!

That’s it for today.

Stay crunchin’ folks and see you next week!

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