Good morning data cruncher!

The Query here 👋

Here’s what we have for you today:

• A fantastic resource for practice datasets 📊

• Tips for writing clean SQL code 👨‍💻

• Open Data job opportunities 💼

• Some memes I really resonate with 🤣

Looking to become a Data Analyst? START HERE.

select * from data-jobs

remote, data jobs

Want a new job?

We cultivate the best data analyst jobs from around the internet to make your search easier.

Check out this week’s featured jobs.

1. Senior Data Analyst @ Simpluris — $75-99k per year

2. Product Analyst @ Future Publishing — $85-93k per year

3. Data Analyst @ Capital Impact Partners — $103-138k per year

freelance gigs

Need work experience? Get real experience with real projects.

1. PowerBI Help — $1,000 fixed (apply here)

2. Inventory Data Analyst — $8-12 per hour (apply here)

3. Looker Studio Dashboard — $38-72 per hour (apply here)

def content_spotlight(🔦):

What are the SQL best practices for writing clean code?

When I was learning SQL, I’d come back to a query I had written a month prior and it’d be really difficult to remember what the query does.

Writing clean code fixes this problem.

Here are a few things to keep in mind when it comes to clean SQL:

• Style

• Readability

• Maintenance

• Indentation

• Comments

In this article, Martin Ganchev goes over each of these in depth.

Highly recommend!

dataset_of_the_week(🔢):

In this week's newsletter, we're taking a different approach.

Introducing… the Datasets Subreddit.

Instead of supplying a dataset, we're focusing on equipping you with the skills to find your own data!

The datasets subreddit has tons of datasets posted every week that you can download and play around with.

If you’re learning data analysis, I would make a habit to check this site once in a while and save any datasets you think might be interesting.

Keep a folder of datasets on your computer that you can come to for inspiration on a new project.

Enjoy!

class SQLMiniLesson:

A Function for Precision in SQL

Kyle here 👋 — A common mistake Data Analysts make (and one I’ve made myself) is including too many decimal places.

Most stakeholders don’t need numbers out to 4 decimal places.

And the number of decimals should be consistent for the same metric.

SQL provides a versatile function called ROUND that helps you with this.

The ROUND function takes two arguments:

1. The number you want to round

2. The number of decimal places to round to.

If you pass a positive value as the second argument, it rounds to that many decimal places.

A negative value will round to the left of the decimal point and passing zero will round the number to the nearest integer.

Here’s an example where we have a table named product_prices and we want to round the prices multiple ways:

In this example, the query uses the ROUND function to round the prices to 2 decimal places, the nearest integer, and the nearest multiple of 10.

As a result, we can see the rounded prices for each product in our dataset.

Happy rounding 🟠 

import memes as 😂 

content & resources 🤓 

1. YouTube Channel: Click here for videos on SQL and data analytics.

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

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

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

5. LinkedIn: I regularly post data content on LinkedIn.

That’s it for today.

Stay crunchin’ folks and see you next week!

— Kyle

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