The Query (aka Kyle and Cody) here 👋

Here’s what we have for you today:

• My favorite SQL function for data cleaning 📊

• A fundamental data concept to learn 👨‍💻

• More open Data analyst jobs 💼

• Memes galore! 🤣

Looking to become a Data Analyst? START HERE.

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remote, data jobs

Open to exploring new job opportunities?

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

Check out this week’s featured jobs here.

1. Data Analyst @ Veeva Systems — $45-90k per year

2. Data Analyst @ Genworth — $65-103k per year

3. Senior Data Analyst @ HopSkipDrive — $100-149k per year

freelance gigs

Need work experience? Get real experience with real projects.

1. Product Analytics Help — $45-180 per hour (apply here)

2. Data Analytic Freelancer — $entry level (apply here)

3. Excel/SQL Help — $150 fixed price (apply here)

def content_spotlight(🔦):

Dimensional modeling is a fundamental concept for data warehouses and data analysis. It’s usually thought of as an intermediate/advanced level topic but I believe it’s well worth the time to learn.

If you’re feeling ambitious check out the Kimball Group website here to learn more about it.

Understanding dimensional modeling will help you out a ton as a data analyst!

Even if you are not designing the databases yourself, you will be much more confident understanding what you are looking at and why the data is in the format it’s in.

class SQLMiniLesson:

The Most Used Data Cleaning Function

Kyle here 👋 — I reviewed all the SQL code I’ve written recently.

Interestingly, the data cleaning function I use most often is LOWER.

The LOWER() function in SQL is a string manipulation function that converts text to lowercase.

It is useful when you need to normalize text data, such as email addresses, to ensure consistent formatting and avoid issues with case sensitivity in your queries.

Email addresses are often entered by users in a free-form manner, leading to inconsistent capitalization.

Some SQL environments are case-sensitive, which means that '[email protected]' and '[email protected]' would be treated as different email addresses, even though they represent the same person.

By using the LOWER() function, you can standardize email addresses to lowercase, ensuring that your queries and joins work correctly regardless of the original capitalization.

Usage is straightforward. Here is an example…

Let's consider an example where we have a table named users with email addresses in various capitalizations.

We want to convert all email addresses to lowercase.

We can use the LOWER() function in a query to achieve this.

Simple, but powerful.

As a data analyst, understanding how to use the LOWER() function in SQL is essential as it allows you to standardize and clean text data within your queries.

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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. 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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