The Query (aka Kyle and Cody) here 👋

Here’s what we have for you today:

• How to develop analytical thinking skills 🤔

• A SQL lesson on appending two datasets 💻

• Open Data jobs galore 💼

• Another good ole meme 🤣

Looking to become a Data Analyst? START HERE.

select * from data-jobs

remote, data jobs

Because who likes writing SQL from a busy office?

Check out this week’s featured jobs.

1. Data Analyst @ Evio — $80-110k per year

2. Senior Data Analyst @ Brightwheel — $104-138k per year

3. Senior Data Analyst @ Peerspace — $140-150k per year

The feedback and ideas so far coming from you all about the job board has been fantastic! Keep it coming here.

freelance gigs

Need work experience? Get real experience with real projects.

1. Marketing Data Analyst — $entry level (apply here)

2. Tableau/CRM Analytics— $30-40 per hour (apply here)

3. SQL Query help — $10 fixed price (apply here)

def content_spotlight(🔦):

Being a data analyst is not just about knowing technical tools like SQL and Tableau.

The biggest trait that sets apart high performing analysts their analytical thinking skills.

How do you develop analytical thinking? That is a tricky question to answer, but I think this article from Field Engineer will help.

It discusses topics like:

• What are analytical skills?

• How do I improve myself analytically?

• How do I highlight my analytical skills on my resume and in interviews?

Check it out!

class SQLMiniLesson:

Appending Together Two Datasets

Kyle here 👋 — When working with data one common task is appending one table of data to another.

Appending data is kind of like adding more pages to the end of a book or adding more items to the end of a shopping list.

The original data stays the same, but new data is added to the end.

For example, if you have a list of names like this:

Alice, Bob, Charlie

And you append the name "Dave" to the list, the list would then look like this:

Alice, Bob, Charlie, Dave

To append data in SQL we use the UNION command. But there are two ways to do a UNION:

1. UNION

2. UNION ALL

An example would look something like this:

While they both serve the purpose of merging query results, there are differences in their behavior and use cases.

UNION: The UNION operation combines the results of two or more SELECT queries and removes any duplicate rows.

Use UNION when you want to merge results from different queries and ensure that the output contains only unique rows, without duplicates.

UNION ALL: The UNION ALL operation combines the results of two or more SELECT queries and retains all rows, including duplicates.

Since UNION ALL does not perform any duplicate elimination, it is generally faster than UNION.

Use UNION ALL when you want to merge results from different queries and keep all the rows, including duplicates, or when you know that there are no duplicates in the result sets and want to improve the query performance.

Now you’ll always know which one to use. Append away!

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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