Good morning fellow data cruncher!

The Query here 👋

Here’s what we have for you today:

• The Most Important Spreadsheets function 📊

• Data Exploration in SQL 👨‍💻

• Data analyst Freelance gigs 💼

• Memes! 🤣

Looking to become a Data Analyst? START HERE.

def content_spotlight(🔦):

If I could only have one spreadsheets function for the rest of my life there’s no doubt what I would choose.

In my daily work as an analyst, I find more value out of the SUMIFS function (followed closely by COUNTIFS) than any other function.

In this week’s video, I break down how to use SUMIFS and COUNTIFS.

We start with simple examples, then I teach you a couple nuances that can trip you up if you don’t know about them.

Hope you enjoy!

select * from data-jobs

remote, data jobs

We cultivate the best data jobs from around the internet to make your job search a little easier.

Check out this week’s featured jobs.

1. Jr. Data Analyst @ TechOp Solutions Intl.

2. LMS Product Analyst @ Riverside Insights

3. Data Analyst (Grocery) @ Congo Brands

freelance gigs

Need work experience? Get real experience with real projects.

1. BigQuery SQL with GA4 — apply here

2. Looker Studio Help — apply here

3. Data Analyst w/ GA4 experience — apply here

class SQLMiniLesson:

The MOST Common Pattern for Exploring Data in SQL

Kyle here 👋 — As a data analyst, exploring and understanding your dataset is crucial before diving into more complex analysis.

One common pattern for exploring data is to find the most frequent values for a specific column, ranked from top to bottom.

Here's a SQL tip for finding the most common values for a column in your dataset.

Let's consider an example where we have a table named orders with the following data:

In this example, the query returns the product categories and their respective frequencies, ordered by frequency in descending order.

This helps us quickly identify the most common product categories in our dataset.

One other tip is you can try to GROUP BY 1 ORDER BY 2, instead of typing the column names explicitly. Not every SQL environment supports this but it can make your query cleaner and faster to write.

As a data analyst, using this pattern for exploring your data will enable you to better understand your dataset and make more informed decisions during your analysis.

It's a simple yet effective way to quickly gain insights into the distribution of values within your data.

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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