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Hey crunchers! The Query here — the data analyst newsletter that's like a primary key for your data career. We help ensure a good relationship.

Here’s what we have for you today:

• Financial Forecasting 101 🤑 

• SUMIFS in… SQL?!?

• The difference between WHERE and HAVING in SQL

• Memememememememe 🤣 

def learn_data_analysis(👨‍💻):

1. Financial Forecasting 101

If you’re looking to land a Data Analyst role in Finance or already work as a Data Analyst in Finance, check out this article in Data Analysis Journal.

It dives into topics you should familiarize yourself with when it comes to financial forecasting like:

• Using historical growth rates

• Moving averages

• Simple linear regressions

• Multiple linear regressions

2. Understanding WHERE versus HAVING in SQL

Both the SQL WHERE clause and HAVING clause filter out rows.

It’s important to understand the differences and when to use each.

This article on SQL Bits is short, sweet, and will teach you what you need to know in 5 minutes or less.

select * from dataset-of-the-week

My first Data Analyst role was in the automotive industry, so in spirit of that, this week’s dataset of the week is a Used Car dataset by Sanjeet Singh Naik.

If you decide to analyze this dataset, I’d look to:

• Understand the relationship between price and mileage.

• Understand what the highest supply vehicle types are.

• Understand the relationship between price and age for certain make, models.

There’s a lot more you can do with this dataset, but that should get you started.

class MiniLesson:

How to Do SUMIFS in SQL

SUMIFS is my favorite Excel function.

But what if you want to do something similar in SQL?

In SQL, the combination of the CASE statement within the SUM function can be used to achieve functionality similar to SUMIFS in Excel.

The first time I saw that you could put a CASE statement inside a SUM, it blew my mind. 🤯

The CASE statement allows you to apply conditional logic within the aggregation function.

This lets you sum the values based on specific criteria.

Suppose we have a table named sales with the following data:

We want to calculate the total quantity sold for product_id 1, but only for completed sales. In this case, we can use a CASE statement within the SUM function to apply the necessary conditions:

In this example, the CASE statement checks if the product_id is 1 and if the sale_status is 'Completed'.

If both conditions are met, it returns the quantity value; otherwise, it returns 0.

The SUM function then adds up the returned values, giving us the total quantity sold for product_id 1 with completed sales.

Using a CASE statement within a SUM function allows you to perform conditional aggregations similar to SUMIFS in Excel.

Hope you put this to good use!

import memes as 😂 

There is nothing IFERROR can’t fix! #exceljokes 🤣

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If you have any questions you’d like answered in the guide, reply to this email and we’ll make sure to include an in-depth and comprehensive answer in the guide.

That’s it for today.

Stay crunchin’ folks and see you next week!

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