We have learned how to write queries to analyze data and perform simple calculations. In this section, we will take this a step further. We will use SQL functions to create custom reports based on our data and will learn how to analyze trends in our data.
Use CASE statements to structure data and create new attributes.
Combine multiple subqueries into one using “AS.”
Temporary Tables and Subqueries.
Determining data trends through advanced reporting.
In this tutorial, we will learn how to use different mathematical functions in order to interpret data better, and how to create reports.
Clean data using SQL mathematical functions (ABS, SIGN, MOD, etc.).
Learn how to write comments in SQL
Creating reports by applying aggregation methods.
We're going to let you in on a secret. SQL can perform most mathematical functions for you independent of the schema. Often when writing queries you may need to do some quick calculations. You can save time by performing the calculations in SQL itself.
SQL or Structured Query Language is a robust programming tool to run queries on large datasets. A query is just another word for code used to interact with the database. SQL is a highly sought after skillset across industries and work profiles because it can be implemented relatively easily and you don’t need a programming background to learn it. Most finance and marketing professionals with little or no programming experience are required to have an in-depth knowledge of it.
Should I use SQL? or Microsoft Excel/VBA?
For large datasets, SQL is preferred since it processes data faster than excel or VBA. VBA is confined by Excel’s processing ability while SQL is confined by the database’s processing ability.
Databases, like a Microsoft Access database, are created to store large quantities of data — they process data faster and ...
In the previous article we learned how to write simple SQL queries. Now, we will expand our skillset to learn how to aggregate data using aggregation commands.
Write Boolean statements with the IN SQL conditional operator and null functions (IS NULL, IFNULL, IS NOT NULL, and <>).
Summarize data sets by employing aggregation functions (Sum, Average, Count, etc.).
Let's say that you have recently started working for a restaurant supply wholesaler. You are tasked with leveraging the sales inquiry table to manage client communication more efficiently. Additionally, you have to co-ordinate with the sales people to ensure all queries are answered. Let’s look at some examples.