Get the join cheat sheet!

Download and print this nifty little PDF with all of the INNER, LEFT, RIGHT, FULL and CROSS JOINs visualized! It’ll look great on your office wall or cubicle. Your coworkers and your interior decorator will love you for it.

How it works: For each join example, there are two tables, the left and the right table, shown as two columns. For the sake of simplicity, these tables are called “a” and “b” respectively in the code.

You’ll notice that the sheet uses a kind of pseudo-code when it comes to table names and column names.

An alternative to data masking

Dynamic data masking is a neat new feature in recent SQL Server versions that allows you to protect sensitive information from non-privileged users by masking it. But using a brute-force guessing attack, even a non-privileged user can guess the contents of a masked column. And if you’re on SQL Server 2014 or earlier, you won’t have the option of using data masking at all.

Read on to see how you can bypass dynamic data masking, and for an alternative approach that uses SQL Server column-level security instead.

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Encrypting SQL Server connections with Let’s Encrypt certificates

Encrypting your SQL Server’s TDS connections should be high on your list of things to do if you’re concerned with the privacy of your data. This often boils down to one big problem: can you get a valid certificate without paying a ton of money, and will it work with SQL Server?

So follow me down the rabbit hole, as we work out the steps to using Let’s Encrypt to create (and auto-renew!) a certificate for SQL Server. This is going to get technical.

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Prioritizing rows in a union

I just remembered a pretty common data challenge the other day. Suppose you have a number of tables, all with similar information in them. You want to union their contents, but you need to prioritize them, so you want to choose all the rows from table A, then rows from table B that are not included in A, then rows from C that are not included in A or B, and so on.

This is a pretty common use case in data cleansing or data warehousing applications. There are a few different ways to go about this, some more obvious than others.

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