{"id":1757,"date":"2022-01-18T09:08:33","date_gmt":"2022-01-18T08:08:33","guid":{"rendered":"https:\/\/sqlkover.com\/?p=1757"},"modified":"2022-01-18T09:09:26","modified_gmt":"2022-01-18T08:09:26","slug":"speaking-at-sqlbits-2022","status":"publish","type":"post","link":"https:\/\/sqlkover.com\/speaking-at-sqlbits-2022\/","title":{"rendered":"Speaking at SQLBits 2022"},"content":{"rendered":"\n

I\u2019m delighted to announce I\u2019ll be speaking at the SQLBits conference in March 2022! I\u2019m not delivering one session, but two this time. Well, actually, for one session I\u2019m co-presenting with Mala Mahadevan<\/a>. I\u2019m really looking forward to this session, as it\u2019s a not-well known topic (I hadn\u2019t heard about it till Mala told me everything about it): Finding and Fixing T-SQL Anti-Patterns with ScriptDOM.<\/strong> Yups, bet you haven\u2019t heard of it either \ud83d\ude42 ScriptDOM is included with SQL Server and it\u2019s a bunch of .NET classes (which you can also use in PowerShell of course) that allow you to parse T-SQL automatically and search for certain patterns in the T-SQL script. For example, you can use it to find out if those sneaky developers have been using SELECT * or NOLOCK. The abstract:<\/p>\n\n\n\n

Quality code is free of things we call \u2018anti-patterns\u2019 \u2013 nolock hints, using SELECT *, queries without table aliases and so on.
We may also need to enforce certains standards: naming conventions, ending statements with semicolons, indenting code the right way etc. Furthermore, we may need to apply specific configurations on database objects, such as to create tables on certain filegroups or use specific settings for indexes.<\/p>
All of this may be easy with a small database and a small volume of code to handle, but what happens when we need to deal with a large volume of code? What if we inherit something full of these anti-patterns, and we just don\u2019t have time to go through all of it manually and fix it? But suppose we had an automated utility that could do this for us? Even better, if we could integrate it in our Azure Devops pipelines?<\/p>
ScriptDOM is a lesser-known free tool from SQL Server DacFx which has the ability to help with finding programmatic and stylistic errors (a.k.a linting) in T-SQL code.It can even fix some of these errors!
In this session we will learn about what it is, how we can harness its power to read code and tell us what it finds, and actually fix some of those anti-patterns.
Join us for this highly interactive and demo-packed session for great insights on how to improve the quality of your code. Basic knowledge of T-SQL and Powershell is recommended to get the most out of this session.<\/p><\/blockquote>\n\n\n\n
The other session is my \u201cIntroduction to Snowflake on Azure\u201d. Both sessions are 50 minutes long and will be presented virtually. SQLBits itself is hybrid, meaning there will be on-premises sessions, but also a number of virtual sessions. You can find more info on the SQLBits website<\/a>. The theme at SQLBits this year is arcade gaming<\/strong>:<\/p>\n\n\n\n
$\"\"$ <\/a><\/figure>\n<\/body>","protected":false},"excerpt":{"rendered":"
I\u2019m delighted to announce I\u2019ll be speaking at the SQLBits conference in March 2022! I\u2019m not delivering one session, but two this time. Well, actually, for one session I\u2019m co-presenting with Mala Mahadevan. I\u2019m really looking forward to this session, as it\u2019s a not-well known topic (I hadn\u2019t heard about it till Mala told me […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[3],"tags":[187,33,16,196],"class_list":["post-1757","post","type-post","status-publish","format-standard","hentry","category-events","tag-snowflake","tag-speaking","tag-syndicated","tag-t-sql"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/posts\/1757","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/comments?post=1757"}],"version-history":[{"count":1,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/posts\/1757\/revisions"}],"predecessor-version":[{"id":1762,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/posts\/1757\/revisions\/1762"}],"wp:attachment":[{"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/media?parent=1757"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/categories?post=1757"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sqlkover.com\/wp-json\/wp\/v2\/tags?post=1757"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}