Byte Me: Paranormal Presence

Machine Learning for Outlier Detection in R

A look into clustering to detect outliers in R. An extension on univariate statistical tests to include multivariate data.

The Basics of Good T-SQL Coding Style

TSQL Code must work properly and efficiently. That's not enough though. Unless you are working alone, have perfect memory and plan to never change job, then you need to comment and document your code, it must be inherently readable, well laid out, use informative and obvious names, and it must be robust and resilient; written defensively. It must not rely on deprecated features of SQL Server, or assume particular database settings. Robert Sheldon starts a series of articles that explains the basics.

SQL Server Memory

SQL Server Memory in Task Manager - Should I be Worried?

3 Solutions For Auditing Long SQL Server Extracts or Loads

In this post, Tim Smith looks at the different options you can use to audit your SQL Server extracts and loads during the ETL process.

A General Way to Maintain History Tables

You will see here a way to handle history tables. This way only takes into account Date-based data cleanup but is easily generalizable.

Export data from SQL Server to Excel

What native SQL Server options are available to export to Excel? Jeremy Kadlec explains.

Scoring Outliers in Non-Normal Data with R

Using R to detect outliers is relatively easy, but most methods assume your data is normally distributed. How do you handle skewed datasets?

Azure Automation Methods

Tim Radney of SQLskills walks through multiple automation methods you can use to manage and maintain your Azure SQL Databases.

Replace Bad Characters in Table

Learn how to clean bad characters from lots of data in this article.