Backup Plans for Data Loss

Today Steve Jones discusses data loss, always a scary topic for the data professional.

How to Decipher sysschedules

Take the mystery out of sysschedules and interpret the data into a plain text format.

SQL Server Row Count for all Tables in a Database

Dattatrey Sindol explains the different ways in which you can get the row counts from all the tables in a SQL Server database.

Statistics in SQL: Simple Linear Regressions

Although linear regressions can get complicated, most jobs involving the plotting of a trendline are easy. Simple Linear Regression is handy for the SQL Programmer in making a prediction of a linear trend and giving a figure for the level probability for the prediction, and what is more, they are easy to do with the aggregation that is built into SQL.

Byte Me: Killer Conference

SQL Azure Reporting Automation

This article will talk about preparing a runbook in Azure to schedule the report of space usage of databases in Azure environment

Dealing with High Concurrency with Table Hints

Systems with a large number of requests on a critical database table are prone to blocking and slowness. We take a look at getting things done using T-SQL table hints.

Migrating Schema Between Platforms

The decision to change platforms isn't one Steve Jones takes lightly.

Properly Persisted Computed Columns

Paul White walks through a new trace flag in SQL Server 2016 designed to yield better execution plans (and performance) for queries involving computed columns.

Statistics in SQL: Kendall’s Tau rank correlation

Statistical calculations in SQL are often perfectly easy to do. SQL was designed to be a natural fit for calculating correlation, regression and variance on large quantities of data. It just isn't always immediately obvious how. In the second of a series of articles, Phil factor shows how calculating a non-parametric correlation via Kendall's Tau or Spearman's Rho can be stress-free.