Multivariate analysis in data science is a type of analysis that tackles multiple input/predictor and output/predicted variables. This tip explores the problem of predicting air pollution measured in particulate matter (PM) concentration based on ambient temperature, humidity, and pressure using a Bayesian Model.
2025-09-19
Synchronous replicas in SQL Server Availability Groups promise no data loss, but they don’t promise zero delay; under heavy load they can still fall behind. This article shows how to measure and track that hidden replication delay using SQL Server performance counters, so you can see how well your system keeps up during IO‑intensive operations and plan maintenance more safely.
2025-09-17
How can we setup alerts in Azure SQL MI to notify us when there are issues?
2025-09-15
This article dives into a fun (and interesting!) strategy for widening fixed-width columns in SQL Server, to reduce downtime, risk, and runtime at the time when a column’s data type needs to be changed.
2025-09-12
I recently resolved an issue where a query pulling data from the last 30 days would time out due to the table’s size and the lack of a supporting index. Creating a supporting index is possible, but not ideal; it will be very large and may not be useful for most queries and use cases. I wonder how I could implement a filtered index that follows time and is always limited to the last n days.
2025-09-10
Introduced in SQL Server 2025 CTP 1.3, the PRODUCT() function acts similarly to SUM(), but multiplies values rather than adds them. It is an aggregate function in SQL Server and therefore operates on a data set, rather than on scalar values.
2025-09-08
The advantage of using triggers is that the same processing can occur regardless of where or how the data has been inserted, updated or deleted. In this article, we look at several examples of where and why triggers could be useful along with an example use case.
2025-09-05
In this article, we’ll revisit the dimension models we created. We wrote the entire SQL statement for the dimension by hand, and the dimensions themselves were very rudimentary; they lacked a surrogate key and there were no audit columns (such as insert date and update date). We’ll show you how we can expand the dimensions using Jinja, but also how we can minimize development effort by baking reusable patterns into the Jinja code.
2025-09-03
Helping people solve T-SQL problems is one of my favorite hobbies. Someone messaged me the other day with a complex query that was almost complete except for one issue. He needed to perform a LEFT OUTER JOIN but had to filter based on a value from the right table. However, when he added the filter, SQL removed rows from the left table. The task was to decide where to place the SQL predicate: in the ON or WHERE clause.
2025-09-01
In this newly updated and expanded edition of the bestselling The Phoenix Project, co-author Gene Kim includes a new afterword and a deeper delve into the Three Ways as described in The DevOps Handbook.
2025-08-29 (first published: 2024-02-20)
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I try to run this code on SQL Server 2022. All the objects exist in the database.
CREATE OR ALTER VIEW OrderShipping
AS
SELECT cl.CityNameID,
cl.CityName,
o.OrderID,
o.Customer,
o.OrderDate,
o.CustomerID,
o.cityId
FROM dbo.CityList AS cl
INNER JOIN dbo.[Order] AS o ON o.cityId = cl.CityNameID
GO
CREATE OR ALTER FUNCTION GetShipCityForOrder
(
@OrderID INT
)
RETURNS VARCHAR(50)
WITH SCHEMABINDING
AS
BEGIN
DECLARE @city VARCHAR(50);
SELECT @city = os.CityName
FROM dbo.OrderShipping AS os
WHERE os.OrderID = @OrderID;
RETURN @city;
END;
go
What is the result? See possible answers