The Bit Bucket

SQL: Don't Play Hide and Seek with T-SQL

SQL: Don't Play Hide and Seek with T-SQL

I spend most of my life in a variety of customer sites. Most of these nowadays tend to be large financial organizations. When I talk to developers in those organizations, and ask them about how they interact with their DBAs, I can’t tell you how often I hear that they try to avoid ever making schema changes, etc. as it takes too long and the process is painful.

When I talk to the DBAs at the same organizations, and I ask them why they resist making schema changes, I hear this:

2026-07-05

Fabric RTI 101: Building Alert-Driven Workflows

Fabric RTI 101: Building Alert-Driven Workflows

In recent posts, I’ve focused on dashboards and visualizations — but real-time intelligence goes beyond that. The real power comes when your system doesn’t just display insights but can act on them automatically.

Dashboards are great for monitoring, but most people can’t sit and watch a dashboard all day. Instead, we can use alerts and automation to make the data work for us.

Alert-Driven Workflows

There are a few ways to do this in Microsoft Fabric and the broader Power Platform: Power BI Alerts can be set up on tiles or visuals. They monitor thresholds — like sales dropping below a target — and notify users when conditions are met.

2026-07-04

Book Review: Agentic Coding with Claude Code

Book Review: Agentic Coding with Claude Code

I recently received a review copy of Agentic Coding with Claude Code by Eden Marco from my friends at PackT.

Author

Eden Marco is an LLM specialist at Google Cloud and a LangChain Ambassador with years of experience in software engineering and cloud architecture. Over many years, he has created practical courses based on his real-world experience.

Content

This is a timely and practical guide for developers who are ready to move beyond casual AI-assisted coding and start treating coding agents as serious development tools. Eden’s main argument is that effective agentic coding is not just about writing better prompts. It is about engineering context: deciding what the agent should know, what it should ignore, what tools it should use, and how its work should be structured so that results are repeatable, controlled, and maintainable.

2026-07-03

Fabric RTI 101: Streaming to Warehouses

Fabric RTI 101: Streaming to Warehouses

Warehouses in Microsoft Fabric are designed for structured, relational analytics — and they’re a perfect destination for streaming data that fits those patterns.

In many organizations, data warehouses have traditionally been refreshed through nightly or hourly batch loads. That meant Power BI dashboards and reports were always slightly behind — reflecting yesterday’s or last hour’s data.

Streaming to Warehouse

With Fabric Eventstreams, we can now stream data directly into Warehouse tables, especially into fact tables that support BI models. This means data becomes queryable within seconds of arrival, rather than waiting for the next batch window.

2026-07-02

PowerShell: Invoke-SqlCmd4 - A Superior SQL Commandlet

PowerShell: Invoke-SqlCmd4 - A Superior SQL Commandlet

Note: This is part of a series of posts where I’m improving some of my older blog posts.

Recently, I wrote about one of the issues with the Invoke-SqlCmd commandlet where it sets the ApplicationName when you use the parameter that should set the host.

Fellow MVP Ben Miller sent me a copy of the Invoke-SqlCmd3 that they were using. It was much better.

I then realized that there were many other options missing from these commandlets (such as options for Database Mirroring and Availablity Groups) and so I set about improving it.

2026-07-01

Fabric RTI 101: Streaming to Lakehouses

Fabric RTI 101: Streaming to Lakehouses

One of the most powerful features of Microsoft Fabric is the ability to stream data directly into a Lakehouse.

Streaming to Lakehouse

A Lakehouse is a unified storage system that brings together both structured and unstructured data. It can store raw files, like CSV or Parquet, as well as structured tables in Delta format. That means it’s equally comfortable handling real-time events and batch-loaded historical data.

When we connect Eventstreams to a Lakehouse, the incoming data is written directly into Delta tables. This format supports transactional consistency, so you can query the data immediately while new events continue to arrive.

2026-06-30

Fix: Out of Memory Errors in SSIS When Loading Older 32 bit DLLs

Fix: Out of Memory Errors in SSIS When Loading Older 32 bit DLLs

Day by day, we’re getting further away from needing to use 32-bit DLLs. One place where I keep coming across them, is when doing integration work. The problem is that there are many 32-bit drivers for older systems, and no-one is going to ever bother to write 64-bit drivers for them. So, if you have to use those drivers, you need to run the 32-bit versions. And SSIS has options that allow you to run 32-bit drivers.

2026-06-29

Fabric RTI 101: Creating Real-Time Dashboards

Fabric RTI 101: Creating Real-Time Dashboards

While Power BI remains a fantastic visualization tool for business reporting, and we’ll talk more about it later, Fabric Real-Time Intelligence also includes its own built-in real-time dashboards — designed specifically for operational monitoring and live analytics.

Real-Time Dashboards

These dashboards are native to the Real-Time Intelligence workspace. They connect directly to KQL Databases or Eventhouses, and they display query results that automatically refresh — often in near real time, with sub-second latency.

2026-06-28

Powershell: Invoke-Sqlcmd –Hostname Parameter sets the Application Name instead of the Host Name

Powershell: Invoke-Sqlcmd –Hostname Parameter sets the Application Name instead of the Host Name

Two of the parameters in SQL Server connections are the Application Name and the Host Name. You can see these in SQL Server if you execute the following command:

SELECT HOST_NAME() AS HostName, APP_NAME() AS ApplicationName;

On my system, that returns:

Host name and App name

I’ve always been a fan of having applications identify themselves in their connection strings. It makes tasks like tracing much easier. The tools supplied with SQL Server do a reasonable job of that as you can see above. But many other tools don’t do such a good job.

2026-06-27

Fabric RTI 101: Trend Analysis in KQL

Fabric RTI 101: Trend Analysis in KQL

Trend analysis is one of the most powerful applications of KQL — it lets you move beyond simple metrics and start understanding how your data evolves over time.

Most trend analysis begins with the make-series operator. This operator constructs a time-series dataset by grouping values into evenly spaced time intervals. You might, for instance, calculate the average response time or error count every minute, hour, or day.

Here’s a simple example:

2026-06-26