The Bit Bucket

One of the interesting aspects of recent AI work is the idea that we’re fast moving beyond prompt engineering. Not that long ago, it was all the rage, so I was fascinated to receive a review copy of The Practical Prompt Guide for GPT-6 Astra from my friends at PacktT.

Author

Curiously, this book is listed as being written by Steve T. As noted on his official Leanpub biography page , the authors behind Steve Publications often choose to write under pseudonyms or partial names for privacy or professional reasons. Consequently, he only operates publicly under the name Steve. I’m not a fan of this as it limits his perceived authority.

2026-10-31

I was watching a preview (but public) presentation today, and I noticed the button in Power BI for a whole new way of creating reports said Modern Report. I really hope that it doesn’t get out the door with that name.

One thing the IT industry never seems to learn is that calling anything New or Modern is a mistake.

I was recently working with a client, and they were changing the working IT environments for their staff. What struck me as odd was that they called the new environments Modern. Amazingly, Modern was actually the name of the environment. I’m sure they currently see the environments as the modern ones, but soon enough, it won’t be modern or new, and then the name looks really, really odd.

2026-10-30

In previous reviews, I’ve mentioned that I spend much of my time nowadays working with Microsoft Fabric but in many of those projects, I still regularly need to use Power Query. Doing that effectively means using the M language. I was pleased to receive a review copy of The Definitive Guide to Power Query (M) from my friends at PacktT.

Authors

Gregory Deckler is a fellow Microsoft Data Platform MVP, actibe blogger and Fabric/PowerBI community member. He is the author of many books on related topics.

2026-10-29

Edge computing plays a key role in modern real-time data architectures by moving some processing closer to where data is generated. Instead of sending every raw data point to the cloud, devices or gateways at the edge can handle local filtering, aggregation, and enrichment.

Using Azure IoT Edge or similar frameworks, organizations can deploy lightweight processing modules directly on devices, gateways, or factory controllers. These modules can execute logic such as:

2026-10-28

I spend much of my time nowadays working with Microsoft Fabric and there are many opinions on how to use it for the best outcomes, so I was interested to see a new book Analytics Engineering with Microsoft Fabric and PowerBI from friends of mine (in the Fabric community), Shabnam Watson and Nikola Ilic. Nikola sent me a copy to review.

Authors

Shabnam Watson is a business intelligence consultant and owner of ABI Cube, a company that specializes in delivering data solutions using the Microsoft Data Platform. She has decades of experience and is a fellow Microsoft Data Platform MVP.

2026-10-27

A digital twin is a virtual representation of a physical system or asset - such as an engine, a building, a production line, or a logistics network.

Unlike a static model, a digital twin is continuously synchronized with its real-world counterpart through real-time telemetry and sensor data. This constant data flow ensures that the virtual model reflects the current operating state of the physical system.

The purpose of a digital twin extends beyond visualization. It enables simulation, monitoring, and predictive analysis. For example, engineers can test what-if scenarios - such as how a machine might behave under higher load or different environmental conditions - without interrupting operations. It also supports predictive maintenance, by identifying early indicators of wear or failure before they result in downtime.

2026-10-26

A while back, I wrote about the ANSI_NULLS option for tables and after that I had several more questions related to NULL values.

Note that I mentioned NULL values, not values of NULL, and not values equal to NULL. That’s because being NULL is a state that a value is in, not itself a value. That’s why our queries say IS NULL and not = NULL.

Magic values

Now because of that, many developers see values that are NULL as a pain in the neck as they have to be dealt with separately, unlike other values. This can lead to many poor design decisions but I want to start today with the decision to use magic values.

2026-10-25

Several important trends are shaping the future of real-time data systems, moving beyond simple event streaming toward intelligent, autonomous, and action-oriented pipelines.

One key direction is the integration of streaming with AI and machine learning. Instead of passively analyzing data, systems can now make inferences or decisions as events occur - for example, predicting failures, recommending actions, or adapting system behavior in real time. This shift from descriptive to predictive and prescriptive analytics marks an important evolution.

2026-10-24

Today, I was editing some SQL code using the SQL editor in a Microsoft Fabric Warehouse.

I needed to reorder a list of columns.

I find that a pretty frustrating editor but usually I can avoid it by connecting with SSMS. But for some reason, SSMS decided it didn’t want to connect to the warehouse today either.

No problems, I thought I’ll just edit the code with a combination of SSMS, and Excel (to reorder the column names), and then paste the code back into the Fabric SQL editor. But every time I did that, I ended up with a bunch of strange orange boxes all throughout the code.

2026-10-23

Both Fabric Real-Time Intelligence (RTI) and Azure Stream Analytics (ASA) are designed to process streaming data, but they serve different roles within the Microsoft data ecosystem.

Fabric RTI is part of the broader Microsoft Fabric platform. It uses KQL (Kusto Query Language) as its foundation and is tightly integrated with OneLake, Power BI, and other Fabric components such as Eventstream and Activator. This integration makes it suitable for end-to-end real-time analytics, where streaming data is combined with historical data, transformed, visualized, and acted upon - all within one environment.

2026-10-22