The Bit Bucket

Fabric Maps allow you to visualize spatial data as it changes in real time. When integrated with Real-Time Intelligence, you can stream live data directly from Eventstreams or query current states from KQL databases.

Each map layer can represent different metrics — such as sensor status, delivery vehicle locations, or regional anomalies — updated continuously as new events arrive.

You can also apply time slicers and filters to replay historical activity, helping to analyze event sequences over time.

2026-07-14

I recently received a review copy of Agentic Architectural Patterns for Building Multi-Agent Systems by Dr. Ali Arsanjani and Juan Pablo Bustos from my friends at PackT.

Authors

Dr. Ali Arsanjani is Director of Applied AI Engineering at Google Cloud where he leads a center of excellence bridging research, forward-deployed engineering, and enterprise implementation.

Juan Pablo Bustos is also currently at Google, and serves as a strategic partner to Fortune 50 corporations and global institutions. He specializes in operationalizing AI for the enterprise.

2026-07-13

Dashboards are an effective way to visualize data, but not every use case involves a person watching a screen.

In many organizations, the most valuable insights come when real-time intelligence is embedded directly into operational systems.

Microsoft Fabric makes this possible by allowing you to expose query results as APIs — typically REST endpoints built on top of KQL Databases. This means that the same data you’re using in dashboards can also be made available to web or mobile applications, business workflows, or partner integrations.

2026-07-12

I recently received a review copy of The New Quantum Era: An Outsider’s Introduction by Sebastian Hassinger from my friends at PackT.

Author

Sebastian Hassinger has held key positions at Apple, IBM, and AWS. He is now an independent consultant and advisor. You can find him on The New Quantum Era podcast.

Content

This is a rare kind of technology book: ambitious, historically grounded, technically serious, and still readable for people who do not have a physics degree. And Sebastian is well placed to write it. He’s had both insider access and outsider sympathy.

2026-07-11

In the past, if you wanted a real-time Power BI dashboard, you had to use streaming datasets — data pushed directly into Power BI from an external source.

While that approach worked, it came with significant limitations: the data couldn’t easily be joined with historical information, retention was limited, and managing the push model was complex.

That model is now deprecated — streaming datasets shouldn’t be used for new solutions.

2026-07-10

I work with data. I understand that for most organizations, that the data they own is the most valuable asset the company owns.

One thing I’ve learned from working with data is that unlike application software, data generally outlives generations of applications, is often used by many different applications, and typically just morphs from shape to shape over time. It almost never gets totally refreshed.

This is a good thing.

2026-07-09

More SQL love !

Recently at Microsoft Build, Azure HorizonDB was announced. And we’ve just completed our first course using it.

Creating reports, analytics, or applications? And need to get data out of Azure HorizonDB? Learn to write SQL queries like a pro !

We have very popular SQL courses, for T-SQL, PostgreSQL, Snowflake, Oracle, DB2, and MySQL. We’ve just added our new course Writing SQL Queries for Azure HorizonDB and you can enrol in it now. It’s just $95 USD.

2026-07-09

Thresholds are great for simple conditions — but they fall short when what’s normal changes throughout the day, week, or season. That’s where anomaly detection comes in.

Instead of relying on fixed limits, anomaly detection uses statistical and machine learning techniques to model what’s normal for a given signal, then flag data points that deviate from that pattern.

For example, network traffic might be high during business hours but low overnight — a single static threshold would either miss issues or trigger constant false alarms. Anomaly detection adjusts dynamically, recognizing these natural variations in the data.

2026-07-08

Memory is a precious resource on most systems today. SQL Server loves memory, so it’s important to avoid wasting it.

One common cause of wasted memory is what we call plan cache pollution. The plan cache is the region where SQL Server stores compiled query plans (and query plan stubs).

There are some nice new DMVs that give you details of what’s in that cache but nothing still compares to one of the older compatibility views sys.syscacheobjects. You can use it to see what’s in your plan cache:

2026-07-07

In real-time analytics, thresholds are the simplest way to detect when something goes outside of normal operating conditions.

A threshold is just a fixed value or condition applied to a metric. For example, you might set a rule to flag when CPU usage stays above 90% for more than five minutes, or when transaction latency exceeds two seconds.

In Fabric Real-Time Intelligence, thresholds are typically implemented within KQL queries or dashboard visuals — for instance, using conditional formatting to highlight values above a certain limit, or defining an analytic rule to monitor a KPI in real time.

2026-07-06