Just don't ignore the economics of productivity. We need a world where we can produce immense amounts of food and energy with as little impact to the environment as possible.
November 26, 2025 at 5:10 PM
Just don't ignore the economics of productivity. We need a world where we can produce immense amounts of food and energy with as little impact to the environment as possible.
As a data professional for 25 years AI is such a valuable tool. It increases my productivity by 10x, soon to be 100x. Increasing productivity is how humans can produce food cheaper, create new innovations (energy efficient transport, solar), and will ultimately be a great benefit to society.
November 26, 2025 at 5:08 PM
As a data professional for 25 years AI is such a valuable tool. It increases my productivity by 10x, soon to be 100x. Increasing productivity is how humans can produce food cheaper, create new innovations (energy efficient transport, solar), and will ultimately be a great benefit to society.
No doubt that AI isn't going away even if the AI bubble pops. We need to learn to to measure carbon and create an economy that can exist with reliance on growth. (And distributes income more widely)
November 26, 2025 at 4:33 AM
No doubt that AI isn't going away even if the AI bubble pops. We need to learn to to measure carbon and create an economy that can exist with reliance on growth. (And distributes income more widely)
A few reasons that are common are 1) Slower performance 2) Dim table gets limited by a fact when it shouldn't 3) potential for ambiguous relationships when expanding (can't create new relationship that is needed because another path exists)
November 14, 2025 at 6:06 AM
A few reasons that are common are 1) Slower performance 2) Dim table gets limited by a fact when it shouldn't 3) potential for ambiguous relationships when expanding (can't create new relationship that is needed because another path exists)
It's certainly less risky in a small model. The larger a model gets the more important data modeling becomes! Starting with a few rules makes life easy. 1) Dims filter Facts with a one way relationship. 2) Facts don't filter other Facts. 3) When Facts need to filter Facts use a SCD or bridge table.
November 14, 2025 at 5:49 AM
It's certainly less risky in a small model. The larger a model gets the more important data modeling becomes! Starting with a few rules makes life easy. 1) Dims filter Facts with a one way relationship. 2) Facts don't filter other Facts. 3) When Facts need to filter Facts use a SCD or bridge table.
Got it. Expose those fields via measures when possible. If the employee fact must filter other facts then decide if that table is actually a dim. The fact could be duplocated to move the attributes you need into a dedicated dim table with new primary key. Similar to a SCD with surrogate key. 😅
November 11, 2025 at 4:22 AM
Got it. Expose those fields via measures when possible. If the employee fact must filter other facts then decide if that table is actually a dim. The fact could be duplocated to move the attributes you need into a dedicated dim table with new primary key. Similar to a SCD with surrogate key. 😅
Other measures should work perfectly if the attributes are all from your common dimension tables. Adding attributes from other fact tables is where it becomes challenging.
November 11, 2025 at 4:13 AM
Other measures should work perfectly if the attributes are all from your common dimension tables. Adding attributes from other fact tables is where it becomes challenging.
Adding an attribute from your current Employee table (which is acting like a fact table) will cause duplication. This can be avoided by only exposing data from Employee Fact via a measure.
November 11, 2025 at 4:07 AM
Adding an attribute from your current Employee table (which is acting like a fact table) will cause duplication. This can be avoided by only exposing data from Employee Fact via a measure.
Thanks for sharing data model. The measure is the glue. Because blank measures results are filtered automatically In Power BI. Create a visual with EmployeeName from EmployeeDim, and Leave Days on rows. Then click a single date and the visual will show only Employees with Leave Days on that date.
November 11, 2025 at 3:52 AM
Thanks for sharing data model. The measure is the glue. Because blank measures results are filtered automatically In Power BI. Create a visual with EmployeeName from EmployeeDim, and Leave Days on rows. Then click a single date and the visual will show only Employees with Leave Days on that date.
The typical best practice is to duplicate the Employee table to create "Employment Fact" (limit columns to just the date fields needed), then use that data for employee measures. This insulates Employee and Date to keep them as fully independent dimensions.
November 11, 2025 at 12:34 AM
The typical best practice is to duplicate the Employee table to create "Employment Fact" (limit columns to just the date fields needed), then use that data for employee measures. This insulates Employee and Date to keep them as fully independent dimensions.
It's 100% possible to build a great data model and never enable a relationship where a Fact filters a Dim. There are some cases where facts can filter other facts but this needs to be done very carefully. The measures are the glue that bind everything together to create the effect you are after.
November 10, 2025 at 11:55 PM
It's 100% possible to build a great data model and never enable a relationship where a Fact filters a Dim. There are some cases where facts can filter other facts but this needs to be done very carefully. The measures are the glue that bind everything together to create the effect you are after.
Enabling this bidirectional relationship will impact the future expandability of your model. When you have a new fact table to add, like "Employee trainings completed", you'll need a relationship between Date and Employee to this new fact table. However the two way relationship creates two pathways
November 10, 2025 at 11:46 PM
Enabling this bidirectional relationship will impact the future expandability of your model. When you have a new fact table to add, like "Employee trainings completed", you'll need a relationship between Date and Employee to this new fact table. However the two way relationship creates two pathways
Typically the measure "Leave Taken" would be used to show the intersection of Date and Employee without create the two way relationship. Add this measure to any visual and it will narrow the data. The measure can be in a hidden column or even visual filter. I'll explain why in my next reply.
November 10, 2025 at 11:43 PM
Typically the measure "Leave Taken" would be used to show the intersection of Date and Employee without create the two way relationship. Add this measure to any visual and it will narrow the data. The measure can be in a hidden column or even visual filter. I'll explain why in my next reply.
First we have to figure out the energy and climate problems we have, but once that is solved then why not? In the future I'd love to have a personal assistant to download my music, find me new music, keep tabs on the bands on town, prep birthday cards for personalization... things I don't do today.
September 29, 2025 at 5:22 AM
First we have to figure out the energy and climate problems we have, but once that is solved then why not? In the future I'd love to have a personal assistant to download my music, find me new music, keep tabs on the bands on town, prep birthday cards for personalization... things I don't do today.
Small stepping stone in the journey to a code based approach. Soon these users will realize Excel is holding them back and the power of AI code generation will win.
Small stepping stone in the journey to a code based approach. Soon these users will realize Excel is holding them back and the power of AI code generation will win.
Great analysis and take. I'm loving the ability to create technical products more quickly than I could have ever done before! While AI has caused a lot of disruption for me (budget shifts / job stability), it's opening up a lot of possibilities.
June 27, 2025 at 4:01 AM
Great analysis and take. I'm loving the ability to create technical products more quickly than I could have ever done before! While AI has caused a lot of disruption for me (budget shifts / job stability), it's opening up a lot of possibilities.
People tell me nobody wants to look at climate curves anymore, yet here we are!!! Please enjoy our interactive journey through 485 million years of climate history and dive into the fascinating and important work of paleoclimate scientists.
It does encourage some people to work on their resume & get in a habit of applying, but if there aren't enough jobs then it's all pointless. The next wave of robotic and AI automation is here and we need policies that help people.
May 25, 2025 at 2:48 PM
It does encourage some people to work on their resume & get in a habit of applying, but if there aren't enough jobs then it's all pointless. The next wave of robotic and AI automation is here and we need policies that help people.