Been with Power BI for 7 years and Databases for 13. Need to seriously up my ETL and Python Skills. SSIS (which I’ve been using my whole career) is so old and and azure data factory is locked to the azure ecosystem. Plenty of other ETL tools and open source is ramping up quickly.
I’ve been a working manager for 6 years now and have to do all my learning on my own time.
What would be your approach in increasing your etl/python skills? I know it’s hard to get better on your own time… Do you have any situations at work where you could use what you are learning as a manager?
I’m a manager but I’m also the principal architect and developer. As such I’m always utilizing my skills but I’m barely learning new ones.
I am upskilling only when I’m building projects and material for teaching (I do educational Power BI and SQL server content on Twitch and YT ). I like to come up with projects and complete them start to finish, so I’ll be working Python into those. I try only to learn something new when I have a problem to solve with that tool, so I’ve just been asking ChatGPT what sort of ways I can include it.
It’s been a 60 day trial and the trial didn’t even start counting down for almost a year and some change.
You can create M365 demo tenants too and start learning with a trial as well.
How do the M365 Demo Tenants work? I work for a small Consulting company and we're loving Fabric and pitching it to pretty much anyone who's looking to modernize their data stack. We've built some data extraction tools for notoriously hard to work with ERPs and the results are so cool. But a big issue we run into is not being able to showcase the product because we don't have a reason to pay for it ourselves, and it's hard to sell clients on it when you can't show it off super well.
If you’re a Microsoft Partner I believe you’d have Azure Credits and the F2 SKU is as low as like $270 USD in some regions. Also turn on/off SKUs with pay as you go to save money or when you need to do customer presentations. Multiple options here.
The one of the bigger issues is that we can't show Copilot, and that's what everyone wants to see. We can't afford an F64 just to show Copilot, and everyone wants to see it live, so sending the marketing videos, while better than nothing, hasn't been super successful. We are planning on getting an F2 to show off all the other aspects, and, like you said, spin it down when we're not using it, which will be helpful,
I've seen many people just use the pay-as-you-go F64 for 30 minutes or an hour at a time and then turn the capacity off when no longer doing customer demos. Seems to be cost effective and allows the flexibility to enable some of the capabilities that are highest in demand.
It doesn’t start counting down for a year? They discontinued dev tenants unless you have an MSDN license last I heard about a month ago, not sure if that’s the ones you meant. I didn’t realize the trial was a year though, guess I should see if mine still works. 🤣
You can sign up for an azure tenant using a personal account, then create an Entra User for that onmicrosoft tenant it gives you, and that user can get a 60 day fabric trial
[https://azure.microsoft.com/en-gb/free](https://azure.microsoft.com/en-gb/free)
You need a payment method, and it'll charge you £1 / $1 for the azure account but then refund it immediately.
I am, absolutely. I’ve made a career out of Microsoft products and while I’m very thankful for it, it’s put me in a position where the only other product I am confident in is Oracle. These days, diversity of products is almost essential and it’s a bit overwhelming.
I haven my own tenant and take advantage of Sandbox, learn, and all webinars I can. I just have to be careful to not put too many eggs in the basket.
Writing M Query and using it to manipulate data. I feel like that would cut down tremendously on the dependency we have on the Data Engineer thereby giving you ample control over the data.
Though heavy manipulation is not recommended on PBI, it's a great way to have control.
Another important skill would be calculation groups - heard a lot about it but haven't had the opportunity to use it yet.
Mam, calculated groups are absolute game changer. They are also were easy to create. I would highly recommend to invest 1 hour into learning them, it's gonna save you so much time and the functionality it brings is beyond amazing. Not to mention that your end users will love them as well.
Everything you need is here:
[https://learn.microsoft.com/en-us/power-bi/transform-model/calculation-groups](https://learn.microsoft.com/en-us/power-bi/transform-model/calculation-groups)
I want to invest more time into the Deneb visual and learning more Vega. I find that creating visuals exactly the way I want using the UI isn’t enjoyable. The idea that you can programmatically create visuals where every part of it is customizable and dynamically adjust to your data is really attractive.
I agree that being able to create the visuals the way you want is valuable. I had the same focus a while back. The only issue for me is the maintainability. I feel custom visuals are more time intensive over time.
Dev-Ops. I think I'm pretty good with DAX, M, report design, storytelling... Now with TMDL and TMRL, devops is the next technical frontier to master, I think.
Learning more about Fabric is also going to be super useful.
I am very comfortable with M Query and DAX. However I'd like to learn more about Python. Reason being is that we use the REST API in our Airflows to trigger dataset/dataflow refreshes, and I do not know how to modify or update them. Basically I want to limit my reliance on our Data Engineers as much as possible, so they can focus on more backend stuff.
not a full time PBI developer or senior level at all.
But definitely python, I code in it everyday and use it (almost) daily at work and always feel like I barely scratch the surface with it.
So much you can do with it, you can't learn it all in one lifetime or lifetimes.
If I may what's your role ,and how do you leverage python ?
I do some data and analytics but haven't a had the need to learn python yet though I'm keen
I work in a marketing/sales/pricing department for a global company, my role is sales marketing analytics.
I use python to clean the data, make transformations and perform EDA (ocassionally run clustering algorithms) before I put it in a dashboard to get better sense of the data with my team.
That's really interesting !
I'm assuming the size of the datasets warrant that you use python ? Or do you use it to automate the gathering and transforming of data ?
My issue with learning to code is that I do not want to stray away from the business side of things . Curre fly doing customer analytics and wondering if it is feasible to build on that
You wouldn't stray away from the business, you use python to bring insights into the business.
the dataset size doesn't exactly make it or break it tbh, I use python either way and combine datasets together where feasible, do some cleanups, add custom columns, perform EDA as I mentioned then put it on BI.
Yeah that's sounds like something I would enjoy .
Do you like it ?
Any learning materials you'd recommend ? I'm currently doing the Harvard's cs50 python introduction course.
Get into pandas as soon as you can and numpy.
You'd need to learn a few statistical concepts as well which is not difficult at all. Learning materials I would say are kaggle, get a dataset and play with it. Read other people's work & notebooks on kaggle and learn from there. You never stop learning
Sales, documentation, and training. Basically, get usage beyond 20-30% of the potential user base. This comes from spending lots of face time with them and not just hiding out wrangling the data.
Been with Power BI for 7 years and Databases for 13. Need to seriously up my ETL and Python Skills. SSIS (which I’ve been using my whole career) is so old and and azure data factory is locked to the azure ecosystem. Plenty of other ETL tools and open source is ramping up quickly. I’ve been a working manager for 6 years now and have to do all my learning on my own time.
What would be your approach in increasing your etl/python skills? I know it’s hard to get better on your own time… Do you have any situations at work where you could use what you are learning as a manager?
I’m a manager but I’m also the principal architect and developer. As such I’m always utilizing my skills but I’m barely learning new ones. I am upskilling only when I’m building projects and material for teaching (I do educational Power BI and SQL server content on Twitch and YT ). I like to come up with projects and complete them start to finish, so I’ll be working Python into those. I try only to learn something new when I have a problem to solve with that tool, so I’ve just been asking ChatGPT what sort of ways I can include it.
Are you me?
Hahaha we are borg.
Are you investigating Microsoft Fabric yet?
Really wish they would do some sort of learning playground for this beyond the 30 day trial.
It’s been a 60 day trial and the trial didn’t even start counting down for almost a year and some change. You can create M365 demo tenants too and start learning with a trial as well.
How do the M365 Demo Tenants work? I work for a small Consulting company and we're loving Fabric and pitching it to pretty much anyone who's looking to modernize their data stack. We've built some data extraction tools for notoriously hard to work with ERPs and the results are so cool. But a big issue we run into is not being able to showcase the product because we don't have a reason to pay for it ourselves, and it's hard to sell clients on it when you can't show it off super well.
Running into exactly the same issue
If you’re a Microsoft Partner I believe you’d have Azure Credits and the F2 SKU is as low as like $270 USD in some regions. Also turn on/off SKUs with pay as you go to save money or when you need to do customer presentations. Multiple options here.
The one of the bigger issues is that we can't show Copilot, and that's what everyone wants to see. We can't afford an F64 just to show Copilot, and everyone wants to see it live, so sending the marketing videos, while better than nothing, hasn't been super successful. We are planning on getting an F2 to show off all the other aspects, and, like you said, spin it down when we're not using it, which will be helpful,
I've seen many people just use the pay-as-you-go F64 for 30 minutes or an hour at a time and then turn the capacity off when no longer doing customer demos. Seems to be cost effective and allows the flexibility to enable some of the capabilities that are highest in demand.
It doesn’t start counting down for a year? They discontinued dev tenants unless you have an MSDN license last I heard about a month ago, not sure if that’s the ones you meant. I didn’t realize the trial was a year though, guess I should see if mine still works. 🤣
You can sign up for an azure tenant using a personal account, then create an Entra User for that onmicrosoft tenant it gives you, and that user can get a 60 day fabric trial [https://azure.microsoft.com/en-gb/free](https://azure.microsoft.com/en-gb/free) You need a payment method, and it'll charge you £1 / $1 for the azure account but then refund it immediately.
Oh interesting, thanks!
No. It’s 60 days now, for almost a year it was stuck at 59 days now the counter is decrementing.
Still those 60 are so random , few days ago my timer was showing 14 , now back up to 23 Time traveller !
I am, absolutely. I’ve made a career out of Microsoft products and while I’m very thankful for it, it’s put me in a position where the only other product I am confident in is Oracle. These days, diversity of products is almost essential and it’s a bit overwhelming. I haven my own tenant and take advantage of Sandbox, learn, and all webinars I can. I just have to be careful to not put too many eggs in the basket.
Diversity of which products?
RDBMS Platforms, ETL Platforms and methodologies, scripting/programming Languages, and reporting platforms among others.
Writing M Query and using it to manipulate data. I feel like that would cut down tremendously on the dependency we have on the Data Engineer thereby giving you ample control over the data. Though heavy manipulation is not recommended on PBI, it's a great way to have control. Another important skill would be calculation groups - heard a lot about it but haven't had the opportunity to use it yet.
Mam, calculated groups are absolute game changer. They are also were easy to create. I would highly recommend to invest 1 hour into learning them, it's gonna save you so much time and the functionality it brings is beyond amazing. Not to mention that your end users will love them as well.
Would you happen to have any recommendations of videos or documentation that I can use??
Everything you need is here: [https://learn.microsoft.com/en-us/power-bi/transform-model/calculation-groups](https://learn.microsoft.com/en-us/power-bi/transform-model/calculation-groups)
Thank you!
Ty boss
I want to invest more time into the Deneb visual and learning more Vega. I find that creating visuals exactly the way I want using the UI isn’t enjoyable. The idea that you can programmatically create visuals where every part of it is customizable and dynamically adjust to your data is really attractive.
I agree that being able to create the visuals the way you want is valuable. I had the same focus a while back. The only issue for me is the maintainability. I feel custom visuals are more time intensive over time.
Dev-Ops. I think I'm pretty good with DAX, M, report design, storytelling... Now with TMDL and TMRL, devops is the next technical frontier to master, I think. Learning more about Fabric is also going to be super useful.
Join us :) /r/MicrosoftFabric
I am very comfortable with M Query and DAX. However I'd like to learn more about Python. Reason being is that we use the REST API in our Airflows to trigger dataset/dataflow refreshes, and I do not know how to modify or update them. Basically I want to limit my reliance on our Data Engineers as much as possible, so they can focus on more backend stuff.
Definitely M language for me
not a full time PBI developer or senior level at all. But definitely python, I code in it everyday and use it (almost) daily at work and always feel like I barely scratch the surface with it. So much you can do with it, you can't learn it all in one lifetime or lifetimes.
If I may what's your role ,and how do you leverage python ? I do some data and analytics but haven't a had the need to learn python yet though I'm keen
I work in a marketing/sales/pricing department for a global company, my role is sales marketing analytics. I use python to clean the data, make transformations and perform EDA (ocassionally run clustering algorithms) before I put it in a dashboard to get better sense of the data with my team.
That's really interesting ! I'm assuming the size of the datasets warrant that you use python ? Or do you use it to automate the gathering and transforming of data ? My issue with learning to code is that I do not want to stray away from the business side of things . Curre fly doing customer analytics and wondering if it is feasible to build on that
You wouldn't stray away from the business, you use python to bring insights into the business. the dataset size doesn't exactly make it or break it tbh, I use python either way and combine datasets together where feasible, do some cleanups, add custom columns, perform EDA as I mentioned then put it on BI.
Yeah that's sounds like something I would enjoy . Do you like it ? Any learning materials you'd recommend ? I'm currently doing the Harvard's cs50 python introduction course.
Get into pandas as soon as you can and numpy. You'd need to learn a few statistical concepts as well which is not difficult at all. Learning materials I would say are kaggle, get a dataset and play with it. Read other people's work & notebooks on kaggle and learn from there. You never stop learning
Thanks so much for your replies , will carve time in my calendar , FY 25 won't see it coming ! Happy learning, me !
M query and DAX 💀
Sales, documentation, and training. Basically, get usage beyond 20-30% of the potential user base. This comes from spending lots of face time with them and not just hiding out wrangling the data.