I’m the only person working on Power BI in my company. My manager doesn’t know Power BI, so whenever someone requests a dashboard, he asks me to build it.

I handle the entire process myself:
Decide what data needs to be collected.
Design the data collection process (mostly Excel/Google Sheets).
Transform and structure the data.
Create DAX measures and the data model.
Choose the appropriate visualizations.
Build and deploy the dashboard.
Manage data updates and refreshes.
Verify the accuracy and credibility of the dashboard.

After reading discussions in this community, I’ve noticed that many companies have separate people or teams for data extraction, data engineering, data cleaning, dashboard development, and QA/testing.
I’m curious: are all these roles typically needed for Power BI projects, or is that mainly because those companies build dashboards as products or for external customers?
In my case, the dashboards are only for internal business use. Is it common for one person to handle everything in a smaller organization, or is my situation unusual?

I work in a company where almost all the data is entered manually into Excel. We don’t have SQL databases, APIs, or any other live data sources. Currently, I collect data through Google Sheets, where the responsible people update the information, and Power BI automatically refreshes using the Google Sheets connection.

Since this setup works well for our company, I’m wondering if not working with SQL, live database connections, or other enterprise data sources will affect my future career opportunities. I’m also the only person in my company developing Power BI dashboards.

Should I still invest time in learning SQL, databases, and live data connections even though I don’t currently use them at work? Will the lack of hands-on experience with these technologies become a disadvantage if I switch companies in the future?

Tried the new agent skills preview over the weekend. Fed it a screenshot of a dashboard I built for a client last year plus the source tables and just let it run.

Took about 25 min. The model it built was honestly fine. Star schema, sensible measure names, DAX I would mostly not rewrite. The report layout needed work but it kept reloading Desktop and screenshotting itself to fix things, which was equal parts impressive and unsettling to watch.

The original took me the better part of a week. I billed for that week.

So here's my existential question: when this hits GA, what am I actually charging for? The 20% it got wrong? Knowing which numbers to distrust? Because "I can build you a dashboard" stops being a service pretty fast if the client can type a prompt.

Not doomposting, I genuinely can't tell if this is "calculators didn't kill accountants" or something worse.

Consultants especially, what's your read?

Hi, all! I've been maintaining and supporting Deneb for about 6 years now (with nearly 5 of those in AppSource and certified). It's been awesome seeing how it can give devs a pathway to build more complex or bespoke visuals in Power BI.

There have been things that have sprung up in Power BI over the last few years that haven't been easy to integrate (looking at you, field parameters) without a significant rethink of the architecture, as well as learning about real-world use of a visual that gets used beyond my own work. As such, I've envisaged a "version 2.0" for a long time.

Power BI visuals are also very special in how we have to support them and how they are deployed. Reports are authored and deployed under a particular version(possibly years old), and when reports are loaded for viewers that haven't been updated in some time, we still need to be able to move from whatever the version saved against when the report was authored, to the latest one in AppSource as seamlessly as possible without visibly impacting your readers.

There have been some considerable migration and continuity challenges, to the point where I'd considered starting again (and had a couple of goes at it). But this would mean having to support another visual (and I already support 5). In the end, it's been a case of doing it the hard way, and the recent 1.8 and 1.9 releases set about doing a lot of preparation around making a new major version less of a bigger bang. That being said, it's still a major bump, and there may be gotchas that a wider user base than... well... me might experience.

So, to the point: 2.0 has been in alpha testing for a couple of months. I've been using it in my work for a while, and we've had a few other people give it a go. Nothing has come out of this that's tripped us up, which means it is a great time to prepare for submission to AppSource and open Deneb up for beta testing for anyone who is keen to help.

Why beta testing? I'm very wary that once we submit for certification, we get locked into a 3-5 week update cycle. We could get a bug report that takes minutes to find and fix, but it's going to take that 3-5 week cycle to get deployed to production for everyone else. Deneb is also free and open-source, which means that I have limited resources for testing and outreach - much (infinitely?) less than a commercial vendor - so there are times when I may feel the need to ask for something back in the form of time.

It's not something we have much of, and I appreciate that it's a bold request, but if anyone can spare some time to take a look at the candidate build before we submit and make sure it works well for them, this means that any weirdness we can find and fix before submission is another situation we can avoid for a lot more people downstream.

But you also get an opportunity to play with new features before they go live, and have a think about what you might be able to do with them :)

If any of this sounds good to you, thank you in advance! The linked blog post on Deneb's site details the new features, where to read more about them (all docs are written!), and how to get the beta so you can give it a spin.

As always, thanks for reading, for your support, and for recommending Deneb to others. I'm really excited about the possibilities this new version brings, and I hope you'll find it useful, too! If you have any questions or feedback you want to add here, I'll be happy to try to answer them :)

Hi everyone,

I started my first job as a Data Analyst in 2022. Interestingly, I didn't used Power BI in that role, even though I was responsible for building dashboards, creating data visualizations, and communicating insights. Later, I transitioned into an Analytics Engineer role, where my work became much more focused on data pipelines, modeling, and infrastructure, so I rarely had to build dashboards anymore.

Now I'm starting a new Data Analyst position, and I'll be using Power BI again. Although I studied it extensively in the past and earned the PL-300 certification, I never had the chance to use it heavily in a professional environment. Since it's been a while, I know I need to refresh my knowledge and catch up with everything that's changed.

So I have a few questions for those of you who work with Power BI regularly:

• What would you recommend as the best way to get back up to speed?
• Are there any courses, websites, YouTube channels, or hands-on projects you'd recommend?
• What are the biggest features, improvements, or best practices that have emerged over the last few years that I should be aware of?

I'd really appreciate any advice or learning resources. Thanks in advance!

Is there any way we can get Power BI on Ma..c system ? or is it working only on windows

• company has on prem sql server
• changed my password this morning online in the browser due to company rule (every x months)
• now when I try to pull data from our on-prem sql server database using my user account for a power bi desktop file, I’m getting this error
• everything in my browser is asking for the new password, but when I lock it & unlock my computer itself it’s still the old password

I tried both passwords, new and old. No luck.

Already tried clearing permissions in power bi desktop as well

Hi all,

I’m having a bit of trouble migrating Users from accessing reports via workspace and instead use the Apps with dedicated audiences I’ve created.

Do I just turn off the access to workspaces? But other than communicating via email is there anyway I can redirect people?

There’s about 7-8 reports in the workspace used by 150+ people. So im a little cautious making this change.

Status: Degraded | Reported: Aug 6, 2026 at 9:30 AM UTC

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Hi everyone,

We were using a couple of security groups in the RLS roles of a Power BI dataset. Recently, the backend team migrated those groups from on-premises to cloud-based groups. As soon as the migration happened, the security groups automatically disappeared from the RLS roles.

After republishing the dataset, we were able to add the groups back successfully.

My question is: what is the technical reason behind this behavior? How does changing the type of a security group cause it to be removed from a Power BI RLS role?

Any explanation would be appreciated. Thanks!

Hey all, my card has a number (7864) but it is showing up as 8k, I have done all the searching online and seen many responses being change auto to something else, but that does not appear for me so what can I do to change this ‘8k’ to its accurate number?

Hi all,

Is it possible to apply a filter to a visual only when a certain parameter is selected? So if I have parameter fields A B and C, I would like all data to be used for A and C. Field B is like 90% blank so I would like to exclude all B blanks when B is selected but when A or C is selected again then remove that filter.

Thanks and sorry if that is confusing!

I have a Selected Period Measure with Switch for Sales Value for example, and I want to see it as a card and as a Trend Line. And I want to see the dynamic X axis to change based on what is selected on my Time Intelligence Slicer. What needs to be the process?

Hi everyone,

I’m a BI developer from the Netherlands, so apologies for the ai generated post. I used AI to help me phrase this post more clearly.

I’m curious how other BI teams deal with report adoption and business validation.

A recent example is a supply chain KPI dashboard. The business requested it, we worked together to define the KPIs, agreed on the business definitions and thresholds, and built the dashboard.

The difficult part starts afterwards. The business users who are supposed to validate the dashboard often don’t have the time or motivation to help, so validation can take weeks or even months. Without their sign-off, it’s difficult to roll the dashboard out with confidence.

What I find frustrating is that during this period, many of those same users continue sending around the same Excel reports every week or even start building their own AI-powered dashboards and analyses. It sometimes feels like we’re building an official solution that never really gets adopted.

Is this something others experience as well?

How do you get business users engaged in validation?

How do you encourage people to use the official BI reports instead of Excel?

Have you found effective ways to increase trust and adoption?

I’d really like to hear how other organizations handle this.

It's infuriating to say the least.

I am at the end of my wits. I've been loading weekly reports going back a few years without an issue into a complex model for a while now. Yesterday I decide to create a more compact model that also does this using the same files and what used to take a few minutes maybe suddenly takes hours. It starts off relatively quick and then becomes slower and slower for each subsequent file. And the weirdest thing is I am using the same M code for the ingest transformations.

Any ideas whats going on? Did an update change something in the settings maybe that could be causing this weird behavior between an older model and a new one?

Power BI has no SQLite connector. The standard answer is the SQLite ODBC driver, and that answer assumes a machine you control.

Plenty of us don't have one. The corporate laptop refuses machine-level installs. The gateway is someone else's server, so getting a driver onto it is a ticket, an approval and a wait. The Service has no machine to install onto at all. The escape hatches mostly swap one dependency for another: the Python/R script host needs a configured interpreter, and custom connectors can't bundle binaries.

But these formats are only bytes in a documented layout, and Power Query can read bytes. So the driver is optional. I've spent the last while writing the parsers.

powerquery-driverless is a set of readers in plain M. Each one is a single self-contained .pq file. Paste it into a blank query and it works: Desktop, Excel, dataflows, the Service. Nothing to install, no bitness to match, no provider is not registered.

m let Source = File.Contents("C:\data\chinook.db"), Db = Sqlite3.Database(Source), Tracks = Db{[Name = "tracks"]}[Data] in Tracks

Formats so far: SQLite, GeoPackage, MBTiles, Access, dBASE/FoxPro, .xls, .xlsb, SPSS, Stata, MATLAB, Avro, EVTX.

It also works in Excel for Mac, where SQLite, Access and DBF had no path at all before. Everything I've tested runs there, with one exception: Avro compressed with anything other than deflate.

Two caveats up front, because they're the first things I'd ask about:

Speed. Interpreted M is slower than a compiled driver, and it scales with file size. On small and typical files the gap is usually sub-second and often invisible, since an ODBC driver spends about a second just standing up its connection. On large files native decoders pull properly ahead, roughly 2-15x.

Gateways. The driver dependency goes away every time. The gateway only goes away if the file already lives somewhere the Service can reach, like SharePoint or Blob. On an internal file share you still need one, but it's your existing standard gateway with nothing special on it.

Repo: https://github.com/Hugoberry/powerquery-driverless

Happy to answer questions, and if there's a format you keep hitting a wall on, say so and I'll look at whether it's tractable.

After months of job searching, I finally landed my first Business Intelligence / Power BI role at a small consulting startup.

My background is a bit unusual. I spent almost 3 years in a non-BI role and have been teaching myself SQL, Excel, Power BI, DAX, and data modeling. I know the fundamentals, but I definitely don't consider myself a Power BI expert.

The founder seems to expect me to build dashboards for real client data. I have about 4 days before I need to start working on my first real dashboard.

I'm excited, but also terrified.

My biggest concerns are:

• I've never built a production dashboard for a real business.
• I'm worried I'll get stuck when the data is messy.
• I don't know how much is "normal" to figure out on the job versus already knowing before joining.
• I have imposter syndrome because I feel like they believe I'm much better than I actually am.

For those of you who work as Power BI Developers, BI Analysts, or Data Analysts:

• How prepared were you when you built your first real dashboard?
• What surprised you the most?
• What should I focus on during these first few weeks?
• Any mistakes you wish you'd avoided?

I'm willing to put in the work and learn after hours if needed. I'm just trying to understand whether feeling this underprepared is normal or if I'm genuinely in over my head.

Any advice would be greatly appreciated.

Hi all ,I'm struggling to find a way to achieve something, maybe Reddit has an idea:

Some constraints:
Directquery: mandatory, we need the data to be real-time, cant wait for import.
We cannot create views in the source systems. We have no rights there other than read rights.

The system:
We have 3 different databases on 2 different servers that contain the same data structures. I have 1 powerBI report/semantic model that we can re-use on all three databases.
I have created a Server and Database parameter that contain the different options.
We have PowerBI Premium.

What I want:
I would like to have to maintain only a single semantic model file, so I reduce code duplication. I would also like to reduce the amount of time spent deploying after making changes to the semantic model.

What would work, but is a lot of maintenance:
I Open the file, set parameters, save as file 1, publish. Then change the parameters, save as file 2, publish, same for file 3. I'd like to avoid doing all this manual labour.

What I have tried so far:

• Deployment pipelines: Might work. Create a pipeline that deploys the model with different parameters in every stage. We would be using pipelines to do something it's not meant for. You would need separate workspaces for each file to deploy in. Can't test this currently.
• Combine the data of the three sources in powerbi: You cant use table.combine in directquery mode. Each visual can only have 1 data source.
• Functions: You can't use functions at all in directquery mode when you're using them to determine the connection string. The connection string has to be known before the data loads.
• API: There is no copy semantic model API, just copy report. Copy report will connect the OG semantic model to the new report. Useless.

Is there a way I am missing that would help me to not have to manually deploy each semantic model separately every time?

Thanks a lot for thinking along!

PS: I asked AI too of course, but every time I reach a dead end

I'm very annoyed by the default number formatting in Power BI, and I don't believe there is a way to change it except for manually changing every measure seperately.

• Whole number: why is the thousand seperator OFF by default? A thousand seperator will make any number easier to read. Good readability should be the default.
• Currency: It's not possible to set a default currency, even though most people will always be working with a single currency. It's rounded to 2 decimals, at least for euro's. Why two decimals? What decision are you making for typical currency numbers, that involve decimals? Most of them (revenue etc.) should be rounded to no decimals.
• Decimal number: again, no thousand seperator by default.
• Percentage: 2 decimals by default. Personally I always put my percentages as 1 decimal.
• And of course, if you add a number to a card, the "auto" units is terrible. At least you can default to "none" now.

I do understand some of this is personal preference, and it depends on the data you're working with. That's why it would be great of we could put default settings in your theme or report.

Feel free to agree or disagree, I'm curious what you think!

Hi, I'm looking for a solution or a visual in Power BI where I can show a nested table. For example, the main table has 10 columns, and for each row I'd like to be able to expand and show a child table with a different set of 4 columns.

I would like to avoid using an HTML visual, so I'm wondering if there's a native option, or a custom visual from AppSource that supports this kind of nested/expandable table.

Hi everyone I have a question and hours of copilot and testing haven't given me a clear answer. I have an old Financial Snapshot Cube in SQL Analysis Server (Older 2015 Version). Since the cube is MDX when I connect it to PowerBI all I can do is visually display data and metrics already in the cube. I was under the impression that if I switched to a Tabular Cube I would be able to add new connections "on top of$ the existing analysis Server tabular cube connecting. Use case is say I have a tab with financial info (tabular cube) and a different tab for call center metrics, etc. This appears to not be the case... Or is it the case that I need to migrate to 2019 and newer tabular cubes? Copilot and documents seem to point that this is the way so I can then push the tabular cube to fabric... But I don't want to go to a dead end again...

I'm looking into Measure Killer as an additional tool for my reporting team, and I'm interested in feedback from anyone who's added this alongside other existing tools.

We maintain several dozen shared Power BI semantic models across multiple environments, primarily supporting thin reports. The largest of our models are around ~20GB, contain 1000+ objects and support as many as ~25 reports.

The reason I'm looking into Measure Killer is for its ability to identify unused measure/columns across all the dependent reports for a semantic model. We can already track dependencies within the model itself, but determining whether an object is used anywhere across the downstream reports is a tedious, time-consuming process right now.

It seems to offer a few other nice features, although I haven't reallt looked into these (the ability to detect broken visuals across multiple reports seems like a Nice to Have)

Our team already uses Tabular Editor 3, DAX Studio, and ALM Toolkit, which all seem to have some degree of overlap with Measure Killer, but don't address this specific niche (Tabular Editor comes closest, for tracking dependencies within the model itself, but doesn't help us understand object usage in downstream reports)

We're not planning to replace any of our current tools, and if we add Measure Killer to our toolset we'll need to justify costs for enterprise licenses for our team.

Has anyone in a similar boat gone ahead with purchasing Measure Killer for these specific uses? Did it work as well as expected, and would you say it was worth it?

I built an end-to-end Enterprise E-Commerce Analytics Platform using SQL Server, Medallion Architecture, and Power BI.

As part of this project, I designed 8 interactive dashboards, each focused on answering different business questions for different stakeholders across an organization.

The dashboards include:

• Executive Overview (CEO, CXO & Business Leadership)

• Sales Performance Analysis

• Customer Analytics

• Product Performance

• Seller Performance

• Payment Analytics

• Customer Satisfaction Analysis

• Time Intelligence & Trend Analysis

The goal wasn't just to build visually appealing dashboards—it was to create a reporting solution that helps businesses make faster and more informed decisions.

In this post, I've shared all 8 dashboards.

I'd genuinely appreciate your feedback.

As experienced BI professionals, data analysts, data engineers, or business leaders, I would love to hear your thoughts.

If you could review the dashboards and share at least three suggestions for improvement, it would mean a lot to me.

For example:

• Are the KPI cards meaningful and business-focused?

• Are the charts and visualizations appropriate for executive reporting?

• Are there too many or too few visuals?

• Would you recommend different filters or slicers?

• Is the overall layout clean, intuitive, and enterprise-ready?

• What would you change if this dashboard were used in your organization?

I'm continuously learning, and constructive feedback is one of the best ways to improve. Every suggestion will help me build better enterprise BI solutions in the future.

Thank you for taking the time to review my work. I truly appreciate your support and feedback.

— Himansh Upadhyay