I have this table in PbI having columns marketname, products and count of review id. I want to calculate the count of markets having 5 products and those 5 products must have 10 reviews each. How can I achieve it in Pbi without downloading this export and do it manually in excel?

We use the traditional ones but they are complicated and not shareable.. Does anybody have experience?

Welcome to the 'Entering & Transitioning into a Business Intelligence career' thread!

This thread is a sticky post meant for any questions about getting started, studying, or transitioning into the Business Intelligence field. You can find the archive of previous discussions here.

This includes questions around learning and transitioning such as:

• Learning resources (e.g., books, tutorials, videos)
• Traditional education (e.g., schools, degrees, electives)
• Career questions (e.g., resumes, applying, career prospects)
• Elementary questions (e.g., where to start, what next)

I ask everyone to please visit this thread often and sort by new.

It’s Thanksgiving - I’ve worked with Power BI since 2018 and have loved every minute of it. To that end, I have made something I genuinely think many will get a lot of value from. It’s my form of thanks to everyone in the Power BI community for all the great years….

Backstory

Over the past 18 months, I’ve been actively working on a solution to address a significant challenge in Power BI: when a data model or dataflow is changed, what is the impact on all the visuals in reports that are connected to that model/dataflow, across all workspaces.

In our organization, our primary Org App has nearly 250 visible pages across 20 reports, all connected to the same model. This makes it difficult to track how and where specific fields, measures, and tables are used, increasing the risk of unintentionally breaking visuals or dashboards during model and dataflow updates. We have tried using Purview but that doesn't extend to the report/visual level. I eventually came across a Tabular Editor script made by Michael Kovalsky that helped extract metadata from reports.

Throw in 18 months of updates, automations, help from my good friend ChatGPT, many tears, lots of joy, a few more tears, and some final joy....and it's now to a point that I can share to the masses for their joy.

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What It Does

This solution provides a quick and automated way to identify where and how specific fields, measures, and tables are utilized across all Power BI reports and workspaces by analyzing the visual object layer. It also backs up and breaks down the details of your models, reports, and dataflows for easy review, offering a truly ‘complete’ view into your Power BI environment.

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Use Case

The main feature enables you to fully understand the downstream impact of data model changes, ensuring you don’t accidentally disrupt visuals or dashboards—especially when reports connected to a model span multiple workspaces.

Additionally, the tool backs up every model, report, and dataflow, providing a clear, comprehensive view of your entire Power BI environment, including dependencies. The results are presented in a Power BI model, making them easy to explore, analyze, and share with your team.

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Key Features

• Automated Impact Analysis
  • Quickly identify where and how specific fields, measures, and tables are used across all reports and workspaces.
• Comprehensive Backups
  • Back up every model, report, and dataflow across all workspaces.
• Detailed Insights
  • Gain a complete view, dependencies, and lineage of your models, reports, and dataflows
• User-Friendly Output
  • Results are presented in a Power BI model, facilitating easy exploration, analysis, and sharing.

Small example of the final Power BI output:
https://app.powerbi.com/view?r=eyJrIjoiYzkzNWZlYWItMDc4OS00YTE2LTg0YTYtZTc3MDdlYzUwMzUxIiwidCI6ImUyY2Y4N2QyLTYxMjktNGExYS1iZTczLTEzOGQyY2Y5OGJlMiJ9

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I hope everyone enjoys!
Github link: https://github.com/chris1642/Power-BI-Backup-Impact-Analysis-Governance-Solution

TLDR: here is a solution that anyone should be able to run and automates backing up every model, report, and dataflow across all workspaces - and then gives you a complete breakdown of your entire power bi environment, even at the visual level of reports connected to a separate model....allowing for a true impact analysis for any model or dataflow changes.

Hi Everyone,

I have over 10 years of experience in analytics across various functions and domains, including working with several tech companies in the SF Bay Area. I’ve also had extensive experience using a variety of analytics tools like Google Analytics (GA) and Amplitude, as well as Business Intelligence (BI) tools.

If anyone has questions about data analysis or working with data in Google Sheets, I’d be happy to help! I have some free time this Thanksgiving and would love to assist anyone looking to analyze or understand their data better.

Feel free to ask!

Happy Thanksgiving!

Does collaboration with other marketing functions helps in driving useful insghts? Eveb after having data and proper visualisation, I am unable to strengthen this area in current role.

I am part of a fairly small IT team within a large organization and on joining them. I noticed over time they have just bought shining tools pushed to them by vendors and the ELT has mandated we should reduced our OPEX cost. One of such tool is called Bizlink(it cost a bunch), it is used for api consumption, load data to a blob container and some EDI txns, some downloading of files from one server to the other, recently it was used to download some vendor data sent to an email. I want to push for the team to start developing some of this thing using Python which am sure like the api consumption and data download from email I have done before so that we can sunset the tool. I am not just sure whether this is a good move or not . Has anyone faced this kind of issue before. Your advise will be highly appreciated. Thanks

Hi all I'm new here so hope this is okay.

My current job uses an excel spreadsheet to input data about different technologies and their maturity alongside other details. The excel then analyses the data using the Heilmeier Catechism method, to provide insight into items to monitor, discard or recommend doing something with based on highest impact, speed, least risk etc. It's very clunky and only as good as the last person to open it (data and formula integrity, accuracy). My question is anyone familiar with a ready built tool or can recommend a simple enough to implement alternative?

Do you keep a data glossary/dictionary to keep track of what each field of each data table means?

If yes, where do you keep track of this stuff? Do you find it helpful?

If no, do you think it would be helpful for your business? Do you find productivity is slower without this common understanding of the data across all employees/stakeholders?

I’m working on a BI project right now and scope creep is starting to become a real issue. It feels like every time we make progress, new requests or changes come in that’s usually outside the original scope. Some are small but they add up so it’s hard to keep things on track.

Just wondering how others deal with this in BI work. How do you balance making reasonable adjustments while keeping the project moving forward? Any strategies or tips to manage scope creep?

Background: I run an e-commerce business that sells software in a traditional model (not SaaS) direct to customers. We have about an even split of first-time and returning customers in any given year, and we have been in business since 2008. Because we're pretty well-established in our niche, we get a ton of referral/word-of-mouth/organic search traffic, which makes ad attribution virtually impossible. That's how I got interested in the concept of MMM to help make sense of ad spend & revenue data to answer key business questions.

Our data:

* Daily revenue starting from Jan 1, 2022 (I could go back further, but because of covid effects boosting us in 2021, I'm not sure that would be helpful?)

* Revenue split between new and returning customers

* Facebook ad spend, broken down into top, middle, bottom of funnel, including revenue attribution and impressions for those

* Total number of visitors per day - although this data unfortunately starts only in Aug 2022, Google deleted our data before that.

* Total orders per day, split by new vs. returning, and free ($0) vs paid

* Total discount as a percentage of MSRP - i.e. a value of 0.8 would mean that factoring in all coupons, sales, crossgrades (etc) people paid 20% less than list price

* True/false flags for whether a day had an email campaign, storewide sale pricing, or a recent new product release

* Traffic origination source as attributed by Google (starting Aug 2022) such as Organic Search, Paid Search, Organic Social, Paid Social, etc.

Our data ranges are fairly variable in terms of revenue per day, although ad spend fluctuates more slowly. We have tracked our Google ad spend as well, although the total spend is probably about 5% of Facebook, and for far fewer days.

The business questions I'm trying to answer via MMM are :

1. To what degree are our ads producing revenue that would not have occurred otherwise? What is our true ROAS?

2. What is our optimal ad spend level, overall and by BOFU/MOFU/TOFU?

3. To what degree does discount % impact # of orders, revenue, and AOV?

4. What is our optimal discount %?

While I'm fairly technical and an experienced programmer, I'm no data scientist. I've been trying to get Claude (the ChatGPT competitor) to walk me through the process step by step of building a Python program to analyze this data using a series of transformations, regressions, and model trainings, but it's all a bit over my head to the point where I don't know if it's doing it 'right'.

I'm wondering if it would be worth continuing down that path, maybe following some more structured guides to build our own analysis tools, OR whether we should use an open-source platform like Facebook Robyn which seems quite powerful but maybe not suited for our data set, OR some third option I don't know about.

Any perspective appreciated... thanks in advance!

Hoping for some recommendations here, my team needs to build some customer-facing reports that I would like to make look extremely professional.

I would like to find something that gives our users high-resolution charts & graphs, good layout capabilities, very good text styles, and ideally an ability to include narrative text.

My team's skillset is SQL, python, golang, web dev, data warehousing. So, we'd prefer a tool that supports SQL & joins rather than a semantic layer, and more of a focus on PDF generation than a general purpose reporting dashboard.

The people creating the reports can write SQL, a bit of python, but are generally less technical.

Thanks in advance!

Is it a wave of bots? Is this sub being recommended when people search for "business?"

Just seems unusual.

What are currently the top choices for this use case?

All data needs to be kept within company on company servers. No cloud connections/transfers.

Ideally drag/drop dashboard building.

Deploy as a company internal hosted web browser.

Ideally with easiest deployment as possible.

Free usage

Hi,

Found this subreddit. I'm currently a Management Analyst in the federal government, but I have no idea what my private sector equivalent is.

Things are looking a little "interesting" with the current administration here in the US and while I have civil service protections. I'm just preparing for a worst case scenario. So just need some clarification.

It seems business intelligence and business analysis is the closest to what I do but I wanted to ask here. Here are my main duties:

Use Tableau and Excel a ton. I create dashboards and connect Tableau servers. I prepare daily, monthly and annual reports on performance in our division and work on projects to address issues.

I assist management in workload tracking and management.

I do some automation with Power automate in our Microsoft ecosystem and work with a few macros in Excel.

I also report back to higher leadership and target certain work items and get them resolved.

Analyze data and come up with solutions to problems to better improve our division..

Maintain access to systems for personnel and manage their production and output for tracking purposes.

I also do some administrative items as well here and there.

I don't do SQL, or Python and we just don't use Power BI. Not sure if I should acquire these skills in the meantime to bolster my resume. I think the next step up from my this job uses these functions.

So am I a business Analyst? Or business intelligence analyst?

Hi Everyone, need some assistant here. I belong to a very small BI team in a retail beverage company, 2 DE who manage the warehouse( one of them understand the business and the data, the second is relatively new: ), 2 DA who do the PowerBI modeling, visualization and dashboard. Our major problem the DW was handed over the to DEs which was built on a lot of ADF connections to oracle, lot of 3rd party data sources. When there are issues, it takes the DE guys to figure out and making changes seems to take forever. The team purchased Databricks for another project and we are thinking of rebuilding the whole old DW on Databricks. We want to do it right this time, but the major problem we have is 1. So many data sources with many data qualities, non homogeneous relationships between the data e.g these data has monthly sales while another provides weekly and the business was to view the data and daily 2. Calendar, the 3rd party datasets has differed business periods and fiscal calendar and we need to map that to our own fiscal calendar. 3. 300 billions lines of rows which might affect Power Bi performance and all.

We want to solution this properly this time, my questions are around is there a specific modeling architecture that will suite this scenario, what other type of question would you be asking the DE team of this new build? Thank you

Hi all, I’m looking for ways to optimize the generation of data-driven A4 reports for our company.

We produce long environmental reports with text, images, graphs, and tables.

Current Workflow:

• Create a Word template for the report
• Use a Power Automate cloud flow to populate the template with data from Excel
• Create graphs in Excel, save them as images via an Excel script (triggered by the flow), and insert them into the Word document
• Trigger the flow either manually or using an HTTP request

Future Goals:

• Insert custom graphs created with Javascript /D3 via PowerBI
• Pull data directly from our data warehouse in Power Automate (instead of Excel).
• Build a simple Power App to manage templates and trigger the generation process.

This setup works but feels a bit clunky.

I’d love to hear how others handle branded, data-driven reports efficiently. Are there better tools or workflows to simplify this process?

We are looking for preferably off-the-shelf products that are usable by non-technical users.

Thoughts?

I’ve hit a brick wall trying to solve this.

Originally, my company had an on-prem BC solution. I had access to the MSSQL server to write SQL queries. When the SQL query was finished, I would then integrate it into PowerBi and everybody saw the data visualizations they needed.

Our consultant recently upgraded our BC solution to the cloud so no more on-prem meaning no-more sql queries.

I’ve tried the BC API Web Services to ping “job” data and I noticed that some of the data that was present in the sql table is not present in the web api page.

That’s the brick wall, how do I get the rest of the data? It looks like API web services pings designed pages and not the table itself.

I’m looking for any documentation or suggestions to help get the raw data out of BC Cloud. I’ve stumbled upon AL code training path with designing custom APIs, but I thought I’d ask for some insight first.

Thanks in advance

My company has gone from having no BI at all, relying on native reporting in various source systems, to having a robust set of dashboards with hundreds of visualizations within the space of 1-2 years. I have personally built everything from the ground up in that time. The typical story: I built some dashboards in Excel, a few executives loved them and asked for more, one thing led to another and we adopted a BI platform (Domo) and I went from accountant to BI Department of 1 practically overnight.

As our dashboards/visuals have grown, I have started recently hearing anecdotal comments like “there’s so much data” or even “there’s TOO MUCH data.”

Has anyone else been in this situation? Do you have any ideas or tips I can implement to help users (especially those lower in the org chart) navigate and find impactful data without getting lost in things they don’t care about? Best practices for a “homepage” or directory?

Edit: does anyone have any example directories or FAQ pages or other documentation for their users? Anything that helps users answer “where do I go for X data?”

Does the upcoming increase in PowerBI licensing 1. change your loyalty towards powerBI or 2. Make you want to consider switching to another platform?

Curious what everyones overall thoughts are and if it's as big a deal as some of the talking heads say.

Hey everyone, I started writing a data analytics newsletter two months ago out of my passion for writing, data, and building a community. I usually write about latest features from Data Platforms like Power BI, Fabric, Databricks, Snowflake, AWS etc. and try to give my POV on it. I enjoy writing and try to put out an edition twice a month. I also curate a list of data events happening in North America and cool data jobs here.

If that something that interests you, please let me know and I can share the link. Please be kind and patient as it is my first attempt at creating something like this. Subscribe if you'd like. Thanks in advance!! :)

Hi all, long time lurker first time poster here. I'd really appreciate if some industry professionals could chime in to tell me what's happening at my workplace. I have 4+ years of experience in data analytics and business intelligence. I recently got a job at one of the Fortune 500 companies (in Europe), as a product data analyst. It pays quite decent. So far so good.

It's a pretty small SaaS product and I'm the only data analyst. I'm reporting to a product manager - not to the head of product, one of the 4 PMs. I'm his only IC. He is responsible of the in-product analytics module and coordinates the developers who do that. The devs do not report to my manager.

Few weeks into the job, I figured out that my manager does not want me to write any code to production at all. We're product and they're engineers. Engineers do that. I'm supposed to 'own' the dashboards, 'define' the business logic and 'suggest improvements'. I'll specify what the devs are supposed to do, then the devs are going to do that.

4 months into the job, I'm creating ETL orchestration improvement suggestions in Figma. I'm writing SQL and testing it in AWS, then delivering it to the devs also in Figma. Meanwhile my manager is absolutely refusing to do any sort of work management. No tickets, to project documentation, no scope, no deliverables - every trick in the book to avoid future accountability is in play. My only OKR is to address discrepancies in the in-product analytics module and all my suggestions (create a supported metrics list? rewrite the pipelines?) have been deprioritised - instead he's insisting that I address the symptoms, like "this number here and that number there should match and it should show the result of this query" for pretty much every single metric in the module. The work I'm creating in Figma is also never taken into devs' sprints and every week he's coming up with a requirement never heard before.

So the question is - what's happening here? Am I just naive to think that the data PM doesn't understand anything about how analysts and BI developers work? I don't think he's trying to get me to quit because the previous analyst has also quit after a few months - that should be detrimental for a new manager.

Financially and in terms of job prospects, I'm ready to walk away tomorrow but I'm genuinely curious what my manager is up to.

Hi all, I'm looking for some advice please. I own a SaaS company and one of our products has been set up in a not too desirable fashion from an architect perspective. I am absolutely not technical, so I have put all of the dev/ architecture in the hands of the developers. One of the lessons learned with the product in question is we didn't build it with multi tenancy in mind. Every customer has their own instance on a VPC.

The issue we face, is as we're growing- our customers now want BI visualisation and charts/ tiles. We already have all of the data - we just need to present it to them, in the product/ webapp directly, rather than exporting the data and letting them use it themselves (our go to market strategy for MVP).

My query isn't around visualisation and what metrics/ data points we should show our customers, but from the perspective of "how" to show them.

As I'm not technical I'm being led by our dev team who have little experience with B.I. I've asked them the question: "rather than building charts from scratch and deploying them to every customers instance, is there not a subscription service we can use, so a customer can essentially build their own charts on their own instance as, whilst every operation is similar, every customers reporting is different".

I know there's products like Qrvey, Bold BI, Tableau etc, but they seem more set up for businesses wanting to drill into their own data - rather than it being embedded into a SaaS product. (I could be wrong.) Due to the lack of multi-tenancy it would appear we'd need individual licenses for the industry named BI providers, which makes it inefficient and unaffordable.

Can anyone shine a light on any product or a clever way to do this? Appreciate I am not very technical, but just trying to understand it so I can have a conversation with the developers rather than leave it up to them to make the decision. I am also happy to be told that building it ourselves is the best way to go.

TIA.

I'm looing to join a specific motor vehicle manufacturing company. There isn't any BI architecture, so it would be all fresh scenario for me.

My question is what 10 dashboards do you think in general a motor vehicle manufacturing company would require.

Moreover, if things don't work out, I'll have something in my portfolio.

Looking forward for positive response.

After deciding to move away from Tableau, I started a POC with Looker but have encountered some concerns:

## Key Issues with Looker

1. Semantic Layer Lock-in - While LookML is powerful, having the semantic layer tied to the BI tool is limiting. I need semantic definitions to be accessible across our data stack (rETL processes, ML pipelines, SQL analysis)
2. Self-Service BI Reality - Research suggests true self-service BI is challenging to implement- Concerned about balancing user autonomy with proper data governance- Looking for practical experiences in managing these trade-offs
3. Visualization Limitations - Basic functionality gaps in table visualizations- For example: column nesting capabilities, multi-level header support.

## Alternative Options

I'm now considering two alternatives:

- Holistic

- Preset (Apache Superset)

Has anyone used either of these tools who can speak to how they handle semantic layer integration, their approach to self-service and governance and their visualization capabilities?

Would appreciate insights from those who have dealt with similar challenges

Hello everyone,

we are currently planning to switch from our existing BI tool to Power BI. In addition, our line manager is considering introducing IBM Cognos Analytics. The background to this is that many of our colleagues still like to work with large (pivot) tables and prefer to receive reports as PDFs by e-mail.

Do any of you have experience with IBM Cognos Analytics, especially in comparison to Power BI Report Builder? Where do you see the strengths and weaknesses of the two tools?

I am also interested to know if anyone uses IBM Cognos Analytics in the cloud version (especially Cognos Analytics on Cloud Hosted). My personal preference would be a pure cloud product - what are your experiences with it?

Thanks in advance!

What's the best way to track leads from a website to a phone call? This client I just started working with doesn't have any kind of shopping cart system- merely a call to action to call their office. I know that's not great, but- that's what we have to work with. I'm guessing I need to just setup a special tag in GTM and apply it to the call to action buttons so I can track conversion rates. Any other suggestions on how I can track/manage this data and get some good insights on the marketing we're starting to do?
Thanks!