This article is all about why every finance professional should learn Power BI, not just Excel, to provide the best service to their departments and look after the financial wellbeing of their companies.
Finance teams today are expected to do more than reconcile numbers, close the books and create financial statements. As a member of a Finance team, you’re the gatekeepers of the company’s finances; making sure that there’s enough cash to operate, ensuring that the right amount of money comes in and goes out, often tasked with getting payroll right, communicating with tax authorities, shareholders, auditors and other stakeholders. In some companies, even Sustainability reporting is coming the way of the Finance teams.
On top of all of those responsibilities, you’re also expected to provide insight, not just information, to help your business make smarter and faster decisions. Because you’re in a Finance team, you also know that what you say matters, and you’ll be expected to support your points of view. It’s just as well then that Finance team members are born with (or spontaneously sprout) the ‘data gene’. Those with the data gene can be easily identified as those that peer interestedly at a table of data to see what insight it holds. Those that don’t have the data gene may appear baffled by the same data table. You may even see recoiling in extreme cases.
But just because you know that tables of data can hold the key to a task and you wield a mean mouse in Excel, doesn’t mean that you’re getting the most of your capabilities. Excel has long been the trusted tool for financial analysis (well all analysis really!) but data is growing bigger, more complex and decision making more dynamic, and in some cases Excel really is no longer the best option, but Power BI is.
Every finance professional should learn Power BI to become more efficient, data driven, and more commercially minded. Speaking from experience, learning Power BI could be the most important investment you make in your career.
And the best thing? Because you’ve spent a hefty portion of your working life in Excel, it will likely be a walk in the park 👌
What is Power BI?
Power BI is Microsoft’s premier data visualisation tool and is the main reason why Microsoft has consistently been ranked as a leader in Gartner’s Magic Quadrant for Analytics and Business Intelligence Platforms for much of the last decade.
Not only can you build beautiful, insightful reports with Power BI, but thanks to Power BI’s capability to automate time consuming data cleaning tasks it can truly transform teams’ repetitive data work, making teams much more efficient, giving teams the ability to focus on tasks that truly add value.
Unlike Excel which is primarily a spreadsheet based analysis tool, Power BI is designed to handle large datasets (tens of thousands to hundreds of millions), automate data refreshes and create dynamic visual insights that anyone in a business can understand.
How does Power BI work?
Power BI works by connecting to your datasets almost wherever they are held. If your data is held in Excel files, databases like Access or Snowflake, ERP Systems or cloud platforms, Power BI can connect to it. You can connect to multiple datasets in different places, and Power BI will handle it, no bother. This happens in a stage of Power BI called Power Query.
Next you transform the data. This means that you remove columns and rows you don’t need, sort out errors, add in more columns you do need, merge datasets together (similar to VLOOKUPs and XLOOKUPs) and a whole host of other useful transformations. Once you’ve got your datasets in good shape then you send your data onto the data model. This also happens in Power Query.
In the Data Model, you join datasets together through relationships, then add in extra calculations either in columns or in measures, which is a fancy word for aggregations or totals at the bottom of columns of data.
Next, in the Report View, you create visualisations (graphs and charts) from the data in the Data Model. Finally you share your reports on Power BI Online so that anybody that you choose to share it with can look at your work.
And if all of that sounds fairly straightforward, that’s because many members of a Finance team will pick it up quickly as you’re already accustomed to following almost the same pattern in Excel. For example, grab a dataset in Excel and clean it as necessary. Next, use an XLOOKUP function to grab more information from another Excel spreadsheet because of course your first dataset doesn’t have everything you need. Attach that data to a pivot table and then create PivotCharts before sending the PivotChart full file off to someone for review.
So why learn Power BI, if you can already do the same thing in Excel?
How can Power BI help finance professionals?
However, in short, Power BI is a major time saver for finance teams because it automates what used to be manual Excel work:
- Automation through Power Query. We mentioned Power Query earlier as the method by which Power BI connects to and transforms data. Instead of cleaning data, and then copying and pasting the results into other datasets each day, week or month, Power Query lets you build a sequence of data transformation steps, simply by clicking buttons. It then remembers these steps, so that the next time you get an updated version of the dataset, it knows exactly what to do to transform it, without you needing to do anything. Suddenly, every time you need a dataset for a task, just show it to Power Query, click refresh and in seconds you’ll have the dataset ready to go.
- Handles larger datasets. Excel starts to struggle with larger files (the infamous row limit). In fact, it can struggle quite a long way before you get to its row limit of about 1 million rows. This is a problem for analysis with tools such as PivotTables (see below!) because PivotTables can only attach to a single dataset, not datasets spread over multiple worksheets. Power BI on the other hand is built with larger datasets in mind and can handle millions of rows without a problem.
- Build custom calculations in PivotTables. PivotTables are great as they are quick to put together, reliable and you can quickly change the data in them. However you can’t build complex calculations in them. For that you need to use functions, which require more knowledge, are easy to break and easier to unintentionally (or intentionally) manipulate. In Power BI, the charts we build are very similar to PivotTables but you can build custom calculations as well so that you have the best of both worlds.
There’s about 10 ways straightaway that Power BI can help out, and if you want to see a more complete list then check out this page here.
How Does Power BI Make Me More Commercially Minded?
Finance professionals who master Power BI become business partners, not just number crunchers. It’s very hard not to become more commercially minded once you’re using Power BI more. This is because:
- You can suddenly combine financial data with operational data such as sales, marketing, supply chain or any other kind of data almost instantly to create a complete picture of business performance. The dashboards that you create can be updated very fast and your reports will very quickly be relied upon.
- you’ll very quickly get into design conversations with business leaders as they ask questions of the dashboards you provide. Suddenly you’ll be viewed as someone who can get reliable answers to difficult business questions quickly
- when your data isn’t perfect, you’ll start to question why it’s not perfect, which will lead you into the business processes of data collection. This will help you get a much more granular understanding of different segments of the business as you start to go through different departments processes.
Can I earn more learning Power BI?
Yes it’s fairly likely that you will earn more knowing Power BI, particularly if you’re mixing it with another specialism, like accounting. Finance professionals with Power BI skills are in high demand. Think of it this way; I’ve never seen a finance job description without a requirement that you need to know ‘advanced Excel’. Well Power BI is a supercharged version, that in many cases, blows Excel out of the water. Whether you’re a financial analyst, FP&A manager or management accountant, Power BI is a skill that signals to employers that you’re analytically advanced and efficiency focused – two traits that every business values highly.
Whether you’re looking to advance in your current role or pivot into a lucrative field, Power BI is a powerful tool to elevate your career trajectory. Due to the way that Power BI can drive efficiencies and uncover business insights, those who can use Power BI can command a premium of between 10% to 20%, while experienced report developers can earn up to £100k in the UK.
How long does it take to learn Power BI?
You can learn the fundamentals of Power BI in less than a week if you really dedicate yourself to it and pick the right resources. Within a few months, most finance professionals can build automated dashboards and reports. If you pick the right resources, you should be up and running with report building sooner than that!
The key is learning in a structured way, and making sure that you know both:
– Power BI hard skills like data connection, data transformation, data combination, and DAX techniques but also…
– Power BI soft skills, including how to best structure your data, deal with common data issues, making a report work for your reviewer, solving refresh errors and so on
Once you’ve learned the fundamentals, then practice! The more practice you get, the faster you’ll get and the better that you’ll get, not only at building reports, but also spotting report building opportunities.
How can I learn Power BI?
Once you’ve decided to learn Power BI then you need to get the best plan for how to learn that fits your circumstances. There’s various options here, but to choose the right one for you, think about the resources you have available from the following: time, money and mental effort. If you’re working on your own you may want to go for a cheaper option, and be happy to swap some of your own time to learn. If you’re working for a company then you will likely be able to expense a course that you go on, but your company may want you to minimise time spent on learning.
- Option 1: Build your own structured course from free online content.
The main advantage here is that this is the most cost effective option as there probably is enough dotted around the internet for you to see all the skills to get a good grasp of Power BI.
The disadvantages are that you’ll first need to build your own structured syllabus, which, even with AI, can be quite tricky to get a good structure together. It will also be difficult to replicate the practice of building Power BI reports from start to finish as you’ll likely need to grab skills videos from different creators, which will use different datasets. This is also likely to be the slowest option and will require more mental effort to get your structure together. In addition, if you’re in a professional body where you need to prove Continuing Professional Development, you may find it hard to prove the work you’ve done. If you’re trying to train a group of people like a whole department, then ensuring that everyone has done the work or followed the same learning structure, again is difficult. - Option 2: Read some books on Power BI.
This is, probably the next cheapest option and will give you some structure to your learning. Otherwise, most of the disadvantages from Option 1 still apply. - Option 3: In person training course.
This is likely to be the most expensive option, with courses costing between around £600 to around £2,000 depending on the provider and duration, and whether they are performed online or face to face. An in person training course will generally last 2-3 days and these should give good learning structure, and should provide instant feedback if something doesn’t go right. You should also learn the fundamentals quickly as you’ll have time set aside to do the course. However, other than the cost, the main disadvantage is that you will go at the pace of the slowest person in the class and need to go with the lesson timetable, rather than what works for you. - Option 4: Pre recorded training courses.
These should be a good middle ground for each of the above as these tend to be cheaper than in person courses – between around £100 to £400 for good ones. At the same time you should still get a good structured training syllabus. You can still block out your diary to ensure that you complete the course so you’ll learn the fundamentals quickly but you can also go at your own pace. If something doesn’t quite go right, then you can just pause the video, and go back a step. Because the course is also not constrained by time limits, you’ll also likely get more practice, or be able to go deeper into Power BI knowledge.
What should I look for in a Power BI course?
Not all courses are created equal, so look for the following when choosing your course or books:
- Getting Power BI report building repetition is key to gaining Power BI proficiency. Look for a course that gives you lots of practice at writing reports. Almost every course will take you through completing one report from start to finish, but look for a course that will allow you to complete 3 or 4 reports. By completing more reports, you’ll understand more intuitively the Power BI report building process, you’ll get more opportunity to practice your skills and see a range of different datasets and different data problems. This will give you more confidence to create your own reports. when you finish the course.
- Real world finance examples. Some courses are quite generic in the data that’s used, so look for one where you build reports or solve problems that you’d likely see in your day job. For example, in our Finance team Power BI courses we cover a range scenarios, including supplier analysis, PO to invoice matching, payroll reconciliations and expense to budget analysis.
- Guidance on sharing and publishing reports securely. One of Power BI’s greatest strengths is its ability to publish data securely and share parts of, or all of a report based on a reviewer’s email address. This allows users to create reports even from sensitive data. You need to know how to use this functionality though, so make sure you choose a course that includes how to use Row Level Security.
- Find a course that shows you how to fix problems as they arise or avoid them altogether.
Problems and errors WILL come up and you’ll need to fix them in your Power BI reports. In real life, datasets are very rarely perfect. You don’t want to spend time creating a report, only to receive an error message when you update your report that you can’t fix quickly. The majority of courses don’t show you how to fix problems, preferring to pretend that nothing ever goes wrong. Things do go wrong, but most errors are quick to fix…if you know how!
We have a range of courses that fulfil all these criteria (and more!), and were designed by Alex Wilson, an ICAEW member, Head of Financial Reporting who has 8 years’ experience on Power BI and 6 years’ Power BI teaching experience.
Will Power BI really save me time?
Definitely. And then once you’ve saved time on the jobs you already do, you’ll then be able to tackle tasks that you thought were out of reach because in Excel they just weren’t feasible.
Let’s say you spend 18-20 hours doing a really good Power BI course and then you spend another 8-10 hours building your first report. That report then only needs to save you 35 minutes a week and you’ve already earned all that time back. Any report you build after that just needs to cover the amount of time you spent building it!
Sometimes, though you need to just get some inspiration for the kind of things you could do, so here are a range of Power BI reports that I’ve seen and the amount of time saved:
- Company Wide function – Group expense vs budget reporting – a report analysing actual costs vs budget, reforecast and prior year. This report saved around 15 days of finance department time every period end vs the previous Excel reporting strategy, or about 140 days in the first year of publication and 180 days each year after that. The previous budgetary reporting by Excel was inconsistent across multiple sites and could only be carried out once a month because it wasn’t feasible to carry it out more frequently. The Power BI report refreshes automatically multiple times a day with no human intervention, but all powered from Excel spreadsheets.
- Finance team wide function – Month End Invoicing Journals Creator – a Power BI report to create invoice generating journals from Excel data dumps. Once in service, the report saved 2-4 days of manual work each month end, brought certainty to the month end timetable, cut month end close by 2-4 days, provided required analytics to a third party as well as internally and saved the need to purchase a third party system.
- Individual employee – Prepayment journal and reconciliation tool – once invoices required for prepayments have been identified, running from an invoice listing, this tool created a number of different types of journals automatically for posting to an accounting system and generated a balance sheet reconciliation template. Brought a 4-6 hour process to approximately 1.5 hours.
Why should I use Power BI now that AI exists?
You should still learn Power BI even in the age of AI, because AI only strengthens the argument to use Power BI. Here’s why:
LLM models have limited resources. If you’re wanting to get insights straight from AI, simply by showing it some files of data and asking AI some questions, then you’re asking AI to do Power BI’s job as well as give you insights. Some Power BI files have tens to hundreds of gigabytes of information. Power BI cleans the data, connects data together and adds in calculations that you don’t have. This is called creating a ‘semantic model’. Even something as powerful as AI will not be able to do that reliably (if it can do it at all) and then give you insights that you can trust on the fly. A much better option is to create your semantic model in Power BI and then ask your LLM to look at the Power BI created semantic model to derive insights. Power BI is still the best way for consistently extracting, connecting and organising data. This means that you then use AI’s resources to focus on deriving the insights, rather than creating the semantic model.
There are also a number of other considerations as well which we’ll get into in future articles but include future tech strategy risk, sustainability, reliability, auditing output and others.
Ready to get started?
A free 1 hour course to find out more about the different parts of Power BI, see a finished report up close in the flesh (on the screen) and understand how it’s put together. By the end of the course you’ll have enough to go off and start experimenting with Power BI yourself.
This 7 hour course that builds on Introduction to Power BI by teaching the basic elements of Power BI and then guiding you through creating a beginner report. You’ll then be guided through a second more complex report to get started on your Power BI Journey.
A complete 18 hour course building on Getting Started With Power BI that teaches the basics of Power BI and then guides you through the creation of 4 varied reports ranging from beginner to advanced, combining Power BI theory with report writing and error fixing practice
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