Why Business Analysts Need to Learn Power BI
So, you’ve decided you’re interested in working as a business analyst or a data analyst.
That’s a wise decision, given the massive and ever-growing mountain of data companies are collecting. At almost every company, even outside of data-specific roles, there’s a drive to be more data-driven and find signals in the noise that can give the company a competitive advantage. There is great (and still growing) demand for analysts, and as a result, it’s a career that pays well and offers good prospects for future career advancement.
What do business analysts really need to know?
But once you’ve decided you’re interested in data analysis, you’re confronted with a difficult question: what do I need to learn?
Having a solid grasp of statistics is important, of course, as are a variety of “soft” skills such as communication and collaboration. The sticking point for most aspiring business and data analysts are the technical skills, though.
If you Google for advice or start browsing job listings, you’ll quickly be confronted with a wide variety of programming languages, technologies, and tools. Excel, Power BI, Python, R, SQL, SAS, SAP, Postgres, MySQL, Oracle… the list goes on. It can be confusing to try to figure out what you really need to know.
While specific companies may require specific software knowledge or tools, at its core the job of a business analyst or data analyst is to:
- Acquire data relevant to the analysis from sources such as databases, Excel files, CSV files, etc.
- Clean and join the data as needed to prepare it for analysis
- Conduct the analysis
- Organize, design, and present the results of the analysis
At the end of the day, a business analyst needs the technical skills to accomplish those tasks, but there’s no one single way to get there.
You could learn SQL (for acquiring and transforming data) and Python (for analysis and presentation). Python is a versatile programming language that’s used in lots of contexts, so it’s a valuable skill to have, but like any programming language, it takes some time and dedication to learn.
You could learn SQL (for acquiring and transforming data) and R (for analysis and presentation). R is a programming language that’s built for working with and visualizing data, so it’s a great fit, although like Python it does take some time to learn.
You could simply learn Excel. This might make ingesting data from some sources difficult, and it would limit the kinds of advanced analyses you can do as well as the size of the datasets you could work with, but there are roles where Excel/spreadsheet skills are really all that’s required.
You could simply learn Power BI. Power BI can work with massive datasets, it can ingest data from a variety of sources, including SQL databases, and it’s built for easy visualization to facilitate the creation of reports and dashboards.
All of these approaches are reasonable, and the reality is that if you’re working in the data analysis field for long enough, you’re likely going to pick up quite a few of these skills.
But which one should you start with? There’s a strong case to be made that you should start by learning Microsoft Power BI. Let’s take a closer look at why.
The most important tenet of all data analysis work
To understand why business analysts should learn Microsoft Power BI, it helps to keep the most fundamental tenet of data analysis work in mind: analysis is only as valuable as it is understandable and actionable.
Aspiring and even experienced business analysts can sometimes focus too much on the process of analysis, applying interesting statistical methods or writing complex formulas to dig into new areas. But ultimately, the best analysis in the world isn’t worth anything if it fails to convince a company’s decision makers to act on it.
For decision makers to act on the results of your analysis, they need to be able to access it easily, and they need to be able to understand it clearly.
With that in mind, let’s look at five reasons data analysts should learn Power BI.
Why learn Power BI?
1. It does everything
Power BI is an end-to-end data analysis tool. Let’s look back at the steps that form the core of data analysis work, as discussed earlier in this article:
Acquire data relevant to the analysis from sources such as databases, Excel files, CSV files, etc.
Clean and join the data as needed to prepare it for analysis
Conduct the analysis
Organize, design, and present the results of the analysis
Microsoft Power BI does all of those things. It can be, for many analyses, a one-stop shop:
It can ingest data from a wide variety of sources, including SQL databases, CSV files, Excel files, and many more.
It includes intuitive tools for cleaning data, establishing relationships between data, computing new columns and other measures from the data, etc.
An intuitive but very powerful drag-and-drop visualization builder makes creating detailed visuals surprisingly straightforward and very quick, enabling you to look at your data in a wide variety of ways and identify patterns.
Those same visualization tools come with built-in features for creating and sharing reports and dashboards, including mobile-friendly dashboards, so that everyone can see your results as well as any annotations and explanations you’ve added.
Of course, programming languages like Python or R can do all of the above as well – in fact, they can do nearly anything! However, working through that process in Python, for example, does tend to be more time consuming, particularly when it comes to the visualization. Even a Python wizard could not create an interactive histogram (or any other chart) as quickly as it can be done in Power BI.
2. It’s an in-demand skill
Ultimately, if your goal is to get a job as a business analyst, that means you need to be able to do the job, but it also means you need to get hired to do the job. Not having the right keywords in your skills can get your application tossed before it’s ever even seen by a human.
Thankfully, Microsoft Power BI is both well-known and well-liked, and it’s a keyword that appears in a lot of job postings. As of this writing, there are nearly 20,000 open jobs on Indeed.com in the US alone that list “Power BI” as a required or desired skill.
Why is Power BI so in demand? Aside from the broader industry trend that makes any kind of data analysis skill desirable, there’s another reason companies love to see Power BI on a resume…
3. It integrates well with the tools many businesses already use
Microsoft’s suite of tools, from the basics like Word and Excel to its cloud computing offerings, are already in use at a huge number of companies. Four out of five Fortune 500 companies use the Office 365 suite of applications, for example.
And for any company that does use Microsoft products in other areas of its corporate life, doing analysis with Power BI makes sense because Power BI is built to integrate smoothly with many of those products, For example, Power BI can be integrated directly with the Office 365 applications, and with Microsoft Teams. It also has deep integration with Excel, even allowing the use of some Power BI features from within Excel.
From a corporate perspective, having your analysts work with Power BI makes life easier if you’re already a Microsoft shop. You know that other team members will be able to (for example) access reports from Teams, and pull data into Excel for their own use when it’s needed.
And it’s not just Microsoft shops that like Power BI, either. Power BI also includes integrations with popular tools such as Salesforce and Zendesk that are in use at tons of companies even outside of the Microsoft ecosystem, and having analytics that can easily plug into those tools can be a massive time-saver and make the data more useful since team members can find and work with it in the software they’re already familiar with.
4. It’s easy to share reports
Power BI is capable of performing some impressive analyses, but it’s also a presentation tool that’s built for sharing those analyses. That’s critical for business analysts who aspire to make an impact with their work.
In Power BI, you build visualizations on pages, with intuitive tools that allow you to do things like highlight specific data points or add annotations and explanations. When you’re ready, you can share specific pages, or the entire report, with stakeholders by publishing it using the Power BI service. There, you can easily build dashboards using your visualizations that will update in real-time when new data is ingested, and you can even build “apps” – curated, shareable, interactive reports.
Power BI even makes accessibility easy with things like specific color schemes to ensure charts are readable even for team members who are colorblind, and mobile-specific design options so that you can tune the way your reports and dashboards appear to fit mobile devices.
All of this is accessible via intuitive menus and drag-and-drop interfaces, without any coding required. Because Power BI makes sharing data so straightforward, it makes it more likely that your work _wil_l be shared – and that’s good for you and for the company.
5. Visuals matter
Finally, we return to that critical tenet of data analysis work: analysis is only as valuable as it is understandable and actionable. So while it would be nice to say that good analysis will always be valued, in a corporate setting, that simply isn’t the case.
Good analysis can still be too complex for non analysts to understand. Or, it can just be unattractive and lose its audience’s interest before they’ve absorbed the information. That’s why being able to create attractive, easy-to-understand visualizations is critical to the work of a business analyst. Without them, your work is far more likely to be misunderstood or ignored.
Power BI’s drag-and-drop interface for creating visualizations is intuitive and deep enough that it’s possible to customize the appearance of nearly every aspect of every chart in your report to ensure the message gets through.
A wide variety of other tools are capable of creating attractive data visualizations too, of course. But few if any of them make it as fast or as straightforward as Power BI. When you don’t have to spend time working on code just to get the basic data points you want to appear on a chart, you have more time to spend making it look just right. And that, in turn, could be the difference between convincing your company to act on the data you found or not.
In the end, these are just a few examples – there are lots of reasons that aspiring data analysts should learn Power BI. Ready to take the plunge? Start learning Power BI right now, from right inside your web browser.