Upgrade to Power BI – Three key steps in the transition from Excel.
What is Power BI?
First things first. Microsoft’s Power BI is the market leading tool for BI analysis and visualisations. It’s a ‘one stop shop’ for data needs, with built-in AI and comprehensive integrations, to provide data insights in an intuitive, digestible way.
In many ways, Power BI is seen as the next step on from Excel, which has traditionally been the go-to solution for assembling, calculating and reporting on data. In fact, the vast majority of learners on our Data Analyst Power BI (Microsoft Cert) Apprenticeship programme, working towards becoming BI specialists or ‘Citizen Developers’, have some experience using Excel.
What skills do you need?
One of the top questions our clients and apprentices ask is ‘what skills will Excel users need to become comfortable with Power BI?’
The answer? A lot of the skills a Citizen Developer needs are transferrable, but you’ll want to enhance a few critical ones.
The key difference between Excel and Power BI is moving on from raw data to interactive dashboards and reports. This means you’re not just analysing but providing the tools for colleagues to interpret the data, too. Effectively, you’re translating data for other parts of your business to understand and use.
This comes with an additional set of steps and skills, which we’ll dive into below.
1. Getting Connected
Like any software, to get the most out of Power BI, you must provide it with an input of data; then it can do the rest.
Ask yourself these initial questions:
- What is the data required?
- How is it structured?
Once you have these answers, you can determine a suitable approach and the best queries to use.
Luckily, Power BI is smart enough to speak to a wide range of tools, which makes setting up your data connections as straightforward as can be.
2. Speaking the language
Power BI is truer to a real ‘database environment’ than Excel. It can format data to appear in a certain way, but this is primarily part of its reporting function.
To get data to behave as needed in Power BI, you’ll need to have greater understanding of data types and how to store them.
You’ll need to get to grips with Power BI’s Query Editor, and its language - known as ‘M’. This is the magic tool that will help you prepare data for analysis. You don’t have to be a total M pro, but you will need to interpret it effectively.
Now let’s talk about DAX. This powerful function-based language combines Excel’s function categories with an object-based approach, as used in the Power Pivot add-in.
Those who know Excel’s aggregate functions will have a good foundation, but DAX is a different animal. You’ll use it to write the Measures for your KPIs, create Date tables that represent your reporting year, and create ad-hoc data subsets for particular reporting requirements, so you’ll want to know it inside-out.
3. A picture is worth a thousand words
Data visualisations are about telling a story. This is where tools such as Power BI really shine, allowing us to grasp valuable insights at a glance.
Excel veterans will be familiar with a selection of columns, lines and pies. Graduating to Citizen Developer-ship, you’ll be introduced to a set of built-in interactions and filter capabilities. Visualisations now include maps, scatters, cards, slicers, tables, bookmarks, KPIs and AI visuals.
You will want to become friendly with all these visualisation types, as well as a new toolkit of features and design considerations to get the most out of Power BI. Once you do, you can move from simply visualising the data itself, to depicting the analysis of the data – painting a clearer picture of the insights your business needs.
Overall, there’s a natural progression from tools like Excel to becoming a Citizen Developer with Microsoft Power BI. Upskilling and learning new skills can empower you to harness the full impact of this industry leading software.
QA can help you take the next step in data analysis and visualisation with an Apprenticeship in Power BI. See the full range of our Apprenticeships in Data, Analytics and AI here.