3/ Power Query (yes, it's still Excel)
This is the real bridge to Power BI. Learn to clean, merge, and reshape data here first. Power Query in Excel and Power BI use the same engine master it once, use it everywhere.
2/ INDEX/MATCH (and XLOOKUP)
VLOOKUP breaks the moment your columns shift. INDEX/MATCH doesn't care about column order. Master this before DAX โ it's the same lookup logic, just a different syntax.
1/ Pivot Tables (properly)
Not just drag-and-drop. Learn calculated fields, grouping dates into quarters, and multi-level row groupings. If you can't summarize messy data fast in Excel, you'll build broken Power BI models later.
The mistake many aspiring analysts make is chasing every new tool while neglecting Excel.
Tools may get you noticed.
Excel gets the work done.
Master the fundamentals first. The advanced tools become much easier afterward.
If you judged the job market by reading job descriptions, you'd think every analyst spends their day using Power BI, Tableau, SQL, Python, and AI.
Reality is different.
Walk into most companies and you'll find one tool quietly running the business:
Microsoft Excel.
Why?
Because Excel is flexible, accessible, inexpensive, and almost everyone already knows how to use it.
Even organizations investing in modern BI platforms still depend on Excel for reconciliations, reporting, budgeting, forecasting, and ad hoc analysis.
A new milestone unlocked. ๐
I'm excited to share that I've earned the CCBAยฎ (Certification of Capability in Business Analysis) from
@IIBA.
This is another step in my journey to help organizations solve business problems through data, strategy, and technology.
@officialladi_T@iamjosephukpong Until you see DAX code on PowerBI that looks as if you are building an app.
When it comes to visualization drag and drop two weeks can make the person feel along.
Managing roles, building deploying and optimizing models.
Writing complex DAX comes with years of experience.