7 Power BI Dashboard Mistakes That Make Your Data Useless

The Dashboard That Looked Amazing and Did Nothing

A client came to me with a Power BI dashboard their previous developer had built. It had 14 pages, 80+ visuals, animated backgrounds, and a colour palette that would make a graphic designer proud. It also had zero impact on any decision the business made.

When I asked the CFO which visual she used most, she said: "Honestly, I just export the data to Excel and build my own table." The dashboard had every chart type Power BI offers. It had none of the answers she needed.

This is the most common Power BI failure pattern. Here are the 7 specific mistakes that cause it.

Mistake 1 — Building Before Defining the Questions

The most damaging mistake happens before you open Power BI Desktop. Building a dashboard without first defining what decisions it needs to enable.

Before touching your data, sit with every stakeholder and ask: "What decision do you make weekly that would be better with better information?" Write down the specific questions. Every visual on the dashboard should directly answer one of those questions. If you can't name the decision a visual enables, delete it.

Mistake 2 — A Broken Data Model

Power BI is built on a column-store database engine. If your data model is wrong, every DAX measure you write will either be slow, incorrect, or both. The most common data model mistakes are: flat tables instead of a star schema, bidirectional relationships everywhere, and calculated columns doing what measures should do.

The correct structure is always a star schema: one or more fact tables (sales, expenses, orders) connected to dimension tables (dates, customers, products, accounts) with single-directional relationships.

-- Fact Tables (many rows, measures)
fact_Sales        [date_key, customer_key, product_key, revenue, cost]
fact_Expenses     [date_key, account_key, amount, category]

-- Dimension Tables (fewer rows, filters)
dim_Date          [date_key, year, month, quarter, week]
dim_Customer      [customer_key, name, segment, region]
dim_Product       [product_key, name, category, price]
dim_Account       [account_key, name, type, department]

-- Relationships: always one-to-many, single direction
dim_Date → fact_Sales        (1:*)
dim_Customer → fact_Sales    (1:*)

Mistake 3 — KPIs Without Targets

Showing a revenue number of £482,000 means nothing in isolation. Is that good? Bad? On track? Without a target, a benchmark, or a prior period comparison, a number is just a number.

Every KPI card on your dashboard should show: the current value, the target or budget, the variance (actual minus target), and the trend direction. A green/red RAG status is acceptable only if the threshold logic is clearly defined and agreed with stakeholders.

Mistake 4 — Wrong Chart for the Wrong Data

Power BI offers 30+ visual types. Most should be used rarely or never. The chart type must match the analytical question being asked:

• Trend over time → Line chart. Not a bar chart, not a scatter plot.
• Part-to-whole composition → Stacked bar or treemap. Not a pie chart with 8 slices.
• Comparing categories → Horizontal bar chart (sorted descending). Not a clustered column chart with 12 groups.
• Single KPI vs target → Card visual with conditional formatting, or a gauge. Not a line chart.
• Correlation between two measures → Scatter plot. Not a dual-axis line chart.

Mistake 5 — Overloaded Pages

I see dashboards with 20+ visuals on a single page. The human brain cannot process 20 charts simultaneously. When everything is highlighted, nothing is highlighted.

The rule is maximum 5–7 visuals per page for an executive dashboard, maximum 10–12 for an analytical drill-down page. If you have more to show, add a page — don't shrink the visuals until they're unreadable on a laptop screen.

Mistake 6 — Ignoring Mobile Layout

If any of your dashboard users view reports on a phone or tablet — and in 2025, most executives do — and you haven't configured the mobile layout in Power BI, they are seeing a zoomed-out version of your desktop report that requires pinching, scrolling, and squinting.

Power BI's mobile layout is a separate canvas you configure in View → Mobile Layout. Every report that will be used on mobile needs this configured separately.

Mistake 7 — DAX Measures That Lie

This is the most technically dangerous mistake. DAX is a powerful language, but it's also counterintuitive — particularly around filter context and time intelligence. The most common DAX errors I audit in client files:

1. CALCULATE with the wrong filter — removing filters you intended to keep
2. Time intelligence on a non-marked date table — TOTALYTD and SAMEPERIODLASTYEAR silently produce wrong results if your date table isn't marked as a date table
3. Dividing without handling blanks — a measure that returns BLANK() instead of 0 will corrupt totals in matrix visuals

-- Wrong: returns BLANK() when denominator is 0
Gross Margin % = DIVIDE([Gross Profit], [Revenue])

-- Correct: returns 0 when denominator is 0
Gross Margin % =
DIVIDE(
    [Gross Profit],
    [Revenue],
    0   -- alternateResult: returned when denominator = 0
)

-- Also correct: explicit BLANK() trap
Gross Margin % =
IF(
    [Revenue] = 0,
    BLANK(),
    DIVIDE([Gross Profit], [Revenue])
)