Power BI End to End Project - Step by Step Data Validation in Tamil

✅ Power BI Dashboard Validation – Step-by-Step Guide for Accurate Reports

Your Power BI dashboard is finally complete 🎉
You’ve designed visuals, aligned elements, and built all KPIs.

But before publishing… there is one critical step you should never skip:

👉 Validation

In this blog, we’ll walk through a real-world validation approach to ensure your Power BI dashboard is 100% accurate and business-ready.

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🎯 What We Completed Before Validation

Before starting validation, let’s quickly recap the improvements made to the dashboard:

📌 Proper alignment of cards and visuals
📌 Consistent theme applied across pages
📌 Clean and professional naming conventions
📌 Icons added for better UI experience
📌 Unnecessary test measures removed

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📊 Adding Metric Definitions (Best Practice)

One important addition is a Metric Definition Table.

👉 This includes:

• Metric Name

• Business Meaning

• Calculation Logic

💡 Why this is important?

👉 Business users can understand:

• What each KPI represents

• How it is calculated

👉 If any mismatch is found, they can immediately inform you.

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🔥 Key KPIs to Validate

Focus on these 4 critical KPIs first:

✔ Total Sales
✔ Total Orders
✔ Total Customers
✔ Total Quantity

💡 If these match correctly →
👉 You can be 90% confident your dashboard is accurate.

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📅 Validation Levels You Must Check

Validation should not be done only at overall level ❌

You must validate across:

📊 Overall total
📆 Day-wise
📅 Month-wise
📈 Week-wise (optional)
📉 Year/Quarter (if needed)

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🛠️ Step 1: Create Validation Table in Power BI

Instead of manually checking each value, we can simplify using:

👉 Field Parameters

Create 2 Parameters:

📌 Metric Parameter:

• Total Sales

• Orders

• Quantity

• Customers

📌 Period Parameter:

• Date

• Month

• Year

• Week

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Create a Table Visual

Add:

👉 Metric Parameter
👉 Period Parameter
👉 Measure Values

Now you can dynamically switch:

✔ KPI
✔ Time Period

💡 This makes validation fast and scalable

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📤 Step 2: Export Data from Power BI

Once your table is ready:

👉 Export the data to Excel

This will act as your Power BI output reference

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🧮 Step 3: Get Data from SQL Server

Now create a query in your SQL source to calculate:

✔ Total Sales
✔ Total Orders
✔ Total Quantity
✔ Total Customers

👉 Group by:

• Date

• Month

• Week

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📊 Step 4: Compare in Excel

Maintain an Excel sheet like this:

Metric	Period	SQL Value	Power BI Value	Delta

👉 Compare both values
👉 Calculate the difference (Delta)

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🚨 Important Validation Tips

✔ Start with Month-level validation
👉 If month matches → day-level will mostly match

✔ If mismatch found:
👉 Drill down to day level and debug

✔ Always validate:

• Row counts

• Distinct counts

• Aggregations

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📁 Final Output – Validation Document

Once everything matches:

👉 Save your Excel as a Validation Document

You can:
✔ Share with stakeholders
✔ Use it during deployment
✔ Keep it for future audits

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⚠️ Without Validation = Risk

Skipping validation can lead to:

❌ Wrong business decisions
❌ Loss of trust
❌ Rework after deployment

👉 That’s why validation is mandatory in real-time projects

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🚀 What’s Next?

Once validation is completed:

👉 You are ready to publish your dashboard

But wait… ⚠️
There’s an important step while publishing that many people miss.

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🎬 Learn More

Want to see this entire validation process in action step-by-step?

👉 Watch the full video here and follow along: