Marg Analytics

Want more PivotTable practice?

I created a PivotTables Practice Pack with 5 real business scenarios.

Inside, you’ll get:

✅ Excel datasets
✅ Guided tasks
✅ Solution walkthrough videos
✅ Practice scenarios covering sales, expenses, support tickets, inventory, and management reporting

This is for learners who already know the basics, but want more hands-on practice using PivotTables to answer business questions.

Find the full practice pack here: www.marg-analytics.com/product-page/pivottables-pr…

#excel #pivottable #marganalytics

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2 months ago | [YT] | 2

Marg Analytics

PivotTables can feel confusing when you only watch random tutorials.

So I created a beginner-friendly PivotTables tutorial series to help you build the foundation step by step.

In this series, you’ll learn how to:
✅ Create your first PivotTable
✅ Change default calculations
✅ Sort, filter, group, and use slicers
✅ Work with multiple fields
✅ Create a PivotChart
✅ Try a final challenge to test your understanding

There’s also a free practice file so you can follow along instead of just watching.

Start with the series in my profile under **PivotTable Series**.

#excel #pivottables #marganalytics

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2 months ago | [YT] | 2

Marg Analytics

One-cell solutions look impressive.
But they often come with a hidden cost.

When all the logic lives inside one long formula:
▪️ Harder to read
▪️ Harder to debug
▪️ Harder for others to maintain
▪️ Harder for future you to understand or change later

In real work, Excel files don’t live in isolation.
They get reused, shared, handed over, and revisited months later.

A solution isn’t good just because it works today.
It’s good if someone else can understand it tomorrow.

Sometimes the better choice is:
🔸 Breaking logic into steps
🔸 Using helper columns
🔸 Choosing clarity over cleverness

That’s not “less advanced.”
That’s building Excel files that last.

#Excel #MargAnalytics

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3 months ago | [YT] | 1

Marg Analytics

One of the most frustrating moments in Excel is this:
Your formula is correct.
There’s no error.
But the result is wrong.

In many cases, the problem isn’t the formula —
it’s the data.

Some common reasons this happens:
▪️ Numbers stored as text.
▪️ Hidden spaces or invisible characters.
▪️ Filtered or hidden rows or columns.
▪️ Mismatched formats (dates, text vs numbers).
▪️ Duplicated lookup keys.
▪️ Assumptions about the data that aren’t actually true.

Excel usually does exactly what we tell it to do.
The issue is often what we’re telling it, based on how the data looks — not how it really is.

That’s why debugging in Excel isn’t just about checking formulas.
It’s about checking:
🔸 The structure
🔸 The data type
🔸 And the context around the calculation
When the formula is right, results feel wrong, slow down and question the data.

#Excel #MargAnalytics

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3 months ago | [YT] | 0

Marg Analytics

Somewhere along the way, helper columns got a bad reputation.
People think:
▪️ “If I use helper columns, I’m not advanced.”
▪️ “A real Excel solution should be one formula.”
▪️ “Cleaner sheet = fewer columns.”


In real work, it’s often the opposite.
Helper columns:
🔸 make logic visible
🔸 make formulas shorter
🔸 make errors easier to spot
🔸 make files easier for others to maintain


A single complex formula might look impressive —
but if only one person understands it, the file is fragile.


Good Excel work isn’t about hiding logic.
It’s about making logic obvious.


If a helper column makes the file clearer,
that’s not beginner Excel,
that’s professional Excel.

#Excel #MargAnalytics

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3 months ago | [YT] | 0

Marg Analytics

XLOOKUP is powerful.
But it’s not always the right choice.

Sometimes people reach for XLOOKUP by default — even when the problem isn’t a lookup problem.

Here are a few situations when XLOOKUP is not suitable:
🔸 When aggregation is needed
(sum, count, average by category → PivotTables, SUMIFS, or Power Query are clearer)
🔸 When there are multiple valid matches
(XLOOKUP quietly returns the first match — which can be misleading)
🔸 When the logic starts getting complex
(helper columns or a structured approach is easier to debug and maintain)

XLOOKUP is a great tool.
But using it everywhere doesn’t make a solution better — just harder to reason about.

Good Excel isn’t about using the “best” function.
It’s about using the right approach for the problem.

#Excel #MargAnalytics

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3 months ago | [YT] | 0

Marg Analytics

𝐋𝐞𝐭’𝐬 𝐫𝐞𝐬𝐞𝐭 𝐭𝐡𝐞 𝐰𝐚𝐲 𝐰𝐞 𝐭𝐡𝐢𝐧𝐤 𝐚𝐛𝐨𝐮𝐭 𝐄𝐱𝐜𝐞𝐥.

Being good at Excel is not about memorising more functions.
It’s not about knowing the newest formula first.
And it’s definitely not about squeezing everything into one clever cell.

Real Excel skill is about:
🔸 understanding the data
🔸 choosing the right approach
🔸 building something others can read, trust, and maintain

Two people can solve the same problem:
🔸 one with a flashy one-cell formula
🔸 one with a clear, structured setup
The second one usually survives longer in real work.

This week, I want to share less “how to click”
and more “how to think” when working with Excel.
If you’ve ever felt:
🔸 overwhelmed by “advanced” Excel
🔸 unsure why something works but feels wrong
🔸 pressured to be clever instead of clear
You’re not alone.
Let’s reset the frame.

#Excel #MargAnalytics

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3 months ago | [YT] | 1

Marg Analytics

𝐏𝐨𝐰𝐞𝐫 𝐐𝐮𝐞𝐫𝐲 𝐈𝐬𝐧’𝐭 𝐀𝐥𝐰𝐚𝐲𝐬 𝐭𝐡𝐞 𝐀𝐧𝐬𝐰𝐞𝐫 — 𝐀𝐧𝐝 𝐓𝐡𝐚𝐭’𝐬 𝐎𝐊

Power Query is amazing, but it shines best when: ✔ your data refreshes
✔ the cleaning steps repeat
✔ files come from systems or folders

It’s not ideal for:
✖ one-off fixes
✖ tiny datasets
✖ quick manual changes

The key idea:
👉 Power Query is for processes, not quick fixes.

Knowing when not to use it is a skill too.

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4 months ago | [YT] | 1

Marg Analytics

𝐃𝐚𝐭𝐚 𝐈𝐬𝐧’𝐭 𝐉𝐮𝐬𝐭 𝐀𝐛𝐨𝐮𝐭 𝐂𝐥𝐞𝐚𝐧𝐢𝐧𝐠 — 𝐈𝐭 𝐒𝐭𝐚𝐫𝐭𝐬 𝐖𝐢𝐭𝐡 𝐇𝐨𝐰 𝐖𝐞 𝐂𝐨𝐥𝐥𝐞𝐜𝐭 𝐈𝐭

People talk a lot about data cleaning.
But from my experience, 𝐝𝐚𝐭𝐚 𝐜𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐦𝐚𝐭𝐭𝐞𝐫𝐬 even more.

How data is collected shapes the entire quality of the dataset.
If the collection process is poor, analysts end up spending hours fixing issues that could have been prevented upstream.
And even with strong cleaning techniques, some inaccuracies can never be fully recovered.

One thing I think is often misunderstood is where responsibility sits.

We can’t simply “push” it to the frontline.
Their priority is serving customers, resolving issues, and hitting operational KPIs.
Expecting them to double-check every field, follow strict formats, and maintain perfect accuracy:
▪️ increases workload
▪️ pulls focus away from their core role
▪️ and still doesn’t guarantee good data

From my experience, the real solution isn’t asking people to be more careful — it’s 𝐝𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐛𝐞𝐭𝐭𝐞𝐫 𝐬𝐲𝐬𝐭𝐞𝐦𝐬.

Things like:
▪️ automatic data capture
▪️ dropdowns instead of free typing
▪️ built-in validations
▪️ auto-calculated fields
▪️ fewer manual handoffs through system integrations
▪️ clear SOPs with simple UX

When systems are designed well, good data becomes a natural byproduct, not an extra burden.
High-quality data doesn’t start in Power Query or other data analytics tools.
It starts at the moment data is collected — and the system should make that process as effortless as possible.

If you’re in analytics or frontline, I’d love to hear your thoughts: How does your team ensure accurate data collection without overwhelming the team?

4 months ago | [YT] | 1

Marg Analytics

Quick Excel Tip — 𝐒𝐭𝐫𝐢𝐤𝐞𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐢𝐧 𝐎𝐧𝐞 𝐊𝐞𝐲𝐩𝐫𝐞𝐬𝐬


Need to mark something as Done or Completed?


You don’t need to open Format Cells.
Just press:
➡️ Ctrl + 5 (Windows)
𝐈𝐧𝐬𝐭𝐚𝐧𝐭 𝐬𝐭𝐫𝐢𝐤𝐞𝐭𝐡𝐫𝐨𝐮𝐠𝐡.


Perfect for checklists and quick notes inside Excel.

#excel #exceltips #excelshortcut #marganalytics

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4 months ago | [YT] | 1