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Sania-F

snapshot calculation

Snapshot is super important in reporting, especially for things like inventory, headcount, or account balances.


🔹 What is a Snapshot?

A snapshot is the value of something at a specific point in time (usually the last day of the month, week, or quarter).
It’s not cumulative and it’s not meant to be summed across days.

👉 Example:

  • If you check your bank balance every day for 10 days:

    • Day 1 = ₹5,000

    • Day 2 = ₹7,000

    • Day 3 = ₹6,500

  • Your "balance" is just one number each day.

  • If you summed them → ₹18,500 (nonsense!).

  • If you take the snapshot on Day 3 → ₹6,500 (correct).


🔹 Snapshot Calculations in Power BI

They are measures where you want to show the state as of the last date in a period, not the sum of all rows.

Typical examples:

  • Inventory Stock on Hand (as of the last date of the month)

  • Employee Headcount (number of employees at month end)

  • Bank Account Balance (balance on last day)


🔹 Why are special DAX patterns needed?

Because in Power BI:

  • By default, dragging a column into Values → SUMs across all rows.

  • For snapshots, that inflates results.

So we use patterns like:

Stock on Hand =
CALCULATE (
    SUM ( Inventory[UnitsBalance] ),
    LASTNONBLANK ( 'Date'[Date], SUM ( Inventory[UnitsBalance] ) )
)

or

Stock on Hand =
CALCULATE (
    SUM ( Inventory[UnitsBalance] ),
    FILTER (
        ALL ( 'Date'[Date] ),
        'Date'[Date] = MAX ( 'Date'[Date] )
    )
)

Both force Power BI to take the balance on the last available date, instead of summing all dates.


In short:
Snapshot calculation = state at a point in time (last date).
Transactional calculation = sum over time (sales, revenue, etc.)

Comments

Hi @Sania-F,

 

The explanation is clear and informative, making it much easier to understand both the concept and the practical application of snapshot calculations. Posts like this are valuable for the community and will help others with similar questions.

Thank you for taking the time to explain it so thoroughly!