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🔍 Performance Bottleneck Analysis

• Repeated use of SUMMARIZE + MAX + SUMX: Very costly with large datasets.
• ALLSELECTED inside complex FILTER: Can slow down visuals drastically with slicers.
• Chained Measures: Each reference adds evaluation overhead.

✅ Optimized Strategy

Step 1: Cache with Variables

DAX
ODM Količina kumulativno po odpoklicu :=
VAR CurrentID = SELECTEDVALUE('f ODM Odpoklici_MES'[ODM Odpoklic_ID])
VAR CurrentDate = MAX('f ODM Odpoklici_MES'[ODM Datum_odpoklica])

VAR BaseTable =
    ADDCOLUMNS(
        FILTER(
            'f ODM Odpoklici_MES',
            'f ODM Odpoklici_MES'[ODM Odpoklic_ID] = CurrentID &&
            'f ODM Odpoklici_MES'[ODM Datum_odpoklica] <= CurrentDate
        ),
        "Enkratna_Kolicina", 'f ODM Odpoklici_MES'[ODM Kolicina_po_odpoklicu]
    )

RETURN SUMX(BaseTable, [Enkratna_Kolicina])

Step 2: Use TOPN for Last Known State

DAX
ODM Barvanje Trajno1 :=
VAR CurrentDate = MAX('d CAS Cas'[CAS Datum])

VAR FilteredTable =
    CALCULATETABLE(
        ADDCOLUMNS(
            VALUES('d CAS Cas'[CAS Datum]),
            "Stanje", [ODM Barvanje Base]
        ),
        'd CAS Cas'[CAS Datum] <= CurrentDate,
        NOT ISBLANK([ODM Barvanje Base])
    )

VAR LatestState =
    TOPN(1, FilteredTable, 'd CAS Cas'[CAS Datum], DESC)

RETURN MAXX(LatestState, [Stanje])

Step 3: Profile Measures with DAX Studio

• Open your PBIX in DAX Studio.
• Enable Server Timings and Query Plan.
• Identify high-cardinality steps and expensive scans.

Step 4: Pre-Aggregate Data

DAX
SummaryTable =
SUMMARIZE(
    'f ODM Odpoklici_MES',
    'f ODM Odpoklici_MES'[ODM Odpoklic_ID],
    "MaxKolicina", MAX('f ODM Odpoklici_MES'[ODM Kolicina_po_odpoklicu]),
    "ZalogaKoncnih", MAX('f ODM Odpoklici_MES'[ODM Zaloga_koncnih_kosov])
)

📌 Next Steps

• Test one optimized measure in a visual.
• Use Performance Analyzer in Power BI to confirm speedup.
• Share row count of f ODM Odpoklici_MES and number of visuals on page if issue persists.