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🖨️ Paginated Reports - Pixel-Perfect Enterprise Reporting¶

Last Updated: 2026-04-21 | Version: 1.0.0

📑 Table of Contents¶

• 🎯 Overview
• 🏗️ Architecture
• ⚙️ Authoring with Report Builder
• 🔌 Data Sources in Fabric
• 📐 Parameters and Subreports
• 📤 Export Formats and Subscriptions
• 🎰 Casino Implementation
• 🏛️ Federal Agency Implementation
• 🔐 Security and RLS
• ⚠️ Limitations
• 📚 References
• 🔗 Related Documents

🎯 Overview¶

Paginated Reports in Microsoft Fabric deliver pixel-perfect, print-optimized reports designed for scenarios where precise layout control, multi-page rendering, and regulatory-compliant formatting are non-negotiable. Unlike interactive Power BI reports that are designed for on-screen exploration, paginated reports are designed for printing and export — every header, footer, page break, and table cell renders exactly where the author placed it.

Why Paginated Reports Matter¶

Interactive Power BI dashboards excel at exploration but fall short when the output must match a regulatory form, print on letter-size paper, or render a 500-page transaction listing. Paginated reports fill this gap.

Key Capabilities¶

Paginated vs Interactive Reports¶

🏗️ Architecture¶

How Paginated Reports Work in Fabric¶

flowchart TB
    subgraph Authoring["✏️ Authoring"]
        RB["Power BI<br/>Report Builder"]
        RDL["RDL File<br/>(.rdl)"]
    end

    subgraph Fabric["🟣 Microsoft Fabric"]
        WS["Workspace"]
        SM["Semantic Model<br/>(Direct Lake / Import)"]
        SQL["Lakehouse<br/>SQL Endpoint"]
        WH["Warehouse<br/>SQL Endpoint"]
        PR["Paginated<br/>Report Item"]
    end

    subgraph Rendering["📄 Rendering Engine"]
        RE["SSRS Rendering<br/>Engine"]
        PDF["PDF"]
        XLS["Excel"]
        CSV["CSV"]
        WORD["Word"]
    end

    subgraph Delivery["📬 Delivery"]
        EMAIL["Email<br/>Subscription"]
        SP["SharePoint"]
        TEAMS["Teams"]
        API["Power BI<br/>REST API"]
    end

    RB --> RDL --> WS
    WS --> PR
    PR --> SM
    PR --> SQL
    PR --> WH
    PR --> RE
    RE --> PDF
    RE --> XLS
    RE --> CSV
    RE --> WORD
    PDF --> EMAIL
    PDF --> SP
    PDF --> TEAMS
    XLS --> API

    style Authoring fill:#2E86C1,stroke:#1A5276,color:#fff
    style Fabric fill:#6C3483,stroke:#4A235A,color:#fff
    style Rendering fill:#E67E22,stroke:#CA6F1E,color:#fff
    style Delivery fill:#27AE60,stroke:#1E8449,color:#fff

Data Source Connection Flow¶

sequenceDiagram
    participant User
    participant Report as Paginated Report
    participant SM as Semantic Model
    participant SQL as SQL Endpoint
    participant DL as Delta Lake (OneLake)

    User->>Report: Open report / trigger subscription
    Report->>Report: Evaluate parameters
    alt Semantic Model Source
        Report->>SM: DAX query with RLS
        SM->>DL: Read Delta tables (Direct Lake)
        DL-->>SM: Column segments
        SM-->>Report: Filtered result set
    else SQL Endpoint Source
        Report->>SQL: T-SQL query with parameters
        SQL->>DL: Read Delta tables
        DL-->>SQL: Row data
        SQL-->>Report: Result set
    end
    Report->>Report: Render pages (PDF/Excel/etc.)
    Report-->>User: Rendered output

⚙️ Authoring with Report Builder¶

Getting Started¶

Power BI Report Builder is the desktop application for authoring paginated reports. It produces .rdl files (Report Definition Language) that are uploaded to Fabric workspaces.

RDL Structure¶

Report (.rdl)
├── Data Sources
│   ├── Lakehouse SQL Endpoint
│   ├── Warehouse SQL Endpoint
│   └── Semantic Model (DAX)
├── Datasets
│   ├── Dataset 1 (T-SQL query)
│   ├── Dataset 2 (DAX query)
│   └── Dataset 3 (stored procedure)
├── Parameters
│   ├── @StartDate (Date)
│   ├── @EndDate (Date)
│   └── @PropertyCode (String, multi-value)
├── Report Body
│   ├── Page Header (logo, title, date)
│   ├── Table / Matrix / List regions
│   ├── Subreports
│   ├── Charts
│   └── Page Footer (page number, disclaimer)
└── Properties
    ├── Page Size (Letter / A4 / Legal)
    ├── Margins
    └── Orientation (Portrait / Landscape)

Dataset Query Examples¶

T-SQL against Lakehouse SQL Endpoint:

SELECT
    t.transaction_id,
    t.transaction_date,
    t.amount,
    t.transaction_type,
    p.player_name,
    p.loyalty_tier,
    l.property_name
FROM lh_gold.gold_transactions AS t
JOIN lh_gold.dim_player AS p ON t.player_id = p.player_id
JOIN lh_gold.dim_location AS l ON t.location_id = l.location_id
WHERE t.transaction_date BETWEEN @StartDate AND @EndDate
    AND (@PropertyCode IS NULL OR l.property_code IN (@PropertyCode))
ORDER BY t.transaction_date DESC

DAX against Semantic Model:

EVALUATE
ADDCOLUMNS(
    FILTER(
        gold_compliance_summary,
        gold_compliance_summary[filing_date] >= @StartDate
        && gold_compliance_summary[filing_date] <= @EndDate
        && gold_compliance_summary[filing_type] = "CTR"
    ),
    "Player Name", RELATED(dim_player[player_name]),
    "Property", RELATED(dim_location[property_name])
)
ORDER BY gold_compliance_summary[filing_date] DESC

📐 Parameters and Subreports¶

Parameter Types¶

Cascading Parameter Example¶

flowchart LR
    P1["📋 Select State<br/>@State = 'Nevada'"]
    P2["📋 Select Property<br/>@Property = 'Bellagio'"]
    P3["📋 Select Date Range<br/>@Start = 2026-01-01<br/>@End = 2026-03-31"]
    P4["📄 Render Report"]

    P1 -->|filters| P2 -->|filters| P3 --> P4

    style P1 fill:#3498DB,stroke:#2980B9,color:#fff
    style P2 fill:#3498DB,stroke:#2980B9,color:#fff
    style P3 fill:#3498DB,stroke:#2980B9,color:#fff
    style P4 fill:#27AE60,stroke:#1E8449,color:#fff

Subreport Pattern: Master-Detail¶

A master report lists summary rows, and each row embeds a subreport showing transaction details:

Master Report: Daily Cage Reconciliation
├── Property Header (name, date, manager)
├── Summary Table
│   ├── Row: Cage 1 | Opening $500K | Closing $485K | Variance -$15K
│   │   └── [Subreport: Cage 1 Transaction Detail]
│   ├── Row: Cage 2 | Opening $300K | Closing $312K | Variance +$12K
│   │   └── [Subreport: Cage 2 Transaction Detail]
│   └── Row: Cage 3 | Opening $750K | Closing $748K | Variance -$2K
│       └── [Subreport: Cage 3 Transaction Detail]
└── Footer: Grand Total | Variance Summary | Signatures

📤 Export Formats and Subscriptions¶

Export Format Comparison¶

Subscription Configuration¶

Workspace → Paginated Report → Subscribe
├── Schedule
│   ├── Frequency: Daily / Weekly / Monthly
│   ├── Time: 06:00 AM EST
│   └── Time Zone: Eastern Time
├── Parameters (locked for subscription)
│   ├── @StartDate = Yesterday
│   └── @EndDate = Yesterday
├── Format: PDF
├── Recipients
│   ├── compliance-team@casino.com
│   ├── cage-manager@casino.com
│   └── SharePoint: /sites/Compliance/Reports/
└── Subject: "Daily CTR Filing Report - {date}"

Power BI REST API Export¶

import requests

# Export paginated report via REST API
url = "https://api.powerbi.com/v1.0/myorg/groups/{workspace_id}/reports/{report_id}/ExportTo"

payload = {
    "format": "PDF",
    "paginatedReportConfiguration": {
        "parameterValues": [
            {"name": "StartDate", "value": "2026-04-01"},
            {"name": "EndDate", "value": "2026-04-15"},
            {"name": "PropertyCode", "value": "LV01"}
        ]
    }
}

response = requests.post(url, json=payload, headers={"Authorization": f"Bearer {token}"})
export_id = response.json()["id"]

🎰 Casino Implementation¶

CTR Filing Report (Currency Transaction Report)¶

Federal law (31 CFR 1021) requires casinos to file a CTR for any cash transaction exceeding $10,000 in a single gaming day. This paginated report generates the FinCEN-compliant form.

Data Model¶

erDiagram
    gold_ctr_filings ||--o{ dim_player : "player_id"
    gold_ctr_filings ||--o{ dim_location : "location_id"
    gold_ctr_filings ||--o{ dim_date : "date_key"

    gold_ctr_filings {
        int filing_id PK
        int player_id FK
        int location_id FK
        int date_key FK
        decimal total_cash_in
        decimal total_cash_out
        decimal aggregate_amount
        string filing_status
        datetime filed_timestamp
        string bsa_id
        string reviewer
    }

    dim_player {
        int player_id PK
        string player_name
        string ssn_hash
        date dob
        string address
        string id_type
        string id_number
    }

    dim_location {
        int location_id PK
        string property_name
        string property_code
        string cage_id
        string state
    }

    dim_date {
        int date_key PK
        date full_date
        string day_of_week
        int month
        int fiscal_quarter
    }

Report Layout¶

┌──────────────────────────────────────────────────┐
│ LOGO    CURRENCY TRANSACTION REPORT       Page 1 │
│         FinCEN Form 103 - Casino                  │
│         Filing Date: 2026-04-15                   │
├──────────────────────────────────────────────────┤
│ Part I — Person Involved in Transaction           │
│ Name: [player_name]    DOB: [dob]                │
│ SSN: [masked_ssn]      ID: [id_type] [id_number] │
│ Address: [address]                                │
├──────────────────────────────────────────────────┤
│ Part II — Amount and Type of Transaction          │
│ Cash In:  $12,500.00   Cash Out: $0.00           │
│ Aggregate: $12,500.00                            │
│ Transaction Type: [Slot Play / Table Game / Cage] │
├──────────────────────────────────────────────────┤
│ Part III — Casino Information                     │
│ Property: [property_name]  EIN: [ein]            │
│ Address: [property_address]                       │
│ Filed By: [reviewer]  BSA ID: [bsa_id]           │
├──────────────────────────────────────────────────┤
│ Page 1 of 1  |  Generated: 2026-04-15 06:00 EST  │
└──────────────────────────────────────────────────┘

W-2G Withholding Report¶

IRS Form W-2G is required for certain gambling winnings. Thresholds: $1,200 (slots), $600 (keno at 300:1+), $5,000 (poker tournament).

-- W-2G Dataset Query
SELECT
    w.form_id,
    w.gaming_date,
    w.win_amount,
    w.federal_withholding,
    w.state_withholding,
    w.game_type,
    p.player_name,
    p.ssn_hash,
    p.address,
    l.property_name,
    l.ein
FROM lh_gold.gold_w2g_filings AS w
JOIN lh_gold.dim_player AS p ON w.player_id = p.player_id
JOIN lh_gold.dim_location AS l ON w.location_id = l.location_id
WHERE w.gaming_date BETWEEN @StartDate AND @EndDate
    AND w.win_amount >= CASE
        WHEN w.game_type = 'Slots' THEN 1200
        WHEN w.game_type = 'Keno' THEN 600
        WHEN w.game_type = 'Poker' THEN 5000
        ELSE 600
    END
ORDER BY w.gaming_date, w.form_id

Daily Cage Reconciliation Report¶

A pixel-perfect daily reconciliation showing opening and closing balances by cage, with variance analysis and supervisor sign-off lines.

Player Activity Statement¶

Monthly statement mailed to loyalty program members showing session history, comps earned, and win/loss summary. Parameters: @PlayerID, @StatementMonth.

🏛️ Federal Agency Implementation¶

Regulatory Compliance Filing Report¶

A multi-agency compliance report template that generates standardized filings for regulatory submissions.

Data Model¶

erDiagram
    gold_compliance_filings ||--o{ dim_agency : "agency_code"
    gold_compliance_filings ||--o{ dim_program : "program_id"
    gold_compliance_filings ||--o{ dim_date : "date_key"

    gold_compliance_filings {
        int filing_id PK
        string agency_code FK
        int program_id FK
        int date_key FK
        string filing_type
        string period
        decimal amount_reported
        string status
        datetime submitted_date
        string reviewer
    }

    dim_agency {
        string agency_code PK
        string agency_name
        string acronym
        string region
    }

    dim_program {
        int program_id PK
        string program_name
        string category
        decimal annual_budget
        string status
    }

Grant Disbursement Report (SBA)¶

A paginated report listing all Small Business Administration grant disbursements for a given fiscal quarter, with subtotals by program and state.

-- SBA Grant Disbursement Dataset
SELECT
    g.disbursement_id,
    g.disbursement_date,
    g.amount,
    g.program_name,
    b.business_name,
    b.state,
    b.naics_code,
    b.employee_count,
    g.status
FROM lh_gold.gold_sba_disbursements AS g
JOIN lh_gold.dim_sba_business AS b ON g.business_id = b.business_id
WHERE g.fiscal_quarter = @FiscalQuarter
    AND g.fiscal_year = @FiscalYear
    AND (@State IS NULL OR b.state IN (@State))
ORDER BY b.state, g.program_name, g.disbursement_date

Report Features¶

USDA Crop Production Summary¶

A quarterly report summarizing crop production statistics by state and commodity, exported as PDF for distribution to congressional committees.

EPA Facility Inspection Report¶

A per-facility inspection report with findings, violation history, and corrective action timelines, rendered as a multi-page PDF with subreports for each inspection event.

🔐 Security and RLS¶

RLS Enforcement in Paginated Reports¶

Row-Level Security defined on the semantic model is enforced when a paginated report connects to a semantic model data source. Each subscription renders with the recipient's identity, ensuring users only see their authorized data.

flowchart LR
    subgraph Sub["📬 Subscription"]
        S1["Floor Manager A<br/>floor_zone = 'North'"]
        S2["Floor Manager B<br/>floor_zone = 'South'"]
        S3["Compliance Officer<br/>all zones"]
    end

    subgraph Report["📄 Paginated Report"]
        R["CTR Filing Report"]
    end

    subgraph RLS["🔐 RLS Filter"]
        F1["North zone data only"]
        F2["South zone data only"]
        F3["All data"]
    end

    S1 --> R --> F1
    S2 --> R --> F2
    S3 --> R --> F3

    style Sub fill:#3498DB,stroke:#2980B9,color:#fff
    style Report fill:#E67E22,stroke:#CA6F1E,color:#fff
    style RLS fill:#C0392B,stroke:#922B21,color:#fff

Security Best Practices¶

⚠️ Limitations¶

📚 References¶

🔗 Related Documents¶

• Direct Lake -- Semantic model connectivity for paginated data sources
• Composite Models -- Mixing storage modes for paginated report data
• Scorecards & Metrics -- KPI tracking complement to paginated reporting
• Fabric IQ -- Natural language queries for ad-hoc analysis
• OneLake Security -- Storage-level security for underlying data
• Architecture -- System architecture overview
• Security -- Security and compliance framework

📝 Document Metadata - Author: Documentation Team - Reviewers: Data Engineering, BI Team, Compliance - Classification: Internal - Next Review: 2026-07-21