| | 1 | = Venue Capacity Utilization Analysis = |
| | 2 | |
| | 3 | == 2. Scenario Overview == |
| | 4 | |
| | 5 | This scenario analyzes venue occupancy and attendance utilization for weddings organized inside the system. |
| | 6 | |
| | 7 | The analysis combines: |
| | 8 | * venue capacity information |
| | 9 | * wedding bookings |
| | 10 | * guest attendance records |
| | 11 | * event participation statistics |
| | 12 | |
| | 13 | The generated report provides operational insights regarding: |
| | 14 | * occupancy percentage |
| | 15 | * attendance efficiency |
| | 16 | * available seating capacity |
| | 17 | * utilization classification |
| | 18 | |
| | 19 | == 2.1 Objective == |
| | 20 | |
| | 21 | Analyze the relationship between confirmed guest attendance and venue capacity constraints. |
| | 22 | |
| | 23 | The report determines: |
| | 24 | * actual occupancy rate |
| | 25 | * available seating capacity |
| | 26 | * venue utilization level |
| | 27 | * attendance efficiency |
| | 28 | |
| | 29 | This analysis combines attendance records, venue specifications, and booking confirmations to establish operational efficiency indicators. |
| | 30 | |
| | 31 | == 2.2 SQL Query Implementation == |
| | 32 | |
| | 33 | === SQL Code === |
| | 34 | |
| | 35 | {{{ |
| | 36 | #!sql |
| | 37 | SELECT |
| | 38 | v.venue_id, |
| | 39 | v.name AS venue_name, |
| | 40 | v.capacity AS venue_capacity, |
| | 41 | |
| | 42 | w.wedding_id, |
| | 43 | |
| | 44 | u.first_name || ' ' || u.last_name |
| | 45 | AS organizer_name, |
| | 46 | |
| | 47 | w.date AS wedding_date, |
| | 48 | |
| | 49 | COUNT(DISTINCT a.guest_id) |
| | 50 | AS confirmed_attendees, |
| | 51 | |
| | 52 | COUNT( |
| | 53 | DISTINCT CASE |
| | 54 | WHEN a.status = 'ATTENDED' |
| | 55 | THEN a.guest_id |
| | 56 | END |
| | 57 | ) AS actual_attendance, |
| | 58 | |
| | 59 | v.capacity - COUNT(DISTINCT a.guest_id) |
| | 60 | AS available_seats, |
| | 61 | |
| | 62 | ROUND( |
| | 63 | ( |
| | 64 | CAST(COUNT(DISTINCT a.guest_id) AS NUMERIC) |
| | 65 | / v.capacity |
| | 66 | ) * 100, |
| | 67 | 2 |
| | 68 | ) AS occupancy_rate_percent, |
| | 69 | |
| | 70 | CASE |
| | 71 | WHEN COUNT(DISTINCT a.guest_id) > v.capacity |
| | 72 | THEN 'EXCEEDED' |
| | 73 | |
| | 74 | WHEN COUNT(DISTINCT a.guest_id) |
| | 75 | >= (v.capacity * 0.9) |
| | 76 | THEN 'HIGH' |
| | 77 | |
| | 78 | WHEN COUNT(DISTINCT a.guest_id) |
| | 79 | >= (v.capacity * 0.6) |
| | 80 | THEN 'MODERATE' |
| | 81 | |
| | 82 | ELSE 'LOW' |
| | 83 | END AS utilization_category, |
| | 84 | |
| | 85 | vb.status AS booking_status, |
| | 86 | vb.date AS booking_date |
| | 87 | |
| | 88 | FROM venue v |
| | 89 | |
| | 90 | INNER JOIN venue_booking vb |
| | 91 | ON v.venue_id = vb.venue_id |
| | 92 | |
| | 93 | INNER JOIN wedding w |
| | 94 | ON vb.wedding_id = w.wedding_id |
| | 95 | |
| | 96 | INNER JOIN "user" u |
| | 97 | ON w.user_id = u.user_id |
| | 98 | |
| | 99 | LEFT JOIN event e |
| | 100 | ON w.wedding_id = e.wedding_id |
| | 101 | |
| | 102 | LEFT JOIN attendance a |
| | 103 | ON e.event_id = a.event_id |
| | 104 | AND a.status IN ('ATTENDED', 'CONFIRMED') |
| | 105 | |
| | 106 | GROUP BY |
| | 107 | v.venue_id, |
| | 108 | v.name, |
| | 109 | v.capacity, |
| | 110 | w.wedding_id, |
| | 111 | u.first_name, |
| | 112 | u.last_name, |
| | 113 | w.date, |
| | 114 | vb.status, |
| | 115 | vb.date |
| | 116 | |
| | 117 | HAVING COUNT(DISTINCT a.guest_id) > 0 |
| | 118 | |
| | 119 | ORDER BY |
| | 120 | v.venue_id, |
| | 121 | w.wedding_id; |
| | 122 | }}} |
| | 123 | |
| | 124 | == 2.3 Query Complexity Analysis == |
| | 125 | |
| | 126 | * Join Count: |
| | 127 | * 6 tables |
| | 128 | |
| | 129 | * Join Types: |
| | 130 | * INNER JOIN |
| | 131 | * LEFT JOIN |
| | 132 | |
| | 133 | * Aggregate Functions: |
| | 134 | * COUNT(DISTINCT ...) |
| | 135 | * ROUND() |
| | 136 | * CASE |
| | 137 | |
| | 138 | * Filtering Logic: |
| | 139 | * HAVING clause after aggregation |
| | 140 | |
| | 141 | * Conditional Categorization: |
| | 142 | * LOW |
| | 143 | * MODERATE |
| | 144 | * HIGH |
| | 145 | * EXCEEDED |
| | 146 | |
| | 147 | == 2.4 Relational Algebra Expression == |
| | 148 | |
| | 149 | {{{ |
| | 150 | π( |
| | 151 | v.venue_id, |
| | 152 | v.name, |
| | 153 | v.capacity, |
| | 154 | w.wedding_id, |
| | 155 | u.fname, |
| | 156 | u.lname, |
| | 157 | w.date, |
| | 158 | COUNT(a.guest_id), |
| | 159 | v.capacity - COUNT(a.guest_id), |
| | 160 | (COUNT(a.guest_id) / v.capacity) * 100 |
| | 161 | ) |
| | 162 | |
| | 163 | ( |
| | 164 | σ(COUNT(guest_id) > 0) |
| | 165 | |
| | 166 | ( |
| | 167 | γ( |
| | 168 | venue_id, |
| | 169 | wedding_id, |
| | 170 | COUNT(DISTINCT a.guest_id) |
| | 171 | ) |
| | 172 | |
| | 173 | ( |
| | 174 | (((Venue ⟕ Venue_Booking) |
| | 175 | ⟕ Wedding) |
| | 176 | ⟕ User) |
| | 177 | ⟕ Event) |
| | 178 | ⟕ Attendance |
| | 179 | ) |
| | 180 | ) |
| | 181 | }}} |
| | 182 | |
| | 183 | === Notation === |
| | 184 | |
| | 185 | * π = Projection |
| | 186 | * σ = Selection |
| | 187 | * γ = Grouping and aggregation |
| | 188 | * ⟕ = Join operation |
| | 189 | * COUNT(DISTINCT ...) = Distinct aggregation |
| | 190 | |
| | 191 | === Interpretation === |
| | 192 | |
| | 193 | The expression combines venue, booking, wedding, event, and attendance relations in order to calculate venue occupancy metrics. |
| | 194 | |
| | 195 | Aggregation is applied after filtering attendance data, enabling utilization analysis for each wedding event. |
| | 196 | |
| | 197 | == 2.5 PostgreSQL Stored Procedure == |
| | 198 | |
| | 199 | === SQL Code === |
| | 200 | |
| | 201 | {{{ |
| | 202 | #!sql |
| | 203 | CREATE OR REPLACE PROCEDURE |
| | 204 | venue_capacity_utilization_report( |
| | 205 | |
| | 206 | IN p_venue_id INT DEFAULT NULL, |
| | 207 | |
| | 208 | IN p_min_occupancy_percent NUMERIC DEFAULT 0, |
| | 209 | |
| | 210 | IN p_max_occupancy_percent NUMERIC DEFAULT 100 |
| | 211 | ) |
| | 212 | |
| | 213 | LANGUAGE plpgsql |
| | 214 | |
| | 215 | AS $$ |
| | 216 | |
| | 217 | DECLARE |
| | 218 | |
| | 219 | v_record RECORD; |
| | 220 | |
| | 221 | v_confirmed_count INTEGER; |
| | 222 | |
| | 223 | v_actual_count INTEGER; |
| | 224 | |
| | 225 | v_occupancy_rate NUMERIC; |
| | 226 | |
| | 227 | v_utilization_category VARCHAR; |
| | 228 | |
| | 229 | v_capacity INTEGER; |
| | 230 | |
| | 231 | BEGIN |
| | 232 | |
| | 233 | CREATE TEMP TABLE capacity_utilization_results ( |
| | 234 | |
| | 235 | venue_id INTEGER, |
| | 236 | |
| | 237 | venue_name VARCHAR, |
| | 238 | |
| | 239 | venue_capacity INTEGER, |
| | 240 | |
| | 241 | wedding_id INTEGER, |
| | 242 | |
| | 243 | organizer_name VARCHAR, |
| | 244 | |
| | 245 | wedding_date DATE, |
| | 246 | |
| | 247 | confirmed_attendees INTEGER, |
| | 248 | |
| | 249 | actual_attendance INTEGER, |
| | 250 | |
| | 251 | available_seats INTEGER, |
| | 252 | |
| | 253 | occupancy_rate_percent NUMERIC, |
| | 254 | |
| | 255 | utilization_category VARCHAR, |
| | 256 | |
| | 257 | booking_status VARCHAR, |
| | 258 | |
| | 259 | booking_date DATE |
| | 260 | ); |
| | 261 | |
| | 262 | FOR v_record IN |
| | 263 | |
| | 264 | SELECT DISTINCT |
| | 265 | v.venue_id, |
| | 266 | v.name, |
| | 267 | v.capacity, |
| | 268 | w.wedding_id, |
| | 269 | u.first_name, |
| | 270 | u.last_name, |
| | 271 | w.date, |
| | 272 | vb.status, |
| | 273 | vb.date |
| | 274 | |
| | 275 | FROM venue v |
| | 276 | |
| | 277 | INNER JOIN venue_booking vb |
| | 278 | ON v.venue_id = vb.venue_id |
| | 279 | |
| | 280 | INNER JOIN wedding w |
| | 281 | ON vb.wedding_id = w.wedding_id |
| | 282 | |
| | 283 | INNER JOIN "user" u |
| | 284 | ON w.user_id = u.user_id |
| | 285 | |
| | 286 | WHERE |
| | 287 | ( |
| | 288 | p_venue_id IS NULL |
| | 289 | OR v.venue_id = p_venue_id |
| | 290 | ) |
| | 291 | |
| | 292 | LOOP |
| | 293 | |
| | 294 | SELECT COUNT(DISTINCT a.guest_id) |
| | 295 | |
| | 296 | INTO v_confirmed_count |
| | 297 | |
| | 298 | FROM event e |
| | 299 | |
| | 300 | LEFT JOIN attendance a |
| | 301 | ON e.event_id = a.event_id |
| | 302 | AND a.status = 'CONFIRMED' |
| | 303 | |
| | 304 | WHERE e.wedding_id = v_record.wedding_id; |
| | 305 | |
| | 306 | SELECT COUNT(DISTINCT a.guest_id) |
| | 307 | |
| | 308 | INTO v_actual_count |
| | 309 | |
| | 310 | FROM event e |
| | 311 | |
| | 312 | LEFT JOIN attendance a |
| | 313 | ON e.event_id = a.event_id |
| | 314 | AND a.status = 'ATTENDED' |
| | 315 | |
| | 316 | WHERE e.wedding_id = v_record.wedding_id; |
| | 317 | |
| | 318 | v_confirmed_count := |
| | 319 | COALESCE(v_confirmed_count, 0); |
| | 320 | |
| | 321 | v_actual_count := |
| | 322 | COALESCE(v_actual_count, 0); |
| | 323 | |
| | 324 | v_capacity := v_record.capacity; |
| | 325 | |
| | 326 | IF v_capacity > 0 THEN |
| | 327 | |
| | 328 | v_occupancy_rate := |
| | 329 | ROUND( |
| | 330 | ( |
| | 331 | CAST(v_confirmed_count AS NUMERIC) |
| | 332 | / v_capacity |
| | 333 | ) * 100, |
| | 334 | 2 |
| | 335 | ); |
| | 336 | |
| | 337 | ELSE |
| | 338 | |
| | 339 | v_occupancy_rate := 0; |
| | 340 | |
| | 341 | END IF; |
| | 342 | |
| | 343 | IF v_confirmed_count > v_capacity THEN |
| | 344 | |
| | 345 | v_utilization_category := 'EXCEEDED'; |
| | 346 | |
| | 347 | ELSIF v_occupancy_rate >= 90 THEN |
| | 348 | |
| | 349 | v_utilization_category := 'HIGH'; |
| | 350 | |
| | 351 | ELSIF v_occupancy_rate >= 60 THEN |
| | 352 | |
| | 353 | v_utilization_category := 'MODERATE'; |
| | 354 | |
| | 355 | ELSE |
| | 356 | |
| | 357 | v_utilization_category := 'LOW'; |
| | 358 | |
| | 359 | END IF; |
| | 360 | |
| | 361 | IF v_occupancy_rate BETWEEN |
| | 362 | p_min_occupancy_percent |
| | 363 | AND |
| | 364 | p_max_occupancy_percent |
| | 365 | |
| | 366 | THEN |
| | 367 | |
| | 368 | INSERT INTO capacity_utilization_results |
| | 369 | |
| | 370 | VALUES ( |
| | 371 | |
| | 372 | v_record.venue_id, |
| | 373 | |
| | 374 | v_record.name, |
| | 375 | |
| | 376 | v_record.capacity, |
| | 377 | |
| | 378 | v_record.wedding_id, |
| | 379 | |
| | 380 | v_record.first_name || ' ' || |
| | 381 | v_record.last_name, |
| | 382 | |
| | 383 | v_record.date, |
| | 384 | |
| | 385 | v_confirmed_count, |
| | 386 | |
| | 387 | v_actual_count, |
| | 388 | |
| | 389 | v_capacity - v_confirmed_count, |
| | 390 | |
| | 391 | v_occupancy_rate, |
| | 392 | |
| | 393 | v_utilization_category, |
| | 394 | |
| | 395 | v_record.status, |
| | 396 | |
| | 397 | v_record.date |
| | 398 | ); |
| | 399 | |
| | 400 | END IF; |
| | 401 | |
| | 402 | END LOOP; |
| | 403 | |
| | 404 | RAISE NOTICE |
| | 405 | 'Venue Capacity Utilization Report Generated - % rows processed', |
| | 406 | |
| | 407 | ( |
| | 408 | SELECT COUNT(*) |
| | 409 | FROM capacity_utilization_results |
| | 410 | ); |
| | 411 | |
| | 412 | END; |
| | 413 | $$; |
| | 414 | }}} |
| | 415 | |
| | 416 | == 2.6 Procedure Characteristics == |
| | 417 | |
| | 418 | * Input Parameters: |
| | 419 | * venue ID |
| | 420 | * minimum occupancy percentage |
| | 421 | * maximum occupancy percentage |
| | 422 | |
| | 423 | * Attendance Analysis: |
| | 424 | * confirmed attendance counting |
| | 425 | * actual attendance counting |
| | 426 | |
| | 427 | * Occupancy Classification: |
| | 428 | * LOW |
| | 429 | * MODERATE |
| | 430 | * HIGH |
| | 431 | * EXCEEDED |
| | 432 | |
| | 433 | * NULL Handling: |
| | 434 | * COALESCE() usage |
| | 435 | |
| | 436 | * Filtering Logic: |
| | 437 | * occupancy percentage range filtering |
| | 438 | |
| | 439 | == 2.7 Proof of Execution with Sample Data == |
| | 440 | |
| | 441 | === Sample Data Insertion === |
| | 442 | |
| | 443 | {{{ |
| | 444 | #!sql |
| | 445 | INSERT INTO "user" ( |
| | 446 | first_name, |
| | 447 | last_name, |
| | 448 | email, |
| | 449 | phone_number |
| | 450 | ) |
| | 451 | VALUES ( |
| | 452 | 'Марко', |
| | 453 | 'Стојановски', |
| | 454 | 'marko.s@email.com', |
| | 455 | '070-123-456' |
| | 456 | ); |
| | 457 | |
| | 458 | INSERT INTO wedding ( |
| | 459 | date, |
| | 460 | budget, |
| | 461 | user_id |
| | 462 | ) |
| | 463 | VALUES ( |
| | 464 | '2024-07-20', |
| | 465 | 12000.00, |
| | 466 | 2 |
| | 467 | ); |
| | 468 | |
| | 469 | INSERT INTO venue ( |
| | 470 | name, |
| | 471 | location, |
| | 472 | city, |
| | 473 | address, |
| | 474 | capacity, |
| | 475 | price_per_guest, |
| | 476 | type_id |
| | 477 | ) |
| | 478 | VALUES ( |
| | 479 | 'Golden Palace', |
| | 480 | 'Centar', |
| | 481 | 'Skopje', |
| | 482 | 'Ilindenska 15', |
| | 483 | 150, |
| | 484 | 55.00, |
| | 485 | 1 |
| | 486 | ); |
| | 487 | }}} |
| | 488 | |
| | 489 | === Query Execution Result === |
| | 490 | |
| | 491 | {{{ |
| | 492 | venue_id | venue_name | venue_capacity |
| | 493 | ----------+---------------+---------------- |
| | 494 | 2 | Golden Palace | 150 |
| | 495 | }}} |
| | 496 | |
| | 497 | === Calculation Verification === |
| | 498 | |
| | 499 | * Confirmed Attendees: |
| | 500 | * guests marked as CONFIRMED |
| | 501 | |
| | 502 | * Actual Attendance: |
| | 503 | * guests marked as ATTENDED |
| | 504 | |
| | 505 | * Available Seats: |
| | 506 | * venue capacity minus confirmed attendees |
| | 507 | |
| | 508 | * Occupancy Rate: |
| | 509 | * percentage of occupied seats |
| | 510 | |
| | 511 | * Utilization Category: |
| | 512 | * calculated based on occupancy thresholds |
| | 513 | |
| | 514 | == Summary == |
| | 515 | |
| | 516 | This scenario demonstrates operational venue analysis using: |
| | 517 | * multi-table joins |
| | 518 | * attendance aggregation |
| | 519 | * occupancy calculations |
| | 520 | * utilization categorization |
| | 521 | * PostgreSQL stored procedures |
| | 522 | * analytical reporting techniques |