Changes between Version 9 and Version 10 of P6


Ignore:
Timestamp:
05/13/26 21:14:50 (13 days ago)
Author:
193284
Comment:

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  • P6

    v9 v10  
    33== Overview ==
    44
    5 In this phase we demonstrate how to extract, analyze and summarize data from the Wedding Planner database using advanced SQL.
     5In this phase we demonstrate how to extract, analyze, and summarize data from the Wedding Planner database using advanced SQL queries, PostgreSQL stored procedures, and relational algebra expressions.
    66
    7 We focus on generating complex reports across multiple related tables, and implementing reusable logic through stored procedures and views.
     7The implementation focuses on generating analytical reports across multiple related tables while demonstrating aggregation, temporal calculations, filtering, grouping, and procedural database logic.
    88
    9 These techniques are important because in a real system the database is not used only for storing data, but also for producing meaningful insights such as guest statistics, financial reports, venue utilization analysis, RSVP conversion analysis, and operational summaries.
     9The phase includes:
     10* complex SQL reporting queries
     11* relational algebra representations
     12* PostgreSQL stored procedures
     13* analytical calculations
     14* financial analysis
     15* venue utilization analysis
     16* RSVP conversion analysis
     17* performance and scalability considerations
    1018
    11 == Phase Structure ==
     19These techniques are important because modern database systems are not only responsible for storing information, but also for generating operational and analytical insights used for decision-making.
    1220
    13 This phase is divided into the following analytical scenarios:
     21== Technical Environment ==
     22
     23|| Component || Technology ||
     24|| Database Engine || PostgreSQL 15 ||
     25|| SQL Language || PostgreSQL SQL / PLpgSQL ||
     26|| Database Management || pgAdmin 4 ||
     27|| Application Layer || Flask REST API ||
     28|| Character Encoding || UTF-8 ||
     29
     30== Objectives ==
     31
     32* perform advanced analytical reporting using SQL
     33* demonstrate multi-table relational queries
     34* implement reusable stored procedures
     35* calculate financial and attendance metrics
     36* represent SQL queries using relational algebra
     37* analyze operational efficiency and guest engagement
     38* evaluate query performance and scalability
     39
     40== Development History ==
     41
     42* v0.1 – Initial analytical SQL queries
     43* v0.2 – Added relational algebra expressions
     44* v0.3 – Added PostgreSQL stored procedures
     45* v0.4 – Added execution examples and validation
     46* v0.5 – Added performance analysis and optimization discussion
     47* v0.6 – Final wiki documentation cleanup
     48
     49== Scenario Summary ==
    1450
    1551|| Scenario || Description ||
    16 || [[P6BudgetAnalysis|Scenario 1: Budget vs Actual Expenditure Analysis]] || Financial analysis of wedding budgets and actual vendor costs ||
    17 || [[P6VenueCapacity|Scenario 2: Venue Capacity Utilization Analysis]] || Analysis of venue occupancy and attendance metrics ||
    18 || [[P6RSVPConversion|Scenario 3: Event RSVP Conversion Rate Analysis]] || RSVP response and attendance conversion analysis ||
    19 || [[P6SynthesisPerformance|Synthesis and Performance Considerations]] || Integrated analytical query and optimization strategies ||
     52|| Budget vs Actual Expenditure || Financial comparison between planned and actual wedding costs ||
     53|| Venue Capacity Utilization || Analysis of venue occupancy and attendance efficiency ||
     54|| RSVP Conversion Analysis || Analysis of invitation, RSVP, and attendance conversion rates ||
    2055
    21 == Technologies and Concepts Used ==
     56== Contents ==
    2257
    23 * Advanced SQL queries
    24 * Aggregate functions
    25 * Multi-table joins
    26 * Relational algebra expressions
    27 * PostgreSQL stored procedures
    28 * Temporary tables
    29 * Analytical reporting
    30 * Performance optimization strategies
     58=== [[P6BudgetAnalysis]] ===
     59Financial analysis using advanced SQL aggregation and stored procedures.
     60
     61=== [[P6VenueCapacity]] ===
     62Venue utilization and attendance analysis using analytical queries.
     63
     64=== [[P6RSVPConversion]] ===
     65RSVP response and attendance conversion analysis.
     66
     67=== [[P6SynthesisPerformance]] ===
     68Integrated reporting, performance optimization, scalability discussion, and conclusions.
    3169
    3270== Summary ==
    3371
    34 The reports implemented in this phase demonstrate how relational databases can be used not only for transactional processing, but also for analytical and reporting purposes.
     72This phase demonstrates advanced relational database analysis through complex SQL queries, aggregation, stored procedures, relational algebra expressions, and analytical reporting.
    3573
    36 The generated reports provide insights into financial planning, attendance analysis, RSVP effectiveness, and overall wedding management efficiency.
     74The implementation provides financial, operational, and engagement insights for the Wedding Planner Management System while illustrating advanced database design and optimization principles.