Changes between Version 4 and Version 5 of AdvancedReports


Ignore:
Timestamp:
01/21/26 04:40:41 (6 days ago)
Author:
221181
Comment:

--

Legend:

Unmodified
Added
Removed
Modified
  • AdvancedReports

    v4 v5  
    22----
    33
    4 == 1.  ==
     4== 1. ABC Анализа на производи (ABC Product Analysis) ==
     5
     6Овој извештај ги дели производите во сегменти A (80%), B (15%) и C (5%) според нивниот придонес во вкупниот промет, користејќи ги овие проценти за да се прикаже кои производи се најважни за приходот и да се олесни управувањето со залихите.
     7
     8{{{#!sql
     9WITH ProductRevenue AS (
     10    SELECT
     11        p.name AS product_name,
     12        SUM(si.quantity * si.unit_price_at_sale) AS total_revenue
     13    FROM product p
     14    JOIN sale_item si ON p.product_id = si.product_id
     15    GROUP BY p.name
     16),
     17RevenueCalculations AS (
     18    SELECT
     19        product_name,
     20        total_revenue,
     21        SUM(total_revenue) OVER (ORDER BY total_revenue DESC) / SUM(total_revenue) OVER () AS cumulative_share
     22    FROM ProductRevenue
     23)
     24SELECT
     25    product_name,
     26    ROUND(total_revenue, 2) AS revenue_mkd,
     27    CASE
     28        WHEN cumulative_share <= 0.80 THEN 'A (High Value)'
     29        WHEN cumulative_share <= 0.95 THEN 'B (Medium Value)'
     30        ELSE 'C (Low Value)'
     31    END AS abc_classification
     32FROM RevenueCalculations;
     33}}}
     34
     35'''Релациона алгебра:'''
     36{{{
     37ProductRevenue ← γ name; SUM(quantity × unit_price_at_sale) → total_revenue (product ⨝ product_id sale_item)
     38
     39RevenueCalculations ← π product_name, total_revenue,
     40                        (RunningSum(total_revenue) / TotalSum(total_revenue)) → cumulative_share
     41                        (τ total_revenue DESC (ProductRevenue))
     42
     43Result ← π product_name,
     44           ROUND(total_revenue, 2) → revenue_mkd,
     45           CASE(cumulative_share ≤ 0.80 → 'A',
     46                cumulative_share ≤ 0.95 → 'B',
     47                ELSE → 'C') → abc_classification
     48           (RevenueCalculations)
     49}}}
     50
     51----
     52
     53== 2. Месечен тренд на продажба (Monthly Sales Growth Trend) ==
     54
     55Ги споредува приходите од тековниот месец со претходниот за да го пресмета процентот на раст или пад на бизнисот.
     56
     57{{{#!sql
     58WITH MonthlySales AS (
     59    SELECT
     60        DATE_TRUNC('month', date_time) AS sales_month,
     61        SUM(total_amount) AS revenue
     62    FROM sale
     63    GROUP BY 1
     64)
     65SELECT
     66    sales_month,
     67    revenue AS current_month_revenue,
     68    LAG(revenue) OVER (ORDER BY sales_month) AS previous_month_revenue,
     69    ROUND(((revenue - LAG(revenue) OVER (ORDER BY sales_month)) /
     70           NULLIF(LAG(revenue) OVER (ORDER BY sales_month), 0)) * 100, 2) AS growth_percentage
     71FROM MonthlySales;
     72}}}
     73
     74'''Релациона алгебра:'''
     75{{{
     76MonthlySales ← γ DATE_TRUNC('month', date_time) → sales_month;
     77                 SUM(total_amount) → revenue (sale)
     78
     79Result ← π sales_month,
     80           revenue → current_month_revenue,
     81           LAG(revenue) → previous_month_revenue,
     82           ROUND(((revenue - LAG(revenue)) / NULLIF(LAG(revenue), 0)) × 100, 2) → growth_percentage
     83           (τ sales_month ASC (MonthlySales))
     84}}}
     85
     86----
     87
     88== 3. Состојба на залихи и критични точки (Inventory Health & Reorder Levels) ==
     89
     90Ги идентификува производите што се под минимумот во магацините и дава аларм за итна набавка.
     91
     92{{{#!sql
     93SELECT
     94    p.name AS product_name,
     95    w.name AS warehouse_location,
     96    ws.quantity_on_hand,
     97    p.reorder_level,
     98    CASE
     99        WHEN ws.quantity_on_hand <= p.reorder_level THEN 'CRITICAL: REORDER'
     100        WHEN ws.quantity_on_hand <= p.reorder_level * 1.5 THEN 'WARNING: LOW'
     101        ELSE 'HEALTHY'
     102    END AS stock_status
     103FROM product p
     104JOIN warehouse_stock ws ON p.product_id = ws.product_id
     105JOIN warehouse w ON ws.warehouse_id = w.warehouse_id;
     106}}}
     107
     108'''Релациона алгебра:'''
     109{{{
     110Temp1 ← product ⨝ product_id=product_id warehouse_stock
     111
     112Temp2 ← Temp1 ⨝ warehouse_id=warehouse_id warehouse
     113
     114Result ← π product.name → product_name,
     115           warehouse.name → warehouse_location,
     116           quantity_on_hand,
     117           reorder_level,
     118           CASE(quantity_on_hand ≤ reorder_level → 'CRITICAL: REORDER',
     119                quantity_on_hand ≤ reorder_level × 1.5 → 'WARNING: LOW',
     120                ELSE → 'HEALTHY') → stock_status
     121           (Temp2)
     122}}}
     123
     124----
     125
     126== 4. Перформанси на добавувачите (Supplier Performance Matrix) ==
     127
     128Го мери доцнењето на испораките од добавувачите и ја пресметува нивната доверливост во исполнување на роковите.
     129
     130{{{#!sql
     131SELECT
     132    s.name AS supplier_name,
     133    COUNT(po.po_id) AS total_orders,
     134    AVG(po.actual_delivery_date - po.expected_delivery_date) AS average_delay_days,
     135    ROUND(COUNT(CASE WHEN po.actual_delivery_date <= po.expected_delivery_date THEN 1 END) * 100.0 / COUNT(*), 2) AS on_time_delivery_rate
     136FROM supplier s
     137JOIN purchase_order po ON s.supplier_id = po.supplier_id
     138WHERE po.status = 'DELIVERED'
     139GROUP BY s.name;
     140}}}
     141
     142'''Релациона алгебра:'''
     143{{{
     144Temp1 ← supplier ⨝ supplier_id=supplier_id purchase_order
     145
     146Temp2 ← σ status='DELIVERED' (Temp1)
     147
     148Result ← γ supplier.name → supplier_name;
     149           COUNT(po_id) → total_orders,
     150           AVG(actual_delivery_date - expected_delivery_date) → average_delay_days,
     151           ROUND(COUNT(actual_delivery_date ≤ expected_delivery_date) × 100.0 / COUNT(*), 2) → on_time_delivery_rate
     152           (Temp2)
     153}}}
     154
     155----
     156
     157== 5. RFM Анализа на клиенти (Customer RFM Segmentation) ==
     158
     159Ги сегментира купувачите според тоа кога последен пат купувале, колку често се враќаат и колку пари потрошиле.
     160
     161{{{#!sql
     162SELECT
     163    c.name AS customer_name,
     164    EXTRACT(DAY FROM CURRENT_TIMESTAMP - MAX(s.date_time)) AS recency_days,
     165    COUNT(s.sale_id) AS frequency_count,
     166    SUM(s.total_amount) AS monetary_total,
     167    NTILE(5) OVER (ORDER BY MAX(s.date_time)) AS r_score,
     168    NTILE(5) OVER (ORDER BY COUNT(s.sale_id)) AS f_score,
     169    NTILE(5) OVER (ORDER BY SUM(s.total_amount)) AS m_score
     170FROM customer c
     171JOIN sale s USING (customer_id)
     172GROUP BY c.customer_id, c.name;
     173}}}
     174
     175'''Релациона алгебра:'''
     176{{{
     177Temp1 ← customer ⨝ customer_id=customer_id sale
     178
     179Result ← γ customer_id, name → customer_name;
     180           EXTRACT(DAY FROM CURRENT_TIMESTAMP - MAX(date_time)) → recency_days,
     181           COUNT(sale_id) → frequency_count,
     182           SUM(total_amount) → monetary_total,
     183           NTILE(5, MAX(date_time)) → r_score,
     184           NTILE(5, COUNT(sale_id)) → f_score,
     185           NTILE(5, SUM(total_amount)) → m_score
     186           (Temp1)
     187}}}
     188
     189----
     190
     191== 6. Искористеност на капацитетот на магацините (Warehouse Utilization Rate) ==
     192
     193Пресметува колкав процент од физичкиот простор во секој магацин е моментално пополнет.
     194
     195{{{#!sql
     196SELECT
     197    w.name AS warehouse_name,
     198    w.capacity AS total_unit_capacity,
     199    SUM(ws.quantity_on_hand) AS units_in_stock,
     200    ROUND((SUM(ws.quantity_on_hand)::NUMERIC / w.capacity) * 100, 2) AS occupancy_percentage
     201FROM warehouse w
     202LEFT JOIN warehouse_stock ws ON w.warehouse_id = ws.warehouse_id
     203GROUP BY w.warehouse_id, w.name, w.capacity;
     204}}}
     205
     206'''Релациона алгебра:'''
     207{{{
     208Temp1 ← warehouse ⟕ warehouse_id=warehouse_id warehouse_stock
     209
     210Result ← γ warehouse_id, name → warehouse_name, capacity → total_unit_capacity;
     211           SUM(quantity_on_hand) → units_in_stock,
     212           ROUND((SUM(quantity_on_hand) / capacity) × 100, 2) → occupancy_percentage
     213           (Temp1)
     214}}}
     215
     216----
     217
     218== 7. Анализа на застојни производи ==
     219
     220Ги прикажува производите што не се продале во последните 90 дена и само зафаќаат простор и капитал.
     221
     222{{{#!sql
     223SELECT
     224    p.name AS product_name,
     225    p.sku,
     226    ws.quantity_on_hand,
     227    COALESCE(MAX(s.date_time)::TEXT, 'NO SALES RECORDED') AS last_sold_date
     228FROM product p
     229JOIN warehouse_stock ws ON p.product_id = ws.product_id
     230LEFT JOIN sale_item si ON p.product_id = si.product_id
     231LEFT JOIN sale s ON si.sale_id = s.sale_id
     232GROUP BY p.product_id, p.name, p.sku, ws.quantity_on_hand
     233HAVING MAX(s.date_time) < CURRENT_DATE - INTERVAL '90 days' OR MAX(s.date_time) IS NULL;
     234}}}
     235
     236'''Релациона алгебра:'''
     237{{{
     238Temp1 ← product ⨝ product_id=product_id warehouse_stock
     239
     240Temp2 ← Temp1 ⟕ product_id=product_id sale_item
     241
     242Temp3 ← Temp2 ⟕ sale_id=sale_id sale
     243
     244Temp4 ← γ product_id, name, sku, quantity_on_hand;
     245          MAX(date_time) → last_sold_date (Temp3)
     246
     247Result ← π name → product_name, sku, quantity_on_hand,
     248           COALESCE(last_sold_date::TEXT, 'NO SALES RECORDED') → last_sold_date
     249           (σ last_sold_date < CURRENT_DATE - 90 ∨ last_sold_date IS NULL (Temp4))
     250}}}
     251
     252----
     253
     254== 8. Маржа на профит по категорија (Category Profit Margin) ==
     255
     256Ја пресметува разликата помеѓу продажната и набавната цена за секоја категорија производи.
     257
     258{{{#!sql
     259WITH ProductCosts AS (
     260    SELECT product_id, AVG(unit_cost) AS average_cost FROM purchase_order_item GROUP BY 1
     261)
     262SELECT
     263    c.name AS category_name,
     264    SUM(si.quantity * si.unit_price_at_sale) AS gross_revenue,
     265    SUM(si.quantity * pc.average_cost) AS total_cost_of_goods,
     266    ROUND(((SUM(si.quantity * si.unit_price_at_sale) - SUM(si.quantity * pc.average_cost)) /
     267           NULLIF(SUM(si.quantity * si.unit_price_at_sale), 0)) * 100, 2) AS profit_margin_pct
     268FROM category c
     269JOIN product p USING (category_id)
     270JOIN sale_item si USING (product_id)
     271JOIN ProductCosts pc USING (product_id)
     272GROUP BY c.name;
     273}}}
     274
     275'''Релациона алгебра:'''
     276{{{
     277ProductCosts ← γ product_id; AVG(unit_cost) → average_cost (purchase_order_item)
     278
     279Temp1 ← category ⨝ category_id=category_id product
     280
     281Temp2 ← Temp1 ⨝ product_id=product_id sale_item
     282
     283Temp3 ← Temp2 ⨝ product_id=product_id ProductCosts
     284
     285Result ← γ category.name → category_name;
     286           SUM(quantity × unit_price_at_sale) → gross_revenue,
     287           SUM(quantity × average_cost) → total_cost_of_goods,
     288           ROUND(((SUM(quantity × unit_price_at_sale) - SUM(quantity × average_cost)) /
     289                  NULLIF(SUM(quantity × unit_price_at_sale), 0)) × 100, 2) → profit_margin_pct
     290           (Temp3)
     291}}}
     292
     293----
     294
     295== 9. Анализа на „пазарна кошничка" (Product Affinity / Market Basket) ==
     296
     297Открива кои производи купувачите најчесто ги купуваат заедно во иста трансакција.
     298
     299{{{#!sql
     300SELECT
     301    p1.name AS product_a,
     302    p2.name AS product_b,
     303    COUNT(*) AS pair_occurrence_count
     304FROM sale_item si1
     305JOIN sale_item si2 ON si1.sale_id = si2.sale_id AND si1.product_id < si2.product_id
     306JOIN product p1 ON si1.product_id = p1.product_id
     307JOIN product p2 ON si2.product_id = p2.product_id
     308GROUP BY 1, 2
     309ORDER BY pair_occurrence_count DESC
     310LIMIT 10;
     311}}}
     312
     313'''Релациона алгебра:'''
     314{{{
     315Temp1 ← ρ si1 (sale_item)
     316
     317Temp2 ← ρ si2 (sale_item)
     318
     319Temp3 ← σ si1.sale_id = si2.sale_id ∧ si1.product_id < si2.product_id (Temp1 × Temp2)
     320
     321Temp4 ← Temp3 ⨝ si1.product_id = p1.product_id (ρ p1 (product))
     322
     323Temp5 ← Temp4 ⨝ si2.product_id = p2.product_id (ρ p2 (product))
     324
     325Temp6 ← γ p1.name → product_a, p2.name → product_b;
     326          COUNT(*) → pair_occurrence_count (Temp5)
     327
     328Result ← δ 10 (τ pair_occurrence_count DESC (Temp6))
     329}}}
     330
     331----
     332
     333== 10. Финансиска вредност на залихите (Stock Asset Valuation) ==
     334
     335Дава точен преглед на вкупната парична вредност на производите во магацините врз основа на последните набавни цени.
     336
     337{{{#!sql
     338SELECT
     339    w.name AS warehouse_location,
     340    SUM(ws.quantity_on_hand * (
     341        SELECT unit_cost FROM purchase_order_item poi
     342        WHERE poi.product_id = ws.product_id
     343        ORDER BY po_id DESC LIMIT 1
     344    )) AS total_inventory_valuation_mkd
     345FROM warehouse w
     346JOIN warehouse_stock ws USING (warehouse_id)
     347GROUP BY w.name;
     348}}}
     349
     350'''Релациона алгебра:'''
     351{{{
     352LatestCost(product_id) ← π product_id, unit_cost
     353                         (δ 1 (τ po_id DESC (purchase_order_item)))
     354
     355Temp1 ← warehouse ⨝ warehouse_id=warehouse_id warehouse_stock
     356
     357Temp2 ← Temp1 ⨝ product_id=product_id LatestCost
     358
     359Result ← γ warehouse.name → warehouse_location;
     360           SUM(quantity_on_hand × unit_cost) → total_inventory_valuation_mkd
     361           (Temp2)
     362}}}
     363
     364----
     365
     366'''Символи и операции:'''
     367* π - проекција (SELECT)
     368* σ - селекција (WHERE)
     369* ⨝ - природен спој (JOIN)
     370* ⟕ - left outer join (LEFT JOIN)
     371* × - Декартов производ (CROSS JOIN)
     372* γ - групирање (GROUP BY)
     373* τ - сортирање (ORDER BY)
     374* δ - лимит (LIMIT)
     375* ρ - преименување (AS / alias)
     376* ∧ - логичко И (AND)
     377* ∨ - логичко ИЛИ (OR)