Context Navigation

Changes between Version 3 and Version 4 of AdvancedReports

Timestamp:: 01/21/26 04:03:45 (6 days ago)
Author:: 221181
Comment:: --

Legend:

: Unmodified
: Added
: Removed
: Modified

AdvancedReports

-              v3
+              v4
 ----
+== 1. ABC Анализа на производи (ABC Product Analysis) ==
+Овој 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.
+{{{#!sql
+WITH ProductRevenue AS (
+    SELECT
+        p.name AS product_name,
+        SUM(si.quantity * si.unit_price_at_sale) AS total_revenue
+    FROM product p
+    JOIN sale_item si ON p.product_id = si.product_id
+    GROUP BY p.name
+),
+RevenueCalculations AS (
+    SELECT
+        product_name,
+        total_revenue,
+        SUM(total_revenue) OVER (ORDER BY total_revenue DESC) / SUM(total_revenue) OVER () AS cumulative_share
+    FROM ProductRevenue
+)
+SELECT
+    product_name,
+    ROUND(total_revenue, 2) AS revenue_mkd,
+    CASE
+        WHEN cumulative_share <= 0.80 THEN 'A (High Value)'
+        WHEN cumulative_share <= 0.95 THEN 'B (Medium Value)'
+        ELSE 'C (Low Value)'
+    END AS abc_classification
+FROM RevenueCalculations;
+}}}
+'''Релациона алгебра:'''
+{{{
+ProductRevenue ← γ name; SUM(quantity × unit_price_at_sale) → total_revenue (product ⨝ product_id sale_item)
+RevenueCalculations ← π product_name, total_revenue,
+                        (RunningSum(total_revenue) / TotalSum(total_revenue)) → cumulative_share
+                        (τ total_revenue DESC (ProductRevenue))
+Result ← π product_name,
+           ROUND(total_revenue, 2) → revenue_mkd,
+           CASE(cumulative_share ≤ 0.80 → 'A',
+                cumulative_share ≤ 0.95 → 'B',
+                ELSE → 'C') → abc_classification
+           (RevenueCalculations)
+}}}
+----
+== 2. Месечен тренд на продажба (Monthly Sales Growth Trend) ==
+Ги споредува приходите од тековниот месец со претходниот за да го пресмета процентот на раст или пад на бизнисот.
+{{{#!sql
+WITH MonthlySales AS (
+    SELECT
+        DATE_TRUNC('month', date_time) AS sales_month,
+        SUM(total_amount) AS revenue
+    FROM sale
+    GROUP BY 1
+)
+SELECT
+    sales_month,
+    revenue AS current_month_revenue,
+    LAG(revenue) OVER (ORDER BY sales_month) AS previous_month_revenue,
+    ROUND(((revenue - LAG(revenue) OVER (ORDER BY sales_month)) /
+           NULLIF(LAG(revenue) OVER (ORDER BY sales_month), 0)) * 100, 2) AS growth_percentage
+FROM MonthlySales;
+}}}
+'''Релациона алгебра:'''
+{{{
+MonthlySales ← γ DATE_TRUNC('month', date_time) → sales_month;
+                 SUM(total_amount) → revenue (sale)
+Result ← π sales_month,
+           revenue → current_month_revenue,
+           LAG(revenue) → previous_month_revenue,
+           ROUND(((revenue - LAG(revenue)) / NULLIF(LAG(revenue), 0)) × 100, 2) → growth_percentage
+           (τ sales_month ASC (MonthlySales))
+}}}
+----
+== 3. Состојба на залихи и критични точки (Inventory Health & Reorder Levels) ==
+Ги идентификува производите што се под минимумот во магацините и дава аларм за итна набавка.
+{{{#!sql
+SELECT
+    p.name AS product_name,
+    w.name AS warehouse_location,
+    ws.quantity_on_hand,
+    p.reorder_level,
+    CASE
+        WHEN ws.quantity_on_hand <= p.reorder_level THEN 'CRITICAL: REORDER'
+        WHEN ws.quantity_on_hand <= p.reorder_level * 1.5 THEN 'WARNING: LOW'
+        ELSE 'HEALTHY'
+    END AS stock_status
+FROM product p
+JOIN warehouse_stock ws ON p.product_id = ws.product_id
+JOIN warehouse w ON ws.warehouse_id = w.warehouse_id;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← product ⨝ product_id=product_id warehouse_stock
+Temp2 ← Temp1 ⨝ warehouse_id=warehouse_id warehouse
+Result ← π product.name → product_name,
+           warehouse.name → warehouse_location,
+           quantity_on_hand,
+           reorder_level,
+           CASE(quantity_on_hand ≤ reorder_level → 'CRITICAL: REORDER',
+                quantity_on_hand ≤ reorder_level × 1.5 → 'WARNING: LOW',
+                ELSE → 'HEALTHY') → stock_status
+           (Temp2)
+}}}
+----
+== 4. Перформанси на добавувачите (Supplier Performance Matrix) ==
+Го мери доцнењето на испораките од добавувачите и ја пресметува нивната доверливост во исполнување на роковите.
+{{{#!sql
+SELECT
+    s.name AS supplier_name,
+    COUNT(po.po_id) AS total_orders,
+    AVG(po.actual_delivery_date - po.expected_delivery_date) AS average_delay_days,
+    ROUND(COUNT(CASE WHEN po.actual_delivery_date <= po.expected_delivery_date THEN 1 END) * 100.0 / COUNT(*), 2) AS on_time_delivery_rate
+FROM supplier s
+JOIN purchase_order po ON s.supplier_id = po.supplier_id
+WHERE po.status = 'DELIVERED'
+GROUP BY s.name;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← supplier ⨝ supplier_id=supplier_id purchase_order
+Temp2 ← σ status='DELIVERED' (Temp1)
+Result ← γ supplier.name → supplier_name;
+           COUNT(po_id) → total_orders,
+           AVG(actual_delivery_date - expected_delivery_date) → average_delay_days,
+           ROUND(COUNT(actual_delivery_date ≤ expected_delivery_date) × 100.0 / COUNT(*), 2) → on_time_delivery_rate
+           (Temp2)
+}}}
+----
+== 5. RFM Анализа на клиенти (Customer RFM Segmentation) ==
+Ги сегментира купувачите според тоа кога последен пат купувале, колку често се враќаат и колку пари потрошиле.
+{{{#!sql
+SELECT
+    c.name AS customer_name,
+    EXTRACT(DAY FROM CURRENT_TIMESTAMP - MAX(s.date_time)) AS recency_days,
+    COUNT(s.sale_id) AS frequency_count,
+    SUM(s.total_amount) AS monetary_total,
+    NTILE(5) OVER (ORDER BY MAX(s.date_time)) AS r_score,
+    NTILE(5) OVER (ORDER BY COUNT(s.sale_id)) AS f_score,
+    NTILE(5) OVER (ORDER BY SUM(s.total_amount)) AS m_score
+FROM customer c
+JOIN sale s USING (customer_id)
+GROUP BY c.customer_id, c.name;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← customer ⨝ customer_id=customer_id sale
+Result ← γ customer_id, name → customer_name;
+           EXTRACT(DAY FROM CURRENT_TIMESTAMP - MAX(date_time)) → recency_days,
+           COUNT(sale_id) → frequency_count,
+           SUM(total_amount) → monetary_total,
+           NTILE(5, MAX(date_time)) → r_score,
+           NTILE(5, COUNT(sale_id)) → f_score,
+           NTILE(5, SUM(total_amount)) → m_score
+           (Temp1)
+}}}
+----
+== 6. Искористеност на капацитетот на магацините (Warehouse Utilization Rate) ==
+Пресметува колкав процент од физичкиот простор во секој магацин е моментално пополнет.
+{{{#!sql
+SELECT
+    w.name AS warehouse_name,
+    w.capacity AS total_unit_capacity,
+    SUM(ws.quantity_on_hand) AS units_in_stock,
+    ROUND((SUM(ws.quantity_on_hand)::NUMERIC / w.capacity) * 100, 2) AS occupancy_percentage
+FROM warehouse w
+LEFT JOIN warehouse_stock ws ON w.warehouse_id = ws.warehouse_id
+GROUP BY w.warehouse_id, w.name, w.capacity;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← warehouse ⟕ warehouse_id=warehouse_id warehouse_stock
+Result ← γ warehouse_id, name → warehouse_name, capacity → total_unit_capacity;
+           SUM(quantity_on_hand) → units_in_stock,
+           ROUND((SUM(quantity_on_hand) / capacity) × 100, 2) → occupancy_percentage
+           (Temp1)
+}}}
+----
+== 7. Анализа на застојни производи ==
+Ги прикажува производите што не се продале во последните 90 дена и само зафаќаат простор и капитал.
+{{{#!sql
+SELECT
+    p.name AS product_name,
+    p.sku,
+    ws.quantity_on_hand,
+    COALESCE(MAX(s.date_time)::TEXT, 'NO SALES RECORDED') AS last_sold_date
+FROM product p
+JOIN warehouse_stock ws ON p.product_id = ws.product_id
+LEFT JOIN sale_item si ON p.product_id = si.product_id
+LEFT JOIN sale s ON si.sale_id = s.sale_id
+GROUP BY p.product_id, p.name, p.sku, ws.quantity_on_hand
+HAVING MAX(s.date_time) < CURRENT_DATE - INTERVAL '90 days' OR MAX(s.date_time) IS NULL;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← product ⨝ product_id=product_id warehouse_stock
+Temp2 ← Temp1 ⟕ product_id=product_id sale_item
+Temp3 ← Temp2 ⟕ sale_id=sale_id sale
+Temp4 ← γ product_id, name, sku, quantity_on_hand;
+          MAX(date_time) → last_sold_date (Temp3)
+Result ← π name → product_name, sku, quantity_on_hand,
+           COALESCE(last_sold_date::TEXT, 'NO SALES RECORDED') → last_sold_date
+           (σ last_sold_date < CURRENT_DATE - 90 ∨ last_sold_date IS NULL (Temp4))
+}}}
+----
+== 8. Маржа на профит по категорија (Category Profit Margin) ==
+Ја пресметува разликата помеѓу продажната и набавната цена за секоја категорија производи.
+{{{#!sql
+WITH ProductCosts AS (
+    SELECT product_id, AVG(unit_cost) AS average_cost FROM purchase_order_item GROUP BY 1
+)
+SELECT
+    c.name AS category_name,
+    SUM(si.quantity * si.unit_price_at_sale) AS gross_revenue,
+    SUM(si.quantity * pc.average_cost) AS total_cost_of_goods,
+    ROUND(((SUM(si.quantity * si.unit_price_at_sale) - SUM(si.quantity * pc.average_cost)) /
+           NULLIF(SUM(si.quantity * si.unit_price_at_sale), 0)) * 100, 2) AS profit_margin_pct
+FROM category c
+JOIN product p USING (category_id)
+JOIN sale_item si USING (product_id)
+JOIN ProductCosts pc USING (product_id)
+GROUP BY c.name;
+}}}
+'''Релациона алгебра:'''
+{{{
+ProductCosts ← γ product_id; AVG(unit_cost) → average_cost (purchase_order_item)
+Temp1 ← category ⨝ category_id=category_id product
+Temp2 ← Temp1 ⨝ product_id=product_id sale_item
+Temp3 ← Temp2 ⨝ product_id=product_id ProductCosts
+Result ← γ category.name → category_name;
+           SUM(quantity × unit_price_at_sale) → gross_revenue,
+           SUM(quantity × average_cost) → total_cost_of_goods,
+           ROUND(((SUM(quantity × unit_price_at_sale) - SUM(quantity × average_cost)) /
+                  NULLIF(SUM(quantity × unit_price_at_sale), 0)) × 100, 2) → profit_margin_pct
+           (Temp3)
+}}}
+----
+== 9. Анализа на „пазарна кошничка" (Product Affinity / Market Basket) ==
+Открива кои производи купувачите најчесто ги купуваат заедно во иста трансакција.
+{{{#!sql
+SELECT
+    p1.name AS product_a,
+    p2.name AS product_b,
+    COUNT(*) AS pair_occurrence_count
+FROM sale_item si1
+JOIN sale_item si2 ON si1.sale_id = si2.sale_id AND si1.product_id < si2.product_id
+JOIN product p1 ON si1.product_id = p1.product_id
+JOIN product p2 ON si2.product_id = p2.product_id
+GROUP BY 1, 2
+ORDER BY pair_occurrence_count DESC
+LIMIT 10;
+}}}
+'''Релациона алгебра:'''
+{{{
+Temp1 ← ρ si1 (sale_item)
+Temp2 ← ρ si2 (sale_item)
+Temp3 ← σ si1.sale_id = si2.sale_id ∧ si1.product_id < si2.product_id (Temp1 × Temp2)
+Temp4 ← Temp3 ⨝ si1.product_id = p1.product_id (ρ p1 (product))
+Temp5 ← Temp4 ⨝ si2.product_id = p2.product_id (ρ p2 (product))
+Temp6 ← γ p1.name → product_a, p2.name → product_b;
+          COUNT(*) → pair_occurrence_count (Temp5)
+Result ← δ 10 (τ pair_occurrence_count DESC (Temp6))
+}}}
+----
+== 10. Финансиска вредност на залихите (Stock Asset Valuation) ==
+Дава точен преглед на вкупната парична вредност на производите во магацините врз основа на последните набавни цени.
+{{{#!sql
+SELECT
+    w.name AS warehouse_location,
+    SUM(ws.quantity_on_hand * (
+        SELECT unit_cost FROM purchase_order_item poi
+        WHERE poi.product_id = ws.product_id
+        ORDER BY po_id DESC LIMIT 1
+    )) AS total_inventory_valuation_mkd
+FROM warehouse w
+JOIN warehouse_stock ws USING (warehouse_id)
+GROUP BY w.name;
+}}}
+'''Релациона алгебра:'''
+{{{
+LatestCost(product_id) ← π product_id, unit_cost
+                         (δ 1 (τ po_id DESC (purchase_order_item)))
+Temp1 ← warehouse ⨝ warehouse_id=warehouse_id warehouse_stock
+Temp2 ← Temp1 ⨝ product_id=product_id LatestCost
+Result ← γ warehouse.name → warehouse_location;
+           SUM(quantity_on_hand × unit_cost) → total_inventory_valuation_mkd
+           (Temp2)
+}}}
+----
+'''Символи и операции:'''
+* π - проекција (SELECT)
+* σ - селекција (WHERE)
+* ⨝ - природен спој (JOIN)
+* ⟕ - left outer join (LEFT JOIN)
+* × - Декартов производ (CROSS JOIN)
+* γ - групирање (GROUP BY)
+* τ - сортирање (ORDER BY)
+* δ - лимит (LIMIT)
+* ρ - преименување (AS / alias)
+* ∧ - логичко И (AND)
+* ∨ - логичко ИЛИ (OR)
+== 1.  ==