[仅限PaaS]{class="badge informative" title="仅适用于云项目(Adobe管理的PaaS基础架构)和内部部署项目上的Adobe Commerce 。"}

分析库存水平

本主题将演示如何设置功能板,该功能板提供有关当前库存的洞察信息,并包含有关旧架构或新架构的客户端说明。 如果您在​ Data Warehouse Views ​菜单下没有​ Manage Data ​选项,则表示您使用的是旧版架构。 如果您使用的是旧架构,请在到达以下计算列说明中的指定部分后,提交主题为​ INVENTORY ANALYSIS ​的​ 新支持请求

要跟踪的列:

要跟踪指令的列

  • cataloginventory_stock_item ​表:

    • item_id
    • product_id
    • qty
  • catalog_product_entity ​表:

    • entity_id
    • sku
    • created_at

计算列:

新架构
  • catalog_product_entity ​表:

    • Product's most recent order date

      • Column type: Many to One

      • Column equation: MAX
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: created_at
      • Filters:
        • [A] Ordered products we count
    • Product's first order date

      • Column type: Many to One

      • Column equation: MIN
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: created_at
      • Filters:
        • [A] Ordered products we count
    • Seconds since product's most recent order date

      • Column type: Same Table

      • Column equation: AGE
      • 选择DATETIME column: Product's most recent order date
    • Product's lifetime number of items sold

      • Column type: Many to One

      • Column equation: SUM
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: qty_ordered
      • Filters:
        • [A] Ordered products we count
    • Avg products sold per week (all time)

      • Column type: Same Table


      • Column equation: CALCULATION

      • Column输入:

        • A: Product's lifetime number of items sold
        • B: Product's first order date

      • Datatype: Decimal

      • 定义:

        • 当A为null或B为null时,则为null,否则第(A::decimal/(extract(epoch from (current_timestamp - B))::decimal/604800.0),2)末尾
  • cataloginventory_stock_item ​表:

    • Sku

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: sku
    • Product's lifetime number of items sold

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Product's lifetime number of items sold
    • Seconds since product's most recent order date

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Seconds since product's most recent order date
    • Avg products sold per week (all time)

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Avg products sold per week (all time)
    • Weeks on hand

      • Column type: Same Table


      • Column equation: CALCULATION

      • Column输入:

        • A: qty
        • B: Avg products sold per week (all time)

      • Datatype: Decimal

      • 定义:

        • 当A为null或B为null或B = 0.0时为null,否则以round(A::decimal/B,2)结束
旧式架构
  • catalog_product_entity ​表:

    • Product's most recent order date

      • Column type: Many to One

      • Column equation: MAX
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: created_at
      • Filters:
        • [A] Ordered products we count
    • Product's first order date

      • Column type: Many to One

      • Column equation: MIN
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: created_at
      • Filters:
        • [A] Ordered products we count
    • Seconds since product's most recent order date

      • Column type: Same Table

      • Column equation: AGE
      • 选择DATETIME列: Product's most recent order date
    • Product's lifetime number of items sold

      • Column type: Many to One

      • Column equation: SUM
      • Path: sales_order_item.product_id => catalog_product_entity.entity_id
      • 选择column: qty_ordered
      • Filters:
        • [A] Ordered products we count
    • Avg products sold per week (all time)

      • 由分析人员在提交​ [库存分析] ​支持请求时创建
  • cataloginventory_stock_item ​表:

    • Sku

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: sku
    • Product's lifetime number of items sold

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Product's lifetime number of items sold
    • Seconds since product's most recent order date

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Seconds since product's most recent order date
    • Avg products sold per week (all time)

      • Column type: One to Many

      • Column equation: JOINED_COLUMN
      • Path: cataloginventory_stock_item.product_id => catalog_product_entity.entity_id
      • 选择column: Avg products sold per week (all time)
    • Weeks on hand

      • 在您提交您的​ INVENTORY ANALYSIS ​支持请求时由分析人员创建

量度

量度说明

  • cataloginventory_stock_item ​表:

    • Inventory on hand:此量度执行

      • 总和 ​位于
      • qty ​列排序依据
      • [无]列

报告

报表说明

  • Inventory on hand by sku

    • Metric: Inventory on hand

    • Time period: All time

    • 时间间隔: None

    • Group by:

      • Sku
      • Weeks on hand

    • Chart type: Table

  • Inventory with less than 2 weeks on hand (order now)

    • Metric: Inventory on hand

      • Filters:
        • [A] Weeks on hand < 2
    • Time period: All time

    • 时间间隔: None


    • 分组依据: Sku


    • Chart type: Table

  • Inventory with more than 26 weeks on hand (put on sale)

    • Metric: Inventory on hand

      • Filters:
        • [A] Weeks on hand > 26
    • Time period: All time

    • 时间间隔: None


    • 分组依据: Sku


    • Chart type: Table

如果您在构建此分析时遇到任何问题,或只是想与专业服务团队接洽,请联系支持人员

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