S/4HANA Database Tables for Products, Material, and Equipment

In SAP S/4HANA, managing products, materials, and equipment involves various database tables that store detailed information about these entities. Understanding the hierarchy and relationships between these tables is crucial for effectively managing and accessing this data.

1. Overview of Key Tables

1.1 Material Master Tables

Material Master data is central to many business processes in SAP, including procurement, inventory management, and production. The main tables include:

  • MARA (General Material Data): Stores general data about materials, such as material type and industry sector.
  • MAKT (Material Descriptions): Contains material descriptions in various languages.
  • MARC (Plant Data for Material): Stores plant-specific data for materials.
  • MBEW (Material Valuation): Contains valuation data for materials at the plant level.
  • MVKE (Sales Data for Material): Stores sales-specific data for materials.
  • MARD (Storage Location Data for Material): Contains data about material quantities at storage locations.
  • MAW1 (Material Master: Warehouse Number Data): Stores warehouse-specific data.

1.2 Product and Equipment Tables

Product and equipment data in SAP S/4HANA is closely related to the Material Master but includes additional tables:

  • EQUI (Equipment Master Data): Contains data about individual pieces of equipment.
  • EQST (Equipment to BOM Link): Links equipment to Bill of Materials (BOM).
  • EQKT (Equipment Short Texts): Stores short descriptions for equipment.
  • IFLOT (Functional Location): Stores data about functional locations, which are hierarchical structures used to manage equipment.

2. Hierarchical Relationships Between Tables

The relationships between these tables form a complex hierarchy, with the Material Master at the core, linking to various other tables for plant-specific, sales-specific, and storage-specific data.

2.1 Material Master Table Relationships

  • MARA (General Material Data) is the central table and links to other tables:
    • MARC (Plant Data for Material) via MATNR (Material Number) and WERKS (Plant).
    • MAKT (Material Descriptions) via MATNR and SPRAS (Language Key).
    • MBEW (Material Valuation) via MATNR and BWKEY (Valuation Area).
    • MVKE (Sales Data for Material) via MATNR and VKORG (Sales Organization).
    • MARD (Storage Location Data for Material) via MATNR and LGORT (Storage Location).

2.2 Equipment and Functional Location Relationships

  • EQUI (Equipment Master Data) is linked to:
    • EQST (Equipment to BOM Link) via EQUNR (Equipment Number).
    • EQKT (Equipment Short Texts) via EQUNR.
    • IFLOT (Functional Location) via TPLNR (Functional Location Number).

2.3 Hierarchical Structure Example

MARA (General Material Data)
├── MARC (Plant Data for Material)
├── MAKT (Material Descriptions)
├── MBEW (Material Valuation)
├── MVKE (Sales Data for Material)
└── MARD (Storage Location Data for Material)

EQUI (Equipment Master Data)
├── EQST (Equipment to BOM Link)
└── EQKT (Equipment Short Texts)
    └── IFLOT (Functional Location)

3. Important Table Relationships

  • MARA-MATNR (Material Number) is the primary key that connects to MARC, MAKT, MBEW, MVKE, and MARD.
  • MARC-WERKS (Plant) connects material data to specific plants.
  • MAKT-SPRAS (Language Key) allows material descriptions in multiple languages.
  • EQUI-EQUNR (Equipment Number) is the key for linking to EQST and EQKT.
  • IFLOT-TPLNR (Functional Location Number) links equipment to its functional location.

4. Example Queries

4.1 Retrieve Material Information with Plant Data

SELECT * FROM mara
  INNER JOIN marc ON mara~matnr = marc~matnr
  WHERE mara~matnr = 'MAT001'.

SELECT * FROM equi
  INNER JOIN eqst ON equi~equnr = eqst~equnr
  WHERE equi~equnr = 'EQ001'.

Conclusion

Understanding the hierarchy and relationships between these S/4HANA database tables is essential for effectively managing and retrieving data related to products, materials, and equipment. This knowledge enables developers and analysts to write efficient queries and build robust applications that interact seamlessly with SAP's complex data structure.