Data modeling overview

A data model identifies the data, the data attributes, and the relationships or associations with other data. It provides a generalized, user-defined view of data that represents the real business scenario and data.

You need to create a data model to understand how to design your database and meet the data modeling requirements for your enterprise. You will use this data model to structure and organize the data.

A data model consists of data objects and workstation data values. The item and category objects are the core objects in the data model, which are defined by the spec object. A collection of item objects is a catalog. The hierarchy object defines a hierarchical form of a collection of categories.

Data modeling is the process of creating a data model. When you create a data model, you define the data and its attributes and relationships with other data and you define constraints or limitations on the data. For example, you might create a data model for a product where the vendor attribute of the product item links to a vendor id in a vendor catalog.

To determine which components to model, you must have a good understanding of the Product Information Management (PIM) domain, IBM® InfoSphere® Master Data Management Collaboration Server, and client requirements.

The data modeling factors include user interface (UI), workflows, and search.
User Interface
The user interface affects the data model for enabling the business processes. For example, if the multi-edit feature is required for the business, then you must model the UI accordingly.
The data model must support the workflow by providing an end-to-end business process with step-based views and user roles. You must test a prototype of the typical business processes and perform a conceptual dry run to check whether the data model design is constraining the use of native workflows.
The data model must facilitate searching. You must understand how users will search for product data before you create the data model. The data model must support the searching and require little UI customization for users.
Note: All attributes of an item are stored in serialized form in the database as a blob, and cannot be searched directly. The only attributes marked as indexed gets stored within a relational table as well to enable fast and easy search. Therefore, when designing the data model you need to make sure to mark only those attributes as indexed that need to be searched on a regular basis. However, avoid to index all attributes as it will increase disk space demand on database server side, thereby, affecting the performance of accessed data.

To create a data model, you must consider the product attributes, foundation data, and product classifications.

Product attributes

Product attributes are a set of attributes that define a product.

Product attributes are typically grouped into a set of core and extension attributes. The core attributes are common for all the enterprise products, for example, the UPC attribute. The extension attributes are specific to certain product types or categories, for example, the screen size attribute. InfoSphere MDM Collaboration Server also supports relationship data, for example, cross-sell, up-sell, and other relationship data.

InfoSphere MDM Collaboration Server serves as a system of record for referential attributes.
  • Handle the attributes that are transactional or volatile in nature outside of a Product Information Management (PIM) system by using the appropriate consuming applications. For example, current price is handled by a pricing engine.
  • Do not model attributes whose values are derived by business logic from the external applications in your PIM system. You can keep such data in a PIM system as read only, but if you do this, you need an update mechanism to keep the data in sync. In addition, keeping such data in a PIM system can add unnecessary load and high availability requirements.

Foundation data

Foundation data encompasses any supporting entities and attribute values that are needed for defining a product. For example, foundation data includes a list of suppliers, locations, product brands, and other information.

Product classifications

The product classifications define how the products are grouped together. You can group products together for a specific business purpose such as organizational structure or for ease of navigation. A product can be categorized in multiple ways. For example, you can categorize the furniture product into kitchen furniture, drawing room furniture, bed room furniture, and study room furniture.

Last updated: 22 May 2018