What Data Modeling Methods Are Supported by DataArts Architecture?

DataArts Studio DataArts Architecture supports Entity Relationship (ER) modeling and dimensional modeling:

• ER modeling

  ER modeling describes the business activities within an enterprise. Compliant with the third normal form (3NF), ER modeling is designed for data integration. It is used for combining and merging data with similarities by subject. ER modeling results cannot be used directly for decision-making, but they are a useful tool.

  You can divide ER modeling into three levels of abstraction: design conceptual models, logical models, and physical models.

  • Conceptual model: A conceptual model is a representation of business processes and business data involved in different activities. It can be used to represent the relationships between business entities.
  • Logical model: A logical model is more detailed than a conceptual model. It is used to outline the entities, attributes, and relationships of a business. It enables communication between IT and business staff. A logical model is a set of standardized logic table structures. Determined by business rules, a logical model outlines business objects, data items of the business objects, and relationships between business objects.
  • Physical model: A physical model is based on logical models and is used to design the database architecture for data storage with a range of technical factors all considered. For example, the selected data warehouse could be defined as DWS.
• Dimensional modeling

  Dimensional modeling is the construction of models based on analysis and decision-making requirements. It is mainly used for data analysis. Dimensional modeling is focused on how to quickly analyze user requirements and respond rapidly to complicated large-scale queries.

  A multidimensional model is a fact table that consists of numeric measurement metrics. The fact table is associated with a group of dimensional tables that contain description attributes through primary or foreign keys.

  Typical dimensional models include star models and snowflake models used in some special scenarios.

  In the DataArts Architecture module of DataArts Studio, dimensional modeling involves constructing bus matrices to extract business facts and dimensions for model creation. You need to sort out business requirements for constructing metric systems and creating summary models.