Despite the sometimes religious wars of dimensional modeling vs. third normal form, the truth is that you need both in order to answer the business needs of real world.

Dimensional Modeling (DM) is a favorite modeling technique in data warehousing. In DM, a model of tables and relations is constituted with the purpose of optimizing decision support query performance in relational databases, relative to a measurement or set of measurements of the outcome(s) of the business process being modeled.

Practitioners of DM have approached developing a logical data model by selecting the business process to be modeled and then deciding what each individual low level record in the "fact table" (the grain of the fact table) will mean. The fact table is the focus of dimensional analysis.

It is the table dimensional queries segment in the process of producing solution sets. The criteria for segmentation are contained in one or more "dimension tables" whose single part primary keys become foreign keys of the related fact table in DM designs. The foreign keys in a related fact table constitute a multi-part primary key for that fact table, which, in turn, expresses a many-to-many relationship.

In a DM further, the grain of the fact table is usually a quantitative measurement of the outcome of the business process being analyzed. Dimension tables are generally composed of attributes, measured on some discrete category scale that describe, qualify, locate, or constrain the fact table quantitative measurements.

In contrast, conventional E-R (3nf) models are constituted to
(a) Remove redundancy in the data model
(b) Facilitate retrieval of individual records having certain critical identifiers and
(c) Therefore, optimize On-line Transaction Processing (OLTP) performance.

Third normal form is a model of entities, relationships, and attributes. It usually represents our world in a logical, mathematical sort of way, like the "who, what, when, and where" approach to journalism. Any departure from this "normal" model is called de-normalization.

We have deep expertise of above modeling techniques which gives you choices by letting you physically implement either or mixed logical model.