Subjects - Business

In part 1 of this article series, we described the staging area and the ETL process of a data warehouse architecture.

According to USFDA, a combination product is one composed of any combination of a drug and device; biological product and device; drug and biological product

In the present and following article we shall describe the presentation area of the data warehouse. The term present

; or drug, device, and biological product and fixed dose combination would include two or more combinations of drug.

Examples of combination products may in

tion is used to denote the fact that this is the area, where data are presented to its Customers (the business analys

lude drug-coated devices, drugs packaged with delivery devices in medical kits, and drugs and devices packaged separately but intended to be used together.

s). There is no globally acceptable standard on the development of the data warehouse presentation area. Two major ap

here is enormous increase in the number of combination products entering the market in the recent years. Combination products have proven advantages but fixe

proaches have prevailed:· the dimensional datawarehouse approach (proposed by R. Kimball)·

d dose combinations are still in the process of convincing regulatory authority on their advantages over the single ingredient formulations.

Combination pro

the corporate information factory (CIF) approach (proposed by B. Inmon) Kimball approach
ucts have become life saving products for the pharmaceutical companies who doesn’t have many innovative molecules in their product pipeline and have been inc
According to the Kimball approach, the presentation area is made of a number of dimensional data structures, called
easingly used in the product life cycle management. Even the companies having product patents are trying to extend their product life cycle through the combi
star schemas. A star schema is a relational data structure which involves the following:
a fact table which s
nation products and maximize the revenues. But the companies involved in this practice are overlooking that they are burdening the patients both economically
ores all the measurements used to produce performance analytics and is linked to
a set of tables which capt
and physically. They need to rightly judge the benefits of the combination products and they have to even look at the risks involved when combining the produ
re the dimensional information, related to the above mentioned measurements. A set of linked star schemas w
ts. Some of the combination products were well accepted by physicians while others suffered. Companies involved in development of combination products are fi
ich focus on a single business process, are called a data mart. Star schemas are linked to each other, based on confo
ding difficulty in defining their combination products and facing various challenges from selecting a combination to marketing it.

Following aspects would a
rmed dimension tables (according to the Kimball parlor, this is called a bus architecture). The major advantage of th
dd to the challenges in developing combination products:

Which markets to tap where the combination products can do fairly well?
Which combination prod
dimensional data structure is derived from the symmetry and simplicity of the star schema, which:
is easily
cts are meaningful and rational?
Which therapeutic categories to select?
Which Combinations can address unmet needs of the patients?
Do combin
nderstood by business users, who can access and use it directly without database manipulation skills
performs
tions increase the patient compliance?
What would be the developing cost?
How to tackle the risks encountered during combination product developmen
better in the execution of complex queries, than complex normalized data structures (used commonly in operational sy
t?

As combination products don't fit into the traditional categories of drugs, medical devices, or biological products, the USFDA is in the process of devel
tems) The Kimball approach is criticized on the following points:
how feasible it is to connect d
ping new procedures for reviewing their safety, efficacy and quality.

Professional from academic institutions, pharmaceutical industries, health care indust
ta marts which capture information at a different level of detail. Linking of data marts is very important, since it
y and representatives from various regulatory agencies are working out to design the regulatory requirements for manufacture and sale of combination products
allows the combined analysis of data from different marts (a practice known as drill across).
normalized dat
.

As there is an increasing trend of the combination products companies manufacturing such products should be able to tackle the problems involved in the de
base structures reflect better complex entity type relationships, compared to the denormalised dimensional model. The
elopment. They need to be wiser in analyzing the market trends and the regulatory requirements.

Companies that provide selfless information through particip
Kimball approach proposes the exclusive use of denormalised structures. Copyright 2006 – Kostis Panayotaki

tion in industry events and feedback to regulatory authorities would be able to face the challenges and will be successful in developing combination products

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Subjects - Components of a Data Warehouse Architecture - Part 2, The Kimball Presentation Area

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