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The primary reason that corporations introduce Six Sigma into data warehousing boils down to cost reduction. Large corporations are incurring huge expenditures, most

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

of the times running into millions of dollars, which eats into stakeholders margin, in creating and maintaining data warehouses. The criticality of data warehouses

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

Examples of combination products may in

can be understood by their vital role in support to prediction of business performance.

There is no denying the fact that data warehousing is in a way, the powerhou

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

se of Six Sigma deployment. In early stages of projects, data warehousing allows for better planning of deployment, design and tuning of the production environment.

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

Data Warehousing Basics

Data warehousing components are complex in nature and are multifaceted. The various components are either developed in house or by a third p

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

Combination pro

arty or in joint development at the partys place of business. Typically, designers focus on functional and business needs and not on performance constraints faced by

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

the production environment. The consequence of this costly mistake is the possibility of missing deadlines and reworking the project, which are manifestations of op

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

erational inefficiencies.

Challenges to Data Warehouse Design

It is not new that modern day data warehouses are built for auto refreshing and/or compatible for at

nation products and maximize the revenues. But the companies involved in this practice are overlooking that they are burdening the patients both economically

east real time updating. ETL, as extraction, transformation and loading of data flow is a very resource-consuming exercise in data warehousing. The importance of dat

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

a warehousing increases several times, considering the fact that data structures are both strategic and functional.

Even the real time refreshing of data becomes a

ts. Some of the combination products were well accepted by physicians while others suffered. Companies involved in development of combination products are fi

daunting task with the refresh window getting clogged straining server resources. Then there are some other factors that have a play in affecting the performance of

ding difficulty in defining their combination products and facing various challenges from selecting a combination to marketing it.

Following aspects would a

ETL.

Meeting the Challenge to Quantify the Data Warehouse Effect

Quantifying the effects of data warehouse is to project whether challenges can be scaled. The rece

dd to the challenges in developing combination products:

Which markets to tap where the combination products can do fairly well?
Which combination prod

t trend in data warehouse development is to treat them as belonging to the same family or group. Consider dedicating each family to a particular geographical locatio

cts are meaningful and rational?
Which therapeutic categories to select?
Which Combinations can address unmet needs of the patients?
Do combin

n, and other subsets of respective hierarchical data. Warehousing modules for individual data groups (families) are developed at their initial stages and new ones ar

tions increase the patient compliance?
What would be the developing cost?
How to tackle the risks encountered during combination product developmen

e taken care off as and when they arise and are just plugged into the main data warehouse. The database could contain three fundamental tables such as tables to stor

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

e attributes of data; storage of linking information; and finally, aggregated data ready for use.

Applying Six Sigma Elements into Software Development

Applying Si

ping new procedures for reviewing their safety, efficacy and quality.

Professional from academic institutions, pharmaceutical industries, health care indust

Sigma elements into software development typically helps in identifying potential problems in production if the development is done in the early stages of the proje

y and representatives from various regulatory agencies are working out to design the regulatory requirements for manufacture and sale of combination products

ct. Secondly, the mammoth task of data warehousing can return positive results if deployment plans are fine tuned before implementation.

The self-assessing nature a

.

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

nd the provisions for internal auditing shed light on the course of implementation. At the same time, one cannot forget that databases developed remain tied to the s

elopment. They need to be wiser in analyzing the market trends and the regulatory requirements.

Companies that provide selfless information through particip

ystem architecture on which they are built and bear heavily on the accuracy of predictions in a fluctuating business environment, ironically for which they are built

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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