Six Sigma Strategy in data warehousing

A data warehousing system is used to gather information from different parts of the business process and then making them a part of a centralized database. In a broader sense, a data warehouse is the collection of data that is used by employees of an organization for easy and smooth working. Six Sigma is a business management strategy that is used to improve the quality of process outputs by removing the reasons for defects in a manufacturing or business process. It includes statistical methods for creating a special infrastructure within the organization.

The most important reason why organizations include six-sigma in data warehousing is because it affects the cost reduction in a positive manner. If the project is in the early stages, data warehousing and Six Sigma strategy will together allow for better planning, design and implementation.

Data warehousing components are complex in nature and are multifaceted. The various components are either developed in-house or by a third party or in joint development at the party’s place of business. Typically, designers focus on functional and business needs and not on performance constraints faced by the production environment. The consequence of this costly mistake is the possibility of missing deadlines and reworking the project, which are manifestations of operational inefficiencies.

It is not new that modern-day data warehouses are built for auto refreshing and/or compatible for at least real-time updating. ETL, as extraction, transformation and loading of data flow is a very resource-consuming exercise in data warehousing. The importance of data warehousing increases several times, considering the fact that data structures are both strategic and functional.

Even the real-time refreshing of data becomes a 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 ETL.

Quantifying the effects of a data warehouse is to project whether challenges can be scaled. The recent 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 location, and other subsets of respective hierarchical data. Warehousing modules for individual data groups (families) are developed at their initial stages and new ones are taken care of 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 store attributes of data; storage of linking information; and finally, aggregated data ready for use.

Applying Six Sigma elements into software development

Applying Six Sigma elements into software development typically helps in identifying potential problems in production if the development is done in the early stages of the project. Secondly, the mammoth task of data warehousing can return positive results if deployment plans are fine-tuned before implementation.

The self-assessing nature and 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 system 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.