What is a Six Sigma Strategy?
Six Sigma is a business management strategy that is used to improve the quality of process outputs by removing the reasons of defects in a manufacturing or business process. It includes statistical methods for creating special infrastructure within the organization.
The most important reason why corporations include six-sigma into data warehousing is because it affects the cost reduction in a positive manner. If the project is in early stages, data warehousing and six-sigma strategy will together allow for better planning, design and implementation.
The Basics of Data Warehousing
The components of data warehousing are multifaceted and complex in nature. They are either developed in-house or by a third party. While designing a data warehouse most of the designers focus on functional and business needs, leaving the performance constraints aside. This one mistake increases the possibility of missing deadlines and reworking on projects that reflect operational inefficiencies.
Today all the data warehouses designed are compatible for real time updating. We know that information extraction, transformation and loading are the most time consuming exercises in data warehousing. If the data structures are strategic and functional the importance of a data warehouse increases automatically.
How to Quantify the Data Warehouse Effect?
In recent times we have started treating warehouses as belonging to the same group or family. While designing a data warehouse you must dedicate each family to a particular geographical location as per the hierarchical data. The warehousing modules for individual data groups are developed at the initial stage and the new ones are just plugged into the main data warehouse. The three fundamental tables to store attributes of data, linking information and aggregated data ready for use are usually included in a data warehouse.
How Can You Apply Six Sigma Elements into Software Development
If you apply six sigma elements into data warehouse software development, it will help in easily identifying the potential problems in the production at the early stages of a project.
Another benefit of including the elements is that the task of data warehousing can give positive results if all the deployment plans are refined before implementation.
Data warehousing is necessary to remove the complexity of tasks in an organization. It has a self-assessing nature and provisions for internal auditing that can make the course of implementation easier. We cannot deny the fact that a data warehouse remains tied to the system architecture in which it is built and also makes highly accurate predictions in the always-fluctuating business environment.