Traditional data warehouse projects follow a waterfall development model in which the project goes through distinct phases such as requirements gathering, design, development, testing, deployment, and stabilization. However, both business requirements and technology are complex in nature and the waterfall model can take six to nine months to fully implement a solution; by then business as well as technology has often changed considerably. The result is disappointed stakeholders and frustrated development teams. Agile development implements projects in an iterative fashion. Also known as the sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in the initial release, with refinements coming in a series of subsequent releases which are scheduled at regular intervals. An agile data warehousing approach greatly increases the likelihood of successful implementation on time and within budget. This article discusses agile development methodologies in data warehousing and business intelligence, implications of the agile methodology, managing changes in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates the impact of agility on the business.

The primary purpose of business intelligence is to improve the quality of decisions while decreasing the time it takes to make them. Because focus is required on internal as well as external factors, it is critical to decrease data latency, improve report performance and decrease systems resource consumption. This article will discuss the successful implementation of a BI reporting project directly against an OLTP planning solver. The planning solver imports data concerning supply, demand, capacity, bill of materials, inventory and the like. It then uses linear programming to determine the correct product mix to produce at various factories worldwide. The article discusses the challenges faced and a working model in which real-time BI was achieved by providing data to a separate BI server in an innovative way resulting in decreased latency, reduced resource consumption and improved performance. We demonstrated an alternative approach to hosting data for the BI application separately by loading BI and solver databases at the same time, resulting in faster access to information.

No abstract

Software development is a complex endeavor. While significant benefits can be achieved, the process is often laborious, time consuming and error prone requiring multiple iterations in order to achieve the desired result. Issues arise for numerous reasons – coding defects, unclear requirements, migration challenges, lack of convention, and inadequate testing to name a few. When convention and automation are introduced into the software development lifecycle there are significantly fewer opportunities for failure. Automation also allows for shorter development windows. Generally there are fewer errors throughout testing, with the bulk of those being found in unit and functional testing, far before the users get involved in systems acceptance testing. A data warehouse consists of multiple subject areas in which many tasks are common and should be automated for the sake of efficiency and enforcing convention. This article discusses a set of tools that can be used to automate writing data warehouse objects. The article also provides statistics of time saved using automation.

Software development is a complex endeavor. While significant benefits can be achieved, the process is often laborious, time consuming and error prone requiring multiple iterations in order to achieve the desired result. Issues arise for numerous reasons – coding defects, unclear requirements, migration challenges, lack of convention, and inadequate testing to name a few. When convention and automation are introduced into the software development lifecycle there are significantly fewer opportunities for failure. Automation also allows for shorter development windows. Generally there are fewer errors throughout testing, with the bulk of those being found in unit and functional testing, far before the users get involved in systems acceptance testing. A data warehouse consists of multiple subject areas in which many tasks are common and should be automated for the sake of efficiency and enforcing convention. This article discusses a set of tools that can be used to automate writing data warehouse objects. The article also provides statistics of time saved using automation.