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deal to wait a couple of days to meet with a key IT or business person, over the life of the project this can add eeks to the schedule just waiting to have the opportunity to ask a question Moreover, if the question cannot be answered by that individual, then the process begins again to gain access to the next person in the chain It is much better to create an environment where the data warehouse team is provided an open door directly to anyone (within reason!) This requires that both business and IT management communicate the importance of the data warehouse project to everyone else It also means that the data warehouse team must act responsibly and respect everyone s time Experience level of the team: There is a lot to learn when working on a data warehouse project, especially for the rst time It takes some time to learn data warehousing concepts and principles It also takes some time to learn and become ef cient with using any new technology Lack of access to the right IT people: Usually, several key people have knowledge of how a system works These IT people are in high demand, and the data warehouse team may have trouble scheduling time with them These individuals often play a critical role in keeping the operational system running and may be involved in other systems development projects Each of these items can increase the amount of time needed to design and build the ETL system This is also the part of the project where you are likely to have the largest number of resources all working on the project A small core group can gather requirements and develop the data model, but now many more people can work at the same time to build the ETL system Small organizations may still have a small core team (likely the same core team), whereas large enterprises may have a dozen or more people working on this All this work translates into dollars, for internal business and IT staff and third-party consultants.

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in managing project knowledge effectively were uncovered Capturing knowledge through post project reviews was found less successful mainly due to the time constraints for conducting it upon the completion of a project and the knowledge loss due to time lapse in capturing the knowledge gained Reassignment of people from one project to another was undermined by the high staff turnover in the industry and the weakness of human memory in memorising facts which it depends on for knowledge transfer The attempt to facilitate the sharing of knowledge through contractual and organisational arrangements also suffered from the fact that organisations collaborating on one project might be in competition in another project which makes them reluctant to share critical knowledge This was further aggravated by corporate restrictions on the transmission of knowledge and information Further review of existing literature suggested the need for a methodology that facilitates the capture and reuse of important knowledge from ongoing projects once it is created or identi ed (ie live ) across geographical boundaries It was established that the methodology could address the aforementioned knowledge loss problem which is due to time lapse in capturing knowledge from projects and staff turnover Furthermore, it would enable the knowledge captured from the initial stages of a project to be reused at the later stages of the project, and help to seize every knowledge reuse opportunity which would, in turn, help to maximise the value of reusing the knowledge captured The novelty of the aforementioned methodology was con rmed in subsequent literature reviews A number of research projects conducted to address the various issues of managing knowledge in construction were identi ed from existing literature However, these research projects were focused at strategic and business perspectives, speci c types of knowledge, speci c project phases or speci c types of construction organisation The need for an approach which is capable of capturing project knowledge, irrespective of the type of project, the type of construction organisation and project phases and particularly capturing the knowledge live , has not been adequately addressed Research at Stanford (Reiner and Fruchter, 2000) was considered as being closest to the goal of live capture and reuse of project knowledge Nonetheless, the research did not cover the entire project but focused only on the design evolution stage Hence, a case for developing the methodology was made Various concepts were explored, in particular learning histories (Kleiner and Roth, 1997) and Collaborative Learning (Digenti, 1999), in terms of the capability to facilitate the live capture and reuse of project knowledge The study of Collaborative Learning had indirectly led to the design of the methodology to capture knowledge through project meetings or eviews This was because Collaborative Learning showed that the interactions among the members of a team can help to reveal and share their tacit knowledge An insight was also gained from learning.

Convert Local Variable to Field Converts a local ariable into a field Extract Superclass Creates a common superclass from a set of sibling types The selected sibling types become direct subclasses of the extracted superclass after applying the refactoring Extract Interface Creates a new interface from a collection of selected methods and makes the selected class implement the interface Use Supertype Where Possible Replaces a type with one of its supertypes anywhere that transformation is possible Push Down Moves fields and methods from a class to one of its subclasses Pull Up Moves fields, methods, or member types from a class to one of its superclasses Extract Class Creates a new data class from a collection of fields Introduce Parameter Object Replaces a set of parameters with a new class, and updates all callers of the method to pass an instance of the new class as the value to the introduce parameter Introduce Indirection Creates a static indirection method delegating to the selected method Introduce Factory Replaces a constructor invocation with a call to a new factory method Introduce Parameter Replaces an expression with a parameter reference Encapsulate Field Replaces all direct references to a field with references to the field s getter and setter methods and creates those methods as necessary Generalize Declared Type Generalizes the type of variable declarations, parameters, fields, and method return types Infer Generic Type Arguments Attempts to infer type parameters for all generic type references in a class, package, or project This is especially useful when migrating from Java 14 code to Java 50 code To use any refactoring command, select the Java element or expression that you would like to refactor and then select the refactoring command Each refactoring dialog collects information appropriate to the task it needs to do Once you have supplied that information (for example, the new method name as shown in Figure 1 48), click the OK button to complete the refactoring.

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