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Falling into the Project Deadline Trap
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Many organizations have invested in setting up procedures and processes that follow a project methodology Clearly, an important part of the process is de ning a project s scope Detailed project plans are developed and used to measure progress Group and individual performance are often based upon the ability to meet project deadlines While project planning and management are critical to coordinating multiple resources and keeping projects moving forward, this focus on the project plan itself can cause data warehousing initiatives to go awry The time needed to extract, transform, and load data for analytical applications (see 10) is one of the least understood and most often underestimated tasks of any systems development project This often leads to project delays One common way to manage these potential delays is to reduce the scope of what is to be delivered This can lead to nally delivering something on time, but the scope has been pared down so that no business value is delivered In other cases, testing and quality checks are reduced or eliminated in order to maintain the project schedule Unfortunately, many organizations reward this type of behavior Delivering something on time is a prevailing theme
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R E C O M M E N D A T I O N Reward project teams for producing quality results This includes validated data and well-tested applications This also means that applications indeed support the business in a valuable way It must not be acceptable to reduce the scope so that little or no value is delivered Part of this change in deadline focus also means that project change requests are viewed in a positive light Project issue logs should be full of open items needing to be addressed Teams should not be penalized for being honest about progress
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Failing to Uphold Organizational Discipline
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Despite an impression that data warehousing is glamorous, most of the work to build one is not The type of work needed to develop and implement a successful data warehouse is detailed and painstaking Project tasks are often
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Part I
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The Essentials of Data Warehousing
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tackled with excitement, but as the realities of the project sink in, enthusiasm begins to wane Data analysis may sound ne in a project plan, but having to crawl through hundreds of data elds is time-consuming, and can be dif cult as well Systems professionals have an aptitude and interest in this type of detailed data work Business professionals rarely do after all, if they did they would probably have become systems professionals! The primary areas of effort for a data warehouse revolve around the data itself When thinking about data, most people think about the technical aspects where the data is stored, what computer programs may access or use it and who to call in systems if you have a problem The technical care and feeding of data is only a part of the picture It is also important to understand the business de nition of each data element, why it matters to the organization, and how the data should or should not be used Resources must be assigned to work on these business aspects of data This is where true discipline comes into play It is much easier to simply move data around than it is to gure out what data is needed and then determine where to nd it This discipline is needed not only for the initial project, but also going forward into the future The need to develop and adhere to good data practices never ceases Organizations that have not been successful with other initiatives that require long-term discipline need to be up-front about this Strategies must be developed to ensure long-term discipline A lack of data discipline does not mean failure, it simply means that the business must be willing to accept and use data as it is This may be suf cient to support today s business needs
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