A Manager's Guide to Data Warehousing by Laura Reeves

By Laura Reeves

Geared toward supporting enterprise and IT managers essentially speak with one another, this useful publication addresses issues straight-on and gives sensible the right way to development a collaborative info warehouse . You’ll get transparent reasons of the objectives and targets of every level of the knowledge warehouse lifecycle whereas studying the jobs that either company managers and technicians play at each one degree. Discussions of the main severe determination issues for achievement at each one section of the information warehouse lifecycle assist you comprehend ways that either company and IT administration could make judgements that most sensible meet unified targets.

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The Essentials of Data Warehousing Data warehousing is not new. Most large organizations have been investing in data warehousing for years. Currently, cost-effective technology is creating more possibilities for small and medium-size companies to build and deploy data warehouse solutions too. There are many stories about wild successes, and just as many about failed projects. With so much buzz about data warehousing, it is often assumed that everyone already knows the basics. However, many 3 4 Part I ■ The Essentials of Data Warehousing people are being exposed to these concepts for the first time.

If the technology does not work well, the effort to build the data warehouse may have been in vain. Roadblocks to Success Many organizations have failed in their data warehousing efforts. Some have struggled for years, while others have failed in a big and highly visible way. Some data warehouses have not failed outright, but have never achieved their full potential. While each case has unique characteristics, several common themes regularly contribute to failure or the lack of total success. Believing the Myth: ‘‘If You Build It, They Will Come’’ There are still many companies who invest in building a data warehouse by pulling data from core operational systems into a common database, expecting that the business will then begin to use it.

For example, the business must determine the criteria regarding who is considered a new customer. Is it when a new customer identifier is assigned in the order entry system? Is it when a customer is issued a new credit card or when that customer uses the card for the first time? Perhaps a customer is also considered new when he or she makes a purchase after a twelve-month lack of purchases. Even seemingly simple concepts require a bit more thought and understanding. Organizations that truly leverage their data do not leave these types of decisions to the technical staff, but work together to clarify and store useful data.

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