A Manager's Guide to Data Warehousing by Laura Reeves

By Laura Reeves

Aimed toward assisting company and IT managers in actual fact converse with one another, this beneficial booklet addresses matters straight-on and gives sensible how you can development a collaborative info warehouse . You’ll get transparent motives of the objectives and ambitions of every level of the knowledge warehouse lifecycle whereas studying the jobs that either enterprise managers and technicians play at every one level. Discussions of the main severe choice issues for achievement at every one section of the knowledge warehouse lifecycle assist you comprehend ways that either enterprise and IT administration could make judgements that most sensible meet unified goals.

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The return on any individual decision may be small. A lot of small, better decisions can add up to a significant impact on the bottom line. While there have certainly been cases, often highly publicized, where a single decision Chapter 1 ■ Gaining Data Warehouse Success resulted in multimillion-dollar results, it is more likely for a business to see benefits from many small decisions. The data warehouse provides the keys that unlock the data’s value. There are several common expectations regarding what a data warehouse should be able to do.

One common way to manage these potential delays is to reduce the scope of what is to be delivered. This can lead to finally 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. R E C O M M E N D A T I O N Reward project teams for producing quality results.

A data warehouse can indeed provide a single repository for all of your data, but that alone is not enough to ensure that all reports will be consistent. Clean, trusted data from the data warehouse is often pulled out, further manipulated, possibly loaded into yet another database, and finally presented on reports. The use of different formulae for calculations, and the criteria used to include or exclude data from the result set, can cause significant differences in what is shown on a report. The effort of loading data into a data warehouse is not enough to fulfill the promise of a single version of the truth.

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