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Transformation Tools and Processes For data to become usable by managers, it must first go through a process known in IT-speak as ETL, for extract, transform, and load. While extract- ing data from its source and loading it into a repository are fairly straight- forward tasks, cleaning and transforming data is a bigger issue. In order to make the data in a warehouse decision-ready, it is neces- sary to first clean and validate it using business rules that use data cleans- ing tools such as Trillium. (For example, a simple rule might be to have a full nine-digit ZIP code for all U.S. addresses.) Transformation proce- dures define the business logic that maps data from its source to its des- tination. Both business and IT managers must expend significant effort in order to transform data into usable information. While automated tools from vendors such as Informatica Corporation, Ab Initio Software Corporation, and Ascential Software can ease this process, considerable manual effort is still required. Informatica's CEO Sohaib Abbasi esti- mates that "for every dollar spent on integration technology, around seven to eight dollars is spent on labor (for manual data coding)." Transformation also entails standardizing data definitions to make certain that business concepts have consistent, comparable definitions across the organization. For example, a "customer" may be defined as a company in one system but as an individual placing an order in another. It also requires managers to decide what to do about data that is missing. Sometimes it is possible to fill in the blanks using inferred data or authorized for use only by Zoey Luo in Enterprise Data Management- Spring 2020 taught by Kaushik Ghosh, Suffolk University from Jan 2020 to Jul 2020. For the exclusive use of Z. Luo, 2020. 14. BUILDING AN ANALYTICAL CAPABILITY projections based on available data; at other times, it simply remains missing and can't be used for analysis. These mundane but critical tasks require an ongoing effort, because new issues seem to constantly arise.

what is the role of transformation tools in the data management process?

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