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Aug 6th, 2022
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the computer has a special vocabulary when it comes to storing information first of all it distinguishes carefully between this which is called a program and the information that you give to this program for the information that this program gives to you which is called data the reason that its called data is because the Latin for given happens to be datum plural data to stand for several pieces of given information when a large collection of data is organized systematically it is called a database in other words a database is a filing system which contains lots of files each of which contains lots of records each of which contains detailed items of information which are called fields for example if you had information about all the students in a school and all the books and all the pencils and if all this information were interrelated in a systematic way then you could call this a database and the information about one particular class of students could be called a file and the info

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Record level transformations are used to transform or augment individual fields of datasets during their movements between set transformations. They are used to create derived values by applying a lookup, function, or expression to the individual data fields.
To be effectively used in making decisions, data must go through a transformation process that involves six basic steps: 1) data collection, 2) data organization, 3) data processing, 4) data integration, 5) data reporting and finally, 6) data utilization.
Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system. Data transformation is a component of most data integration and data management tasks, such as data wrangling and data warehousing.
Data transformation includes two primary stages: understanding and mapping the data; and transforming the data.
Create a planned task. Create a baseline. Measure time and effort. Important planned task table fields. Planned task scripts. Planned task hierarchy. Configure rollup for planned task fields.
There are four types of transformations - translation, rotation, reflection, and dilation. Out of these, rotation, translation and reflection are rigid transformations.
During the transformation process, an analyst or engineer will determine the data structure. The most common types of data transformation are: Constructive: The data transformation process adds, copies, or replicates data. Destructive: The system deletes fields or records.
The most common types of data transformation are: Constructive: The data transformation process adds, copies, or replicates data. Destructive: The system deletes fields or records. Aesthetic: The transformation standardizes the data to meet requirements or parameters.
Data transformation is the process of converting data from one format to another, typically from the format of a source system into the required format of a destination system. Data transformation is a component of most data integration and data management tasks, such as data wrangling and data warehousing.
To create a Transform Event Script, switch to the Transform Scripts related list in a Transform Map and click the New button. The When option in the Transform Script trigger specifies when in the transformation process the script should run.

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