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Data Transformation

   

Added on  2019-09-23

6 Pages1400 Words328 Views
Data Science and Big Data
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DATA TRANSFORMATIONJuly 25th, 2019INTRODUCTION TO THE DATA TRANSFORMATIONIn the field of computing, the concept such as data transformation tends to play a vitalrole. However, the given transformation is mainly useful for the researchers that are planning tomake an analysis of the collected data. In this regard, it is examined that in order to interpret theresult of the collected data, the researcher has to transform the data in some specific formatwhich is readable to his/her system or the software. If it is not done then in this situation aresearcher is not able to attain its goals and objectives in an effectual way.Thus, it can be said that data transformation is being regarded as the systematic processof converting the data from one format to another. It is being regarded as one of the mostfundamental aspects of the concept such as data integration. Data integration is the process ofcombining the data that are being resided in the different sources and it will also provide the userthe unified view of the data in an effectual way. On the other hand, it can also be said that there is a different type of activities areinvolved in the concept such as data transformation. It comprises converting the types of data,to perform the cleaning of the data by removing different duplicate and the null data, to enrichthe data and to carry out the aggregations, etc. Besides this, there are some benefits are alsoassociated with the data transformation. However, discussion about the same is carried outlater. DATA TRANSFORMATION PROCESSIn order to get more details about the concept such as data transformation, it is verymuch important for the individual that it should have a thorough understanding about the processwhich is being used for data transformation. The details about the same are depicted below:Data discovery: The process of the data transformation begins with the discovery ofdata. In accordance with the given context, it can be said that in the respective phasemainly profiling of the data is performed. However, with an aim to do the sameassistance is being taken from different profiling tools in an effectual way. Among all,1
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basically, the written profiling script is being used in this. This is used with an aim to geta better idea about the characteristics and structure of data. Data mapping: In the second step, it is being defined that how different individual fieldcan be mapped, joined, modified, aggregated and fitted together. This is done with an aimto perform the production of the final desired output. The mapping of data is being doneby the developer from the time when they start working on the specific type oftechnology. Code generation: It is being regarded as the third step of data transformation. Herein,different executable code is being generated that will help in the process of transformingthe data as per the desired data mapping rules. Typically, different data transformationtechnologies are used here in order to generate the code. Code execution: In the respective step, the code which is generated above is sent for theexecution purpose. The codes which are executed are being integrated into thetransformation tool. Data review: It is the final step in which programmer or the analyst will get the idea thatwhether the output of the data is fulfilling all the requirements of data transformation ornot. TYPE OF DATA TRANSFORMATIONTill now we have gathered much more information about the data transformation. Nowwe will discuss more about the different types of data transformation. In this context, thedetails about the same are given below:The data transformations are of two types such as batch data transformation and theinteractive data transformation.Batch data transformationTraditionally, the activity of the data transformation is being performed in the bulk orin the batch. In this regard, in the respective form of data transformation, the developers usedto write the code and they also used to perform the implementation of different transformationrules in the data integration tools in an effectual way. After doing the same, they perform theexecution of the generated code on the large volume of the data. The respective process tends tofollow the linear set of steps. In other words, it can also be depicted that batch data2
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