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Understanding Your BillAppendix DUNE Usage Bill___ONE/CLP Usage Bill Section Mapping How to Navigate Appendix D The table called Usage Mapping Document contains all the network call flows that IBS
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To fill out what is data mapping, follow these steps:
02
Understand the purpose of data mapping: Data mapping is the process of linking data elements from one dataset to another. It helps in transforming data from the source system to the target system.
03
Identify the source data: Determine where the data is coming from and the format in which it is stored. This could be a database, a file, or an API.
04
Understand the target data: Define the structure and format of the data in the target system. This could be another database, a data warehouse, or an application.
05
Analyze the data fields: Examine the data fields in the source and target data to identify any discrepancies or mismatches.
06
Create a mapping document: Document the mapping rules and transformations that need to be applied to each field. This document acts as a guide during the data mapping process.
07
Validate and test the data mapping: Perform test data mapping exercises to ensure the accuracy and quality of the mapped data.
08
Implement the data mapping: Use ETL (Extract, Transform, Load) tools or programming languages to carry out the actual data mapping based on the defined rules.
09
Monitor and maintain the data mapping: Regularly monitor the data mapping process and make necessary updates or modifications as per changing business requirements.
10
Document and share the data mapping results: Record the final data mapping results and share them with relevant stakeholders for future reference.

Who needs what is data mapping?

01
Data mapping is needed by individuals or organizations involved in data integration, migration, or transformation projects. Some examples of who needs data mapping include:
02
- Data analysts and data scientists who work with multiple datasets and need to align them for analysis.
03
- IT professionals responsible for integrating data from different systems.
04
- Business analysts who need to ensure consistent data across various business applications.
05
- Data architects and database administrators who design data storage and retrieval systems.
06
- Data engineers who develop data pipelines for data processing and ETL.
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Data mapping is the process of creating data element mappings between two distinct data models. It is often used in data integration, data migration, and data warehousing efforts.
Typically, organizations that handle data integration or migration must file data mapping documentation, especially if they are working with regulated data or transitioning data to a new system.
To fill out data mapping, identify the source data fields, define the target data fields, and document the transformations and rules applied to convert the data from the source to the target.
The purpose of data mapping is to ensure that data from one source aligns correctly with the data structure of another, facilitating accurate data transformation and integration.
Information reported on data mapping includes source and target data fields, data types, transformation rules, and any relevant metadata that supports understanding the data flow.
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