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What Exactly Is Data Mapping?

All Marketing Tips - April 2, 2024

What Exactly Is Data Mapping?

 

Data Mapping: The method of matching fields of data in one source to information fields in another is known as data mapping. It aids in making sure that information from one source may be appropriately converted or moved to another location without compromising its accuracy, consistency, or significance. Any info process, particularly ETL and info integration, starts with data mapping.

Table of Contents

  • Process of Data Mapping
    • Data Migration:
    • Enhancing Data Quality:
    • Determine the Sources of Data:
    • Comply with the fields:
    • Evaluate and Program:
  • Data Transfer
  • Data Conversion

Process of Data Mapping

Now that you are clear on what info mapping is, let us take you step-by-step through the procedure.

Describe the Project’s Scope: Clearly state the goals of the information’s mapping process, along with the information that must be transferred and why. Typical data mapping goals include the following: 

Integration of Data: You could have information from several sources, and

It might need to be combined into a single, standardized format. To have a comprehensive understanding of your clients, you might choose to merge customer information from your online store, mobile application, and physical storefronts.

Process of Data Mapping

Data Migration:

Moving current data from the previous system to the freshly installed one while maintaining data integrity as well as compatibility may be the goal when switching to a new database or system.

Enhancing Data Quality:

When data quality is the main objective, data mapping can be used to find and fix flaws, inconsistencies, and duplication in the data as it’s being processed. This can be made simpler with data mapping tools that are available for just this type of project. 

Determine the Sources of Data:

Next, ascertain which kinds of information sources are pertinent to your project. These can consist of information warehouses, flat files, relational information bases, APIs, and external or legacy systems. Next, look over each information source’s schema or structure.

Gain an understanding of the connections, tables, columns, and information types included in the source information. This will enable you to design the information translation process more efficiently.

Among the most crucial phases in the data transfer process is gathering profile information. Understanding the organization of the information, including whether it is kept in files, tables, or another format, will be made easier with the use of information profiling.

Data profiling in relational databases is the process of utilizing primary keys, foreign keys, or other linkages to determine the relationships between tables. It is essential to comprehend these linkages in order to map and combine info effectively. Additionally, it will enable you to assess the caliber of the information you provide in the event that any values are missing, inconsistent, etc. 

Comply with the fields:

One of the most important steps in the information mapping process is matching fields, which is finding and defining connections between info components (fields) in both the target and source databases. The simplest fields to map are those where source and destination have a one-to-one connection.

For instance, you might map them straight if the target likewise requires a “Customer Name” field and the source contains one. You would define the transformation logic. If the source field had to be changed before it is loaded into the destination. To change the date format, for example, you might map the “Birthdate” field in the source using a transformation rule if the destination and source have different date formats. 

Transform Data: You may need to transform your info because it is quite likely not consistent or in a single format. Handling info is made simpler by the fact. That most tools provide built-in functions and data transformations. Transformations are simply joined, merged, sorted, and dropped. Complex transformations like tree join, denormalization, and normalization can also be used. 

Evaluate and Program:

Testing must be done before you are able to wrap up it. Once you have completed all the criteria and configured your data mappings. To map a little quantity of data, start small and observe if any problems arise. You may easily automate the entire procedure if there are no problems. Tools for info mapping provide trigger-based task schedulers. Enabling you to plan your procedure based on a time or occasion. Check more information here.

Data Transfer

Transferring info across systems is known as data migration, and it may be done easily with the help of an InfoBase mapping tool. Although there are several phases in the process, one of the most time-consuming parts is making source-to-target mappings by hand.

At this point, inaccurate and incorrect mappings have the potential to negatively impact info completeness and correctness. Which might ultimately result in the data transfer project failing. A safer option for effectively migrating data to any location, including an info warehouse, is code-free software with automated features.

Data Conversion

Due to the diverse locations and formats in which company info is stored, info mapping and

Breaking down information barriers and gaining insights requires info transformation. The process of transforming info begins with mapping. Which moves the data towards a staging location where it is transformed into the required format. It is subsequently sent to the database, which is its ultimate destination, following transformation.

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