Data Mapping – What is it?
Talking about the simple language, data mapping is a relationship between two data systems. Data mapping connects two different types of data models together. In data integration process data mapping is one of the most important factors. Making it simpler, data mapping is all about finding how a computer application or database connects to another computer or database. To make it more easy and simple to understand the concept, here is an example:
Suppose you have a list of people, a list that contains a few names of your friends. As well you have another list that contains the phone numbers of your friends. Now you want to connect both of the lists together and that is where data mapping works for you.
Data mapping is the first step in many complex sectors that come under the data integration process. That includes data transformation between the data source and the data destination. It helps in discovery of a private data such as the last digits in a social security number and so on. It can also be used for securing many databases and merge them into one while looking for redundancy.
How is Data Mapping being used?
One can use the data mapping concept for many tasks. However, all of the tasks mainly fall into two categories. The first category is the data migration and the second category is the data integration.
- Data Migration: The data migration process focuses on mainly moving information from one data model to another data model. What mapping actually do is, it creates a way between the source data model and the destination data model. That is where a data mapping software comes to the light. The software makes the migration process really easy and efficient. For example, suppose you have purchased a new mobile and now you want to move all the data that contains contacts number, text messages, and photos to your new mobile from the old one. To perform this task you will simply use a software or a feature like Bluetooth to get the job done. Well, that’s how data migration works.
- Data Integration: The data integration process mainly focuses on new information. What actually date integration process do is it creates a way between a new data model and an old data model and makes them connected to each other. By connecting both of the new and old data models it gets easier to access data from both of the sources. You can say it creates an argument between the new and existing data.
Industry proven data mapping best practices:
This section is going to mention some of the popular data mapping practices that the data analyst uses. The process of data mapping is a complex task and it’s a responsibility for the data analyst to figure out which data to map. These decisions are made on the basis of the common best practices. Here are some of those practices:
- Data mapping is all about maintaining relationships between two data elements. For example, two students live in different places but they use the same school to study.
- It helps in identifying and securing private and personal data. For example data mapping helps in securing information like, bank details, social security number, and health information and so on.
- It helps in Identifying and resolving data exceptions. In simple words it helps to figure out wrong data pattern.
- It helps the programmers to add a default value in the null area.
- Data mapping helps in ensuring that a specific data pattern should not look like another pattern. For example the pattern of a date should look like (dd-mm-yyyy) and not any other format.
What is Data Mapping software and how it works?
The data mapping software usually works as a converter. The main purpose behind the mapping software is that it converts the data into electronic data interchange file format. So the incoming data can be matched with the existing data.
The Software for mapping data usually transforms information between systems in an efficient way. Data mapping software can transform any field data into specific lengths, data types, or formats that the receiver system needs. Data mapping also drops the redundant or irrelevant data fields and combine the elements into a new field. The data mapping tools completely erase the need of manual data transformation.
Softwares used for data mapping purpose
There are many data mapping software exists on the internet which are available as free and paid version. Some of the software handles simple tasks while others handle highly complicated tasks. In fact for every task, complicated or simple there is a mapping tool. However here are some of the popular data mapping software names that you can use:
- Adeptia: Adeptia Integration Suite or AIS is an enterprise level solution. It deals with the cloud and on-premise integration. Also it includes B2B Integration, Application Integration, Business Process Management, and Data Integration and so on.
- Alooma: Alooma is another popular tool. It handles your data integration needs in sectors like cloud data warehouses, modern analytics solutions, mobile, IoT, web, cloud apps and so on.
- Dell Boomi : The Dell Boomi is an integration solution built in the cloud. Also, they are one of the most trusted brand for small and large business enterprises.
- HVR: HVR is also one of the trusted platforms. It provides real-time data replication for Business Intelligence, Big Data, and hybrid cloud. People using HVR for Data Integration, data migrations, data Lake consolidation, and so on.
- IBM InfoSphere: IBM InfoSphere Information Server comes with rich set of information integration and governance capabilities. That allows you to integrate big data with your traditional enterprise data. As a result IBM InfoSphere displays critical business insights. The IBM InfoSphere end-to-end information integration capabilities make you understands your data and helps your data monitor.