What is Data Mapping? Definition, Examples, Categories & Factors

Data mapping is the process of creating a correspondence between two data sets. This can be done in a number of ways, but most commonly, it is done by creating a table that lists the values from one data set alongside the corresponding values from the other data set. Data mapping is a useful way to keep track of relationships between data and can be used to make sure that data is correctly transferred from one system to another.

‍

What is a Data Mapping Tool?

A data mapping tool is a software application that helps users create diagrams or charts that illustrate the relationships between data elements. Data mapping tools are often used by businesses to visualize data flows or dependencies and can be used to create both high-level and detailed maps. There are a variety of data mapping tools available on the market, ranging from simple desktop applications to complex enterprise-level solutions.

‍

The features and functionality of each tool vary depending on the vendor. Still, most data mapping tools offer some basic features, such as the ability to create and edit maps, add annotations, and export maps in various formats. In addition, many data mapping tools offer advanced features, such as the ability to create custom diagrams or connect to external data sources. Automating the process with these mapping tools can save users a lot of time and effort.

‍

Importance of Data Mapping in ETL Process

Data mapping is a critical component of the ETL process. ETL stands for Extract, Transform, and Load, which is the process of taking data from one or more source systems, transforming it into a format that can be loaded into a target system, and then loading it into the target system. The extract phase involves extracting data from the source system. The transformation phase involves transforming the data into the format required by the target system. The load phase involves loading the data into the target system. Data mapping is typically done during the transformation phase, as it can be used to determine how the data should be transformed in order to be compatible with the target system.

‍

1. Automated Data Mapping & Data Integration:

Automated data mapping and data integration are essential for businesses that want to consolidate important information from different data sources. Data mapping software bridges the differences in the schemas of the source and target repositories, allowing businesses to easily integrate data from multiple sources. This makes it possible for businesses to make better decisions by having access to a more complete picture of their data.

‍

2. Data Mapping assists in data migration:

A code-free mapping solution is essential for Data Migration as it can automate the process of inaccurate and invalid Data Mapping. This solution will impact the accuracy and completeness of the data being migrated, making it a crucial part of the migration process.

‍

3. Automated Data Mapping & Transformation:

Data transformation is essential for drawing insights from data and breaking information silos. Data modelling is the first step in data transformation, which helps create a framework for what changes need to be made to data before it is loaded into the target database. The Data Conversion Mapping feature offered by Data Mapping Tools can help with this process.

‍

Factors to consider when choosing Data Mapping tools

A good data mapping solution should include support for multiple data sources and targets, transformation capabilities, and a user-friendly interface. There are a few key factors to consider when choosing data mapping tools.

‍

• Graphical Drag-and-Drop, Code-Free User Interface: A Data Mapping Tool that requires no coding and offers a drag-and-drop user interface is critical for an easy data mapping process.

‍

• Ability to Schedule & Automate Database Mapping Jobs: In order to effectively manage your database, it is essential to choose a Data Mapping Software that offers a time-based mapping function and event schedule. This will allow you to trigger specific events based on certain conditions.

‍

• Support for Diverse Systems: All Data Mapping Software should have the ability to connect to many types of data sources, which are structured, unstructured, and semi-structured. This would include databases, REST APIs, and web services, along with FLAT file formats that are commonly used, such as XML files, JSON files, EDI files, and Excel spreadsheets.

‍

• ‍Instant Data Mapping Preview: To avoid any data mapping errors in your design, use Data Mapping Software that allows you to view both the processed and raw data at any step of the modelling process.

‍

3 Categories of Best Data Mapping Tools

There are three primary categories of data mapping tools available on the market.

1. Open Source Data Mapping Tools.
2. On-Premise Data Mapping Tools.
3. Cloud-Based Data Mapping Tools.

‍

1) Open Source Data Mapping Tools:

Open-source data mapping tools are free and typically have a community-based support system. Some of the most popular open-source data mapping tools include:

• Pentaho Data Integration.

• Talend Open Studio.

• CloverETL.

• Pimcore

‍

1. Pentaho Data Integration

Pentaho Data Integration (PDI) is an open-source Data Integration tool by Hitachi Data Systems. It offers ETL solutions to enterprises that need automatic data mapping and loading of data from source to destination. With Pentaho Data Integration, users can easily map data from source to destination and save time with its no-code GUI interface. It supports deployment on single-node computers as well as on a cloud or cluster. PDI's other services include OLAP services, reporting, information dashboards, and data mining.

‍

Pros of Pentaho Data Integration:

• It offers a no-code graphical interface that is easy to use.

• It can be deployed on a single node or in the cloud.

• It supports various data formats and sources.

‍

Cons of Pentaho Data Integration:

• It does not have an inbuilt scheduler, so users have to rely on third-party tools.

• The community edition does not include support for big data sources.

‍

2. Talend Open Studio

Talend Open Studio is a powerful data integration tool that supports 100+ connectors for various sources. It provides continuous integration, reducing deployment and repository management overheads. Talend's graphical user interface allows you to visually map source data to destination data types, providing a consistent and singular view of enterprise data. Talend also allows you to write portable custom code in Java to incorporate your specific business needs.

‍

Pros of Talend Open Studio:

• It provides a great and easy-to-use interface.

• It offers a wide range of connectivity options for various data sources.

‍

Cons of Talend Open Studio:

• The community edition does not include support for big data sources.

• The Open-Source edition only has a few features related to scheduling and streaming.

‍

3. CloverETL

CloverETL is an open-source Data Integration platform that supports Extract, Transform, and Load (ETL) processes. CloverETL's visual interface allows you to easily map source data to destination data types. CloverETL also supports various data formats, such as XML, CSV, and Flat Files. It can be deployed on-premise or in the cloud. CloverETL's other features include a data profiling tool, a metadata repository, and a data quality module.

‍

Pros of CloverETL:

• This tool is great for quickly transforming data.

• You can create web services by using data parallelism data services.

‍

Cons of CloverETL:

• If you do not have the proper documentation, setting up and implementing this will be significantly more difficult.

• A fewer number of files and formats are supported.

‍

4. Pimcore

Pimcore is a powerful open-source data management platform that is entirely developed in PHP. It offers easy data imports from formats such as CSV, XLSX, JSON, XML, and map data without writing any code, making it an ideal solution for enterprises that need to manage large amounts of data. Pimcore also integrates with other product-based websites like eCommerce platforms and social media websites, providing up-to-date data to all team members.

‍

Pros of Pimcore:

• Pimcore's Data Hub allows you to connect easily to various data sources.

• Its enterprise-grade solution is available for free.

‍

Cons of Pimcore:

• Pimcore requires a bit of technical expertise to set up and use.

• It is not as widely used as some of the other data management platforms, so there is less support available.

‍

2) On-Premise Data Mapping Tools  

On-premise data mapping tools are software tools that are installed on a business's infrastructure and used for source-to-target mapping and integration. On-premise data mapping tools have many benefits, including the ability to handle huge volumes of data, provide fast access, and easily read archival data/tapes. However, on-premise data mapping tools also have some drawbacks, such as being limited in the number of data formats they can handle and having substantial maintenance and running costs. Ultimately, whether or not an on-premise data mapping tool is right for a business depends on the specific needs and circumstances of that business.

‍

• Informatica PowerCenter

• IBM InfoSphere

• Microsoft SQL

• WebMethods

‍

1. Informatica PowerCenter

Informatica PowerCenter is a highly scalable Data Integration solution that provides powerful performance and flexibility. With its proprietary transformation language, users can build custom transformations. By using its pre-built data connectors for most AWS offerings, users can easily configure a versatile Data Integration solution for their needs. Additionally, Informatica PowerCenter adheres to many compliance and security certifications, such as SOC/HIPAA/Privacy Shield.

‍

Pros of Informatica PowerCenter:

• If you have confidential data stored across multiple data sources on AWS, Informatica is the software for you. It provides a centralized repository where all related data (from databases and flat files to streaming data and network info) is securely kept.

‍

Cons of Informatica PowerCenter:

• The tool can be challenging to use for those without a technical background.

• It is a commercial product and requires a license fee.

‍

2. IBM InfoSphere

IBM InfoSphere is a Data Integration tool that is often used in conjunction with other IBM products, such as the IBM Data Warehouse. It offers many features for data transformation and migration, including a drag-and-drop interface, pre-built transformations, and real-time integration. Additionally, IBM InfoSphere can be used to cleanse and enrich data, as well as to monitor and track data changes.

‍

Pros of IBM InfoSphere:

• It has a wide range of capabilities for data transformation and migration.

• The drag-and-drop interface makes it easy to use.

‍

Cons of IBM InfoSphere:

• It is a commercial product and requires a license fee.

• It can be challenging to use for those without a technical background.

‍

3. Microsoft SQL

Microsoft SQL Server Integration Services is a powerful data integration and data migration tool that can automate the maintenance of SQL server databases and updates to multidimensional cube data. It includes a rich set of built-in tasks and transformation tools for constructing packages, making it an ideal choice for complex jobs. With its easy-to-use workspace, Microsoft SQL Server Integration Services makes it simple to get started with data integration and migration.

‍

Pros of Microsoft SQL Server Integration Services:

• It comes with excellent support from Microsoft

• The Graphical User Interface helps users easily visualize how data flows.

‍

Cons of Microsoft SQL Server Integration Services:

• Skilled developers are needed to operate it because it has a coding interface.

• It is less efficient for handling JSON and has fewer Excel connections.

‍

4. WebMethods

WebMethods Integration Server is a powerful tool for enterprise data mapping and communication between systems. It supports many services, including data mapping, to on-premise, hybrid, and cloud solutions. It also supports Java, C, and C++ for more flexibility for users. WebMethods Integration Server is an ideal solution for data mapping of B2B solutions.

‍

Pros of WebMethods

• It can help to track user documents.

• Easy to use and widely comprehensive, this enterprise tool is perfect for businesses of any size.

‍

Cons of WebMethods

• The tool might be too comprehensive for some users.

• It is expensive for small and mid-sized companies.

‍

3) Cloud-Based Data Mapping Tools

A cloud-based data mapping tool is a software application that helps users create, manage and share maps of their data. The maps can be used to visualize data sets, track changes over time or identify patterns and relationships. The tools typically offer a range of features, such as the ability to import data from spreadsheets or databases, create customised map views, add annotations and share maps with others. Some of the most popular cloud-based data mapping tools include Google Maps, Mapbox and Tableau. While each tool has its own unique features and pricing model, they all provide an easy way for users to create and share interactive maps of their data.

‍

• Oracle Integration Cloud Service

• Dell Boomi AtomSpehre

• Talend Cloud Integration

• Jitterbit

• MuleSoft Anypoint Platform

• SnapLogic

‍

1. Oracle Integration Cloud Service

Oracle Integration Cloud Service (ICS) is an integration application that can perform Source to Target Mapping between many Cloud-Based applications and data sources. It can also go beyond that to include some On-Premise data. It also provides 50+ native app adapters for integrating On-Premise and other application data. With ICS, you can easily connect your On-Premise and cloud-based applications, allowing for a seamless flow of data between them. This makes it easy to keep your data up-to-date and consistent across all your applications.

‍

Pros of Oracle Integration Cloud Service:

• SaaS Extension and Integration come together under one product.

• Our product integrates smoothly with other Oracle products, such as Oracle Sales Cloud, API Platform Cloud Service, and SPMS.

‍

Cons of Oracle Integration Cloud Service:

• Although it offers many features, the high price tag may deter some potential buyers.

‍

2. Dell Boomi AtomSphere

Dell Boomi AtomSphere is a cloud-based data mapping tool that enables users to quickly and easily connect their applications and data sources. It offers a point-and-click interface that makes it easy to create maps and workflows without any coding required. AtomSphere also includes a range of features, such as the ability to connect to more than 100 different data sources, real-time data synchronization, and support for multiple languages.

‍

Pros of Dell Boomi AtomSphere:

• No coding is required, making it easy to use for non-technical users.

• Supports a wide range of data sources, making it easy to connect all your applications and data.

‍

Cons of Dell Boomi AtomSphere:

• The interface can be a bit overwhelming for some users.

• Pricing is based on the number of connections, which can be expensive for large-scale projects.

‍

3. Talend Cloud Integration

The platform allows you to connect applications, data, and devices anywhere—on-premises or in the cloud—with drag-and-drop simplicity. Talend Cloud Integration Platform is built on top of Apache Camel and offers over 400 connectors and components to make integrating a snap. You can use it as a stand-alone application or embed it into your own application. Talend Cloud Integration offers a graphical user interface that makes the tool user-friendly and helps save time. The platform is also scalable, so it can handle increasing volumes of data as your business grows.

‍

Pros of Talend Cloud Integration:

• Connectors and components make integration easy.

• The graphical user interface is user-friendly.

• Scalable to handle increased data volume.

‍

Cons of Talend Cloud Integration:

• Cannot connect to some legacy systems.

• Paid subscription required for some features.

‍

4. Jitterbit

Jitterbit is a powerful data integration and data mapping tool that can help enterprises establish API connections between apps and services. It can automate the data mapping process in SaaS applications and on-premise systems, making it much easier and faster for users. Additionally, Jitterbit's AI features make it possible to control the interface using speech recognition, real-time language translation, and a recommendation system. This makes Jitterbit an extremely versatile and user-friendly data integration tool.

‍

Pros of Jitterbit

• The configurations are mostly intuitive and easy to figure out.

• The interface is user-friendly and comes with great documentation.

‍

Cons of Jitterbit

• Poor quality logging and debugging

‍

5. MuleSoft Anypoint Platform

The MuleSoft Anypoint Platform is a powerful iPaaS tool that helps enterprises to map data easily between disparate systems. It uses its own MuleSoft language to create and execute Data Mapping tasks and also supports a mobile version for remote management and monitoring. With the Anypoint Platform, enterprises can quickly connect data sources and destinations to streamline data flow and ensure consistent data across their applications.

‍

Pros of MuleSoft Anypoint Platform:

• It comes with plenty of connectors that eliminate the need to code for new data mapping, which saves time.

‍

Cons of MuleSoft Anypoint Platform

• It features its own MuleSoft language to create solutions, which is unique among Data Mapping tools that mostly provide drag-and-drop features.

‍

6. SnapLogic

SnapLogic is a powerful data migration and data mapping tool that can automate many of the tedious and time-consuming aspects of data management. Its workflow builder and artificial intelligence capabilities make it easy to map data between cloud applications and destinations, keeping your streaming data in sync. With its visualization and reporting tools, you can easily track all your data migration and data mapping activities, ensuring a smooth and successful transition.

‍

Pros of SnapLogic:

• Workflow builder and artificial intelligence make data mapping easy.

• Visualization and reporting tools help track data migration activities.

‍

Cons of SnapLogic:

• The interface can be a bit overwhelming for some users.

• Pricing is based on the number of connections, which can be expensive.

‍

Conclusion

Data mapping is a critical process for managing data, ensuring its integrity, and maximizing its value. By leveraging AI/ML, businesses can gain the insights they need to make informed decisions and stay ahead of the competition. Boltic can help you with all your data mapping needs. Our no-code, the easy-to-use platform will save you time and money. With our help, you can focus on your business more and worry less about data privacy compliance. You can easily map data, create workflows, and build applications without writing a single line of code. Visit us at boltic.io today and see how we can help you take your business to the next level. Thank you.

‍