Data Mapping is the process of matching data fields from the source to the data fields of the target when undertaking the course of a Data Migration or warehousing project with the help of data Mapping Tools.

The process involves the transfer of data between the source and destination so that the semantic and logical meanings remain in place and the accuracy for the purpose of using data coming from the destination is improved.

Furthermore, your data may be transferred between your data warehouse and your BI tools. Therefore, an additional version of Data Mapping would be needed for fine-tuning your data in order to get the most relevant details and conform to the nuances of the software and analysis procedure.

Data that is similar to yours may require to be processed in a different way, according to the goal of the different analytical methods.

The most powerful and flexible Data Mapping Tools are essential for your strategy to use data.

This article can help readers understand the fundamentals of data mapping and how it can be essential to an ETL process.

In addition to the essential aspects to keep in mind when searching to find Data Mapping Tools, a comprehensive description of the three top Data Mapping Tools presently in the market is provided to the reader.

What Exactly Is Data Mapping?

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Data mapping is a simple term that is the process of making a map that will allow the data from the source will be sent to the database of choice.

The database that is targeted could be a Relational Database, NoSQL Database, and a CSV document. The choice will be based on the preference of the user for the type of database that they want to use.

Data Integration Mapping tasks are a bit more difficult. Data Integration Mapping challenges vary in difficulty depending on the structure of the data to be mapped and also the difference between the structure of data at the source and of the destination.

The majority of Data Mapping Tools offer pre-built templates for matching data sets that are then used to make database matches from the target system to the source.

A simple Data Mapping Template will look like an ER(Entity-Relationship) design with structured data in sourced entities.

The Data Mapping Template differs from the ER diagram in that it is able to transform into ready-made workflows that can be added to workflows and then automated, creating an automatic data mapping system.

The process is executed with Data Mapping Tools within a few seconds and with no human involvement.

Database Mapping depends on the amount, schema as well as the foreign and primary keys for the Relational Databases data sources.

What Is A Data Mapping Tool?

The majority of businesses now are moving to data-driven business decision-making to boost their performance. With the growth of companies, the requirement to organize and store the quantity of data is growing rapidly.

Data Mapping is necessary for this stage, and manually accomplishing this task in Big Data is a tedious and lengthy task.

Data Mapping Tools allow the mapping of data to different data sources and can store any size of data.

It is based on the business requirements, whether they require source Data Mapping Tools or on-premise Data Mapping Tools. They automatize the mapping process or aid users in mapping data effortlessly with minimal effort.

The Importance Of Data Mapping In The ETL Process

In order to leverage data and gain economic value, The data is gathered from a variety of internal and external sources. The data must be unified and converted into a format compatible with the process of analysis and operations, which is achieved by Source to the Target Mapping.

Automatic Data Mapping and Data Integration: To effectively integrate data, it is essential that the Data Model for the source and destination data repositories has to be identical.

Because this is not the case within the context of a Data Warehouse, Data Mapping Software can bridge the gaps between the schemas used by the repository that is used for source and destination. It allows businesses to consolidate crucial data across multiple data sources without difficulty.

Data Mapping Aids with Data Migration: Inaccurate or invalid data Mapping throughout this Data Migration phase impacts the precision and quality of the data to be migrated. Thus, a non-code mapping solution that can be automated is crucial to Data Migration.

Automatic Data Mapping and Transformation: The term Data Transformation is crucial in finding insights and breaking up data silos as enterprise data is available in multiple different formats and locations.

The process of data Modeling is the very first stage of Data Transformation, which helps create an outline of changes that need to be applied to the data prior to it being loaded into the database of choice through the Data Conversion Mapping feature given by Data Mapping Tools.

Things To Consider When Choosing The Right Data Mapping Software

For the best chance of success for every Data Integration, Data Warehousing project and Enterprise Data Transformation or , you need to select the appropriate Data Mapping Software that fits the requirements of your business precisely.

Before you begin choosing the appropriate tool, the first step is to determine your unique Data Modeling requirements and must-have capabilities.

The most important features of a great Data Mapping solution must include are:

Graphical Drag and Drop and code-free User Interface: it is essential that you choose the right Data Mapping tool with a no-code method to build data maps and manipulate data with the intuitive drag-and-drop user interface.

Ability to schedule and automate Database Mapping Tasks: it is crucial to select the right Data Mapping Software that can arrange the Database Workflow by using an algorithm for mapping time and events schedules that are activated by certain circumstances.

Quick Data Mapping Preview: Pick a Data Mapping software that is able to avoid mapping mistakes in the application during the designing phase. It will allow users to see the mapped raw data as well as processed at any stage in the Data Modeling process.

Assistance for Diverse systems: All the Data Mapping Software must provide access to a variety of unstructured, structured as well as semi-structured data sources that include REST APIs, databases, web services with FLAT formats files, such as XML, JSON, EDI, Excel, etc.

Three Categories of Best Data Mapping Tools

Data Mapping Tools are classified into three types. The three categories could be: 

• Open Source Data Mapping Tools.
• On-Premise Data Mapping Tools.
• Cloud-Based Data Mapping Tools.

Open Source Data Mapping Tools

The Data Mapping Tools are characterized in that they make their source code accessible to the general people at large. Additionally, they let you modify the code base on specific requirements. 

Talend Open Studio For Data Integration

It can do more than simply Source to Target Mapping and could be used to act as a Data Integration Tool. Talend Open Studio supports 100 plus connectors for diverse sources. It allows continuous integration, thereby cutting down on deployment and repository managing costs.

It offers a graphic user interface to allow users to map visually sources to the type of data that will be used for the destination.

Organizations have the ability to maintain a consistent and unique perspective of their data thanks to Talend’s intuitive GUI-driven Master Data Management (MDM) capability.

Talend lets you create portable, custom- code written in Java that can be adapted to your particular requirements for business.

Advantages from Talend the Open Studio to data Integration

Talend can support dynamic schemas (i.e., tables). This allows users to handle records through the pipeline without having to know the column names and types prior to the time of compilation.

Because Talend operates on a row-by-row basis, it can work to the row-based processing of the data source before it is used by the warehouse that will be consuming it.

Cons of Talend Studio for Data Integration

• The Open Source edition is limited in terms of options for scheduling and streaming.
• It is suited to Big Data programme rather than ETL.

Pentaho Data Integration

it is an open-source Data Integration tool by Hitachi Data Systems. It provides ETL solutions to companies who require automated Data Mapping and transfer of data from the source to the target.

It provides solutions to Data Minning, Data Warehousing as well as Data Analysis. Other services offered include OLAP services, reports, Data dashboards, reporting, and Data Mining.

Pentaho Data Integration tool is code-named Kettle and provides a no-code user interface with a GUI that lets users quickly map data from sources to destination while reducing time. It is able to be installed on single-node PCs as well as the cloud or cluster.

Pros of Pentaho Data Integration

• It has a fun and interactive no-code interface.
• It offers analytics, as well as task-related results, to provide clear and accurate information about the operation.

Cons of Pentaho Data Integration

• The Community edition does not have the Job Manager and Scheduler that performs some jobs manually.
• The documentation required to support PDI isn’t very useful because implementation can be difficult.

CloverETL (CloverDX)

It is an open-source Data Mapping and Data Integration software that runs in Java. It’s a great tool to map, transform and modify data. It gives users the flexibility to make it an independent application, command-line tool, server software, or even integrated into different applications.

CloverETL lets companies develop, test, deploy, and manage the loading procedure from origin to end-point. It offers code and visual interfaces to developers for mapping and altering data.

Pros and cons of CloverETL

• It provides a high speed for the process of data transformation.
• Data parallelism services for data can be utilized to build web-based services.

Cons of CloverETL

• Insufficient documentation to guide the setup and operation.
• A smaller number of file types and formats are supported.

Pimcore

Pimcore is an open-source Data Management system which is completely developed using PHP. It’s an enterprise-level Data Mapping tool for content management, customer management, digital commerce, and more. It provides accurate data to all staff members in a business.

It allows easy import of data using formats like CSV, XLSX, JSON, XML, and map data, without having to write any code. It allows users to add data at regular intervals. The system also works with other sites that offer products, like E-Commerce websites, Social Media websites, and so on.

Pros of Pimcore

• It is easy to integrate other platforms by using web services.
• It provides an enterprise-level solution at no cost.

Cons of Pimcore

• It is not easy to use, even for people who do not have technical skills.
• The asset portal extension in the DAM module isn’t compatible with mobile devices.

On-Premise Data Mapping Tools

On-Premise, just as the name implies, is a software tool that is exclusive. However, they are placed on the infrastructure of the company and utilized for Source To Target Mapping and Integration.

Although on-premise data Mapping Tools are restricted in terms of the formats that they can work with and have substantial cost of maintenance and operating costs. They’re great when your data is private.

On-Premise Tools will handle large volumes of data. They provide rapid access and quickly read your archived data or tapes. While the price may be costly, they can provide enterprises with a feeling of security as well as ease in the IT departments that handle the coordination.

Informatica PowerCenter

Informatica PowerCenter provides a highly adaptable Data Integration solution with powerful functionality and versatility. With its unique transformation language, users are able to create customized transformations.

Utilizing its pre-built data connectors that are compatible with the majority of AWS services like S3/DynamoDB/Redshift. AWS users are able to configure an incredibly flexible Data Integration solution for AWS.

A variety of security and compliance certifications, such as SOC/HIPAA/PrivacySheld, are made a part of Informatica PowerCenter.

Pros of Informatica PowerCenter

• Informatica is ideal for you when you have several data sources in AWS, and you have sensitive data. It is a central place that houses all details (e.g., databases/flat files/streaming data/network, etc., associated with sources/targets) saved.

Con of Informatica PowerCenter

• Initial licensing costs and high running expenses.
• If you are interested in using Cloud Data Warehouse, the destination will only work with Amazon Redshift.
• Microsoft Azure SQL Data Lake is the sole Data Lake destination it supports.

IBM InfoSphere

IBM InfoSphere is part of the IBM Information Platforms Solutions suite as well as a Data Integration platform that helps companies monitor, clean, and process data.

It provides high performance in Data Mapping and loading by utilizing its Massively Parallel Processing (MPP) capabilities. It’s extremely adaptable and scalable for managing massive quantities of data at a rapid pace.

Pros of IBM InfoSphere

• It’s an adaptable and flexible platform for handling huge amounts of data.
• It is easy to integrate into other IBM Data Management solutions and provides more flexibility for the options.

Cons of IBM InfoSphere

• IBM InfoSphere is not easy to learn and is not flexible.
• It’s more expensive than other Data Mapping tools available.

Microsoft SQL

Microsoft SQL Server Integration Services is a part of Microsoft SQL and a Data Integration as well as a Data Migration tool.

It’s utilized to automate maintenance for SQL Server Databases and updates to Multidimensional Cube data. Most of the workflow for Microsoft SQL Server Integration Services involves coding. The workspace looks like Visual Studio Code.

Microsoft SQL Server Integration Services will perform complicated tasks effortlessly and comes with a wide array of integrated tasks as well as transformation tools to build software.

Pros of Microsoft SQL

• It has excellent support from Microsoft.
• It comes with a GUI that allows users to see the flow of data.

Cons of Microsoft SQL

• It needs skilled developers to use it because it has an interface for coding.
• It’s not the best to handle JSON, and it has fewer Excel connections.

WebMethods

This Server is a Java-based integration server that is designed specifically for companies. It provides many functions, including Data Mapping and communication between Systems.

WebMethods Integration Server can converse Data Mapping tasks to On-premise, cloud, and hybrid. It can also support Java, C, and C++ for greater flexibility for the users. It’s best to be used for Data Mapping of B2B solutions.

Pros of WebMethods

• It is able to support Document Tracking.
• It’s simple to operate, is scalable, and incorporates the majority of business tools (all together).

Cons of WebMethods

• The cost is prohibitive for smaller and mid-sized businesses.
• Insufficient documentation for legacy technology.

Cloud-based Data Mapping Tools

Cloud-based Data Mapping Tools are among the most active, widely used and modern these days.

They offer flexibility as well as speed and flexibility with the lowest cost. Cloud-based Tools let you access data to any location and permit users to store, map and connect your data from a variety of sources.

The majority of data utilized today is created through cloud computing, such as stream data, clickstreams APIs, databases, etc.

One of the benefits these tools provide is the ability to set up and provide support. Continuously developed and upgraded, this tool offers modern technologies to users.

Oracle Integration Cloud Service

It is an application for integration that can carry out Source to Target Mapping among many cloud-based apps and sources of data.

Additionally, it can extend it to incorporate some on-premise data. The service also offers 50+ native app adapters that allow for the integration of the On-Premise data and any other app data.

Pros of Oracle Integration Cloud Service

• Both SaaS Extension and Integration coalesce into one project.
• Integrates seamlessly with other Oracle products such as Oracle Sales Cloud/API Platform Cloud Services/SPMS, for instance.

Cons of Oracle Integration Cloud Service

• This could be too much for your needs since it is a tool for Process Automation, Visual Application Building.
• The price could be too high since it’s priced in accordance with its many functions.

Dell Boomi AtomSphere

Dell Boomi AtomSphere is a cloud-based Data Mapping and Integration tool developed by Dell. Through its interactive design, users are able to connect data across the two platforms and connect these platforms. Dell Boomi AtomSphere is suitable for businesses of any size.

Pros of Dell Boomi AtomSphere

• It has drag-and-drop capabilities that make the process easier for those who are not tech-savvy.

Cons for Dell Boomi AtomSphere

• The absence of any documentation.
• The feature of point and click is not able to solve complex problems.

Talend Cloud Integration

It is an ETL solution that presents with the Data Mapping tool. Talend Data Mapper allows users to designate mapping fields and perform the conversion of data across records on two platforms. Talend Cloud Integration offers a graphic user interface that is user-friendly and can help users to save time.

Pros Talend Cloud Integration

• It has an option to drag and drop on the tool pallet, which helps in the process.

Cons of Talend Cloud Integration

• There are fewer integrations in other modules.

Jitterbit

It is a Data Integration and Data Mapping tool for enterprises that lets them connect APIs between their apps and services. It will automatize data mapping and automate the Data Mapping process in SaaS applications as well as on-premise systems.

Through its AI capabilities, users are able to use the interface to control it using speech recognition, real-time translation, as well as a suggestion system. Jitterbit’s Automapper allows you to map similar fields to make the conversion process much easier.

Pros of Jitterbit

• A majority of the settings involve a point-and-click.
• It has a simple-to-use interface and great documentation.

Cons of Jitterbit

• Logging and debugging of poor quality.

MuleSoft Anypoint Platform

MuleSoft Anypoint Platform is an integrated iPaaS Data Mapping tool that aids enterprises in mapping data from a destination to SaaS applications to act as sources.

It makes use of its own MuleSoft language to develop and complete Data Mapping tasks. It also has mobile versions, which allow users to monitor and manage Data Mapping and data integration tasks remotely. 

Pros MuleSoft Anypoint Platform

• It includes a variety of exciting connectors, which make it easier to write code to make new Data Mapping.
• The program provides an IDE which is simple to use and allows for easy development and testing.

Cons of MuleSoft Anypoint Platform

• It has its own MuleSoft language to develop solutions. There are also a number of Data Mapping tools that provide drag-and-drop features.

SnapLogic

This tool is a Data Migration and Data Mapping software that automatizes the majority of all Data Mapping fields using its Workflow Builder as well as Artificial Intelligence. The tool automatically maps data between different cloud services and locations so that the data streaming is up to date.

The users can monitor all Data Migration and Data Mapping processes with the aid of reports and visualization tools.

Pros of SnapLogic

• Data Mapping is simple to use and gives the flexibility needed by users.
• A user-friendly interface that doesn’t need the involvement of any developers.

Cons of SnapLogic

• This isn’t suited for large pipelines or filed mappings.
• It can be expensive when dealing with massive databases.

Conclusion

This blog provides a good overview of Data Mapping. It began by examining the details of what Data Mapping actually is, then describing the procedure for Data Mapping, its importance to an ETL process, as well as the things that an individual should think about prior to selecting a suitable Data Mapping Tool from the marketplace.

The final part of the article discusses the top 3 Data Mapping Tools spread across Cloud-based Tools, Open Source Tools as well as On-Premise tools. We also look at a tool that provides users with the benefits of all of these techniques in a way that is cost-effective.