It implies a diversity of data types that need to come together to provide a complete picture of an enterprise’s moving parts. It also means the business needs to use one – or more – data mapping tools and software to extract information composed of multiple inputs and piece them together to get accurate information in real-time.

Here is our list of the seven best data mapping software:

  • HVis A data mapping tool for larger organizations that have to deal with bulkier volumes of data; it is highly flexible and fits into any architecture, regardless of its diversity or complexity.
  • Boomi AtomSpheris An on-demand multi-tenant cloud integration platform for syncing and replicating data; it is easy to master and comes with templates that allow novices to master the pipelining process.
  • CloverDX A “universal” data mapping tool that connects data and destination regardless of the platforms, network architecture, and applications involved; it can be used to design, create, and deploy data flows for a wide array of scenarios.
  • IBM InfoSphere DataStage A data mapping tool from one of the leaders in the data storage industry that integrates a wide range of data; it also helps that the tool combines with IBM’s vast array of data management tools.
  • Oracle Data Integrator Another product from one of the biggest data storage technology companies; this tool is ideal for larger businesses looking for multi-dimensional data organization, mapping, and storage.
  • Pimcore Product Information Management (PIM) This mapping tool binds all data found on a network and brings it together as real-time information; it works seamlessly with a wide array of enterprise systems and technologies.
  • Talend Data Integration This mapping tool works with enterprise data located in any type of architecture; it unifies, integrates, transforms, and deploys it wherever it is required to after ensuring it is clean.

What is a data mapping tool?

Data mapping software and tools are used to plan and design the flow of data ETL by taking the correct data sets from the correct sources, transforming them into expected formats, and uploading them into their corresponding target databases.

What is data mapping?

Data mapping is the term used to describe the plotting of a flowchart that shows the process involved in taking data from various sources, processing or parsing it into required formats, and sending it on to be stored in one or more target databases.

It also involves matching data fields or elements from one or more source databases to their corresponding or intended data fields in other target databases.

Data mapping is a critical part of data management and is used in processes like Data Integration, Data Transformation, Data Migration, and Data warehousing.

Data mapping also helps to combine data into a destination system by extracting, transforming, and loading (ETL) it. As a result, businesses can use the mapped data for producing deeper, all-inclusive insights into their processes’ currency and efficiency. It allows them to organize, distill, analyze, and understand vast amounts of data in numerous locations and extract comprehensive and all-inclusive information.

Once they have been configured, these tools continue to automatically perform the data mapping based on schedules or triggering conditions.

Why do we need data mapping?

There are times when it is necessary to use data mapping tools and software, including:

  • Administrators might need to automate their data mapping process to cater to multiple data migration schedules instead of writing scripts or manually importing data each time they need to extract data.
  • Using these tools ensures data that needs parsing is converted correctly and the correct data goes to the right destination – every single time.
  • They make it easier to integrate, transform, and move mission-critical data and create data warehouses.
  • The connection between target and source databases can become permanent – these tools can help keep the live connection
  • They keep data clean – they can be configured to trigger alerts when any inconsistencies are spotted.
  • Most of them come with insightful and interactive reports that can be shared with all stakeholders.

The bottom line is that these tools cut human error and help deliver all-inclusive information in real-time.

What are the features that make for a good data mapping tool?

Let’s have a look at some features to look for in professional data mapping tools and software:

  • Ease of use – features like graphical user interfaces, drag-and-drop operation, and code-free configuration make for great tools.
  • Automation – they should also make it easy to create workflows, schedules, and triggers.
  • Instant preview – when the tools allow users to view data in both raw and processed formats, it is easier to prevent mapping errors during design time.
  • High compatibility – in today’s world of complex data types, diversity of software, and hybrid configuration of networks, it makes sense for mapping tools to handle complex design requirements and work with a wide array of technologies.
  • Price – it is always important that any software solution, not just data mapping tools, be worth the investment, i.e., positive ROI.

The tools we have included on our list have been rated based on these and more points.

The best Data Mapping software

Let’s go ahead and have a look at the seven best data mapping tools and software:

1. HVR

HVR delivers on their motto – “Fresh data. Where you need it.” This is a tool that can handle large amounts of data and have complex ETL requirements. It is designed for medium to large enterprises.

It is a data integration solution packed with features that make it easy for administrators to control various architectures, work with numerous data types, and present it all in insightful statistical reports.

But there are more HVR features:

Try HVR for FREE.

2. Boomi AtomSphere

Boomi AtomSphere is an on-demand multi-tenant cloud integration platform that syncs and replicates data between apps, SaaS, databases, and more. It offers a cloud integration platform that integrates different applications with the help of a library of pre-built solutions or customized ones for more unique requirements.

More Boomi AtomSphere features include:

  • Dell Boomi AtomSphere is easy to use, even for non-technical beginners – they will soon be syncing and replicating data using drag-and-drop UIs; they can immediately start connecting cloud and on-premises applications and data
  • This platform allows for the creation of cloud-based integration processes – called “Atoms” – to transfer data between cloud and on-premises applications according to the specific requirements of each data integration process.
  • Unique features include future-proof testing (known as Boomi Assure) to guarantee processes will keep working with every new release of AtomSphere; it has a bulk-copy feature for loading large volumes into databases and allows for more significant numbers of integration projects that can be managed centrally.
  • It is ideal for medium-to-large businesses and enterprises. It supports products they may own like Oracle E-Business Suite or Hadoop HDFS – both products used for extensive data management.
  • Dell Boomi AtomSphere offers easy integration to seamlessly connect data, applications, and users and serve as a unified platform for end-to-end handling workflows – all of which leverage the power of cloud technology.
  • It integrates well into the cloud as it is built on an advanced distributed architecture that offers uncompromising security.

Try Boomi AtomSphere for FREE for 30 days.

3. CloverDX

CloverDX boasts that it can connect to “just about any data source or output.” It is an easy-to-use tool that supports on-premises, cloud, multi-cloud, and hybrid deployments. Once deployed, it is easy to master the platform and start creating, automating, running, and publishing data pipelines.

Looking at more features of CloverDX:

  • It offers seamless integration and automation from end to end by combining visual (for beginners) and coded (for advanced users) design approaches to create effective and adaptive solutions for validating, transforming, and moving data with ease.
  • The tool offers a developer-friendly design tool that can be used to design, debug, run, and troubleshoot data flows and extract, transform, and load (ETL) it with accuracy.
  • It is highly flexible; while it can be deployed on-premise and in the cloud-like on Google Cloud – it can also deploy data workloads into robust enterprise environments that could also be in the cloud or on-premises.
  • CloverDX is an enterprise data management platform that is also highly customizable and integrates well into complicated tech stacks, delivery processes, and automation requirements; this is true even when the data comes from or goes to different complex enterprise projects.
  • It has a Java-based Data Integration framework that makes it easy to run independently or embed into existing databases and file transfer applications, processes, and protocols – like RDBMS, SOAP, and HTTP.
  • It makes sure the data is clean with its built-in data quality features that work as the information is in motion; these features can be used to automatically clean up data by checking for data that doesn’t conform to preset rules as well as performing simple checks like validating email address and phone number formats.
  • Data cleaned up, processed, and transported can be made available in any format and type – like files, databases, and APIs, for example.

Try CloverDX FREE for 45-days or book a demo.

4. IBM InfoSphere DataStage

IBM InfoSphere DataStage is an ETL tool and part of the IBM InfoSphere Information Server. It uses graphical UIs to create data integration solutions. Coming from a company that has made data storage its bread and butter, it shouldn’t be a surprise that they have put all their knowledge about data mapping into their tool.

Looking at some of its features, we find:

  • The first thing anyone will notice about this tool is the easy-to-master UIs which allow for efficient data integration flows with almost no coding required.
  • It is highly scalable when it brings substantial data processing powers backed with in-built auto workload balancing capabilities for high performance and elastic management of computing
  • It can also integrate with a wide range of native products like IBM Cloud Pak for Data, allowing for data virtualization, business intelligence, data mining, and governance purposes.
  • After it has been processed and transformed, the data can be delivered to any destination, including for storage – like data warehouses and data marts – as well as being thrown back into processing by sending it all to operational data stores, real-time web services, and messaging system.
  • Users can auto-generate jobs and use custom rules to enforce them while ensuring clean data delivery using IBM InfoSphere QualityStage, which automatically resolves quality issues as data is inputted into target environments.

Try IBM InfoSphere DataStage for FREE.

5. Oracle Data Integrator

Oracle Data Integrator is a comprehensive data integration platform from one of the leading technology companies. It covers all data integration requirements: high-volume, high-performance batch loads to event-driven, trickle-feed integration processes and SOA-enabled data services.

Like most Oracle products, this too is targeted at larger enterprises that can invest in the tool and the technology needed to run it.

Looking at some features of the Oracle Data Integrator:

  • This quality product offers superior developer productivity, an improved user experience (UX), and a flow-based declarative user interface for easier control and mastery.
  • It easily integrates with other products on Oracle Cloud Infrastructure (OCI); for example, it can work with Object Storage and Object Storage Classic to ensure data is stored securely at all times.
  • ODI comes with a set of Knowledge Modules (KMs) – code templates that define entire integration processes – and ODI Tools to connect to Object Storage and Object Storage Classic for ELT of data in local directories or distributed storage systems like Hadoop Distributed File Systems (HDFS).
  • It even integrates and works with Oracle Enterprise Resource Planning (ERP) Cloud – a powerful suite of applications that support and enable every aspect of a business’ mission-critical processes like human capital management (HCM), finance, and project management.
  • It also caters to RESTful Service for secure connectivity with several parameters supported for maximum flexibility; it uses data chunking and pagination for moving larger data payloads.
  • A feature that stands out with ODI is its ability to enhance the ETL process with two types of dimensional objects: Dimensions and Cubes that are used to organize and store data in a more detailed form.
  • It also has a release management feature that helps create deployment objects in a development environment that are then deployed in a Quality Assurance environment. It is tested before it is moved into the production environment.

Download an evaluation version of Oracle Data Integrator for FREE.

6. Pimcore Product Information Management (PIM)

Pimcore Product Information Management (PIM) is designed to bind all the data on a business network and bring them together to be presented as up-to-date product data. It was developed using Enterprise Open Source technology and powered by easy-to-use APIs, which come together to allow for the retrieval of all data in real-time.

Pimcore Product Information Management (PIM) has more features:

Get a Pimcore Product Information Management (PIM) demo for FREE.

7. Talend Data Integration

Talend Data Integration is a data integration software solution that allows for ETL and data integration across enterprise-level cloud or on-premises architectures.

Talend is a scalable tool that offers over 900 pre-built components and can easily integrate into any corporate network environment.

Talend Data Integration has more features:

  • Talend offers an automated and unified approach, including integration, transformation, and mapping of data that then undergoes quality checks for clean and secure data flow every single time.
  • It can be used to work on any type of data, from any data source and to any data destination – be it on-premises or in the cloud.
  • It offers the flexibility of building vendor- or platform-independent data pipelines that can be run from anywhere using the latest cloud technologies; the Pipeline Designer makes it easy to design, deploy, and reuse the pipelines anywhere and under any new criterion.
  • One feature, the Data Fabric, helps with obtaining and maintaining the complete, clean, and uncompromised data needed to stay in control and mitigate risks; this feature, combined with the Data Inventory, makes it easy to discover, sift through, and share data.
  • Then we have the Data Preparation feature, which helps prepare data with intuitive self-service tools that offer data organization and collaboration functionalities.

Try Talend Data Integration for FREE.

Who are the data mapping tools for?

The ideal candidates for deploying one of the seven data mapping tools we have just seen are businesses with:

  • Data sources from various incompatible systems with a variety of data types
  • Complex network architectures and remote source and destination data hosts
  • Requirements for accurate, comprehensive, and real-time reporting of the overall health of the business – including remote sites
  • A budget that has been set aside for the significant data mapping process that needs to be handled with accuracy and in an organized manner

These are the types of requirements that make it a must for adopting and deploying one of the seven best data mapping tools and software we have seen in this post.

Let us know what you think – leave us a comment below.