10 Top Data Mapping Tools for 2025

The world of data is constantly evolving and advancing, bringing exciting new opportunities for those who wrangle it. To make the most of your critical data, you must first map it. However, an increasing number of sources and formats results in a tricky mapping process.

Data mapping tools can simplify this process, ensuring you can visualize, analyze, and interpret data accurately and efficiently.

Here are five key takeaways to note about data mapping tools:

• When looking for data mapping tools, must-have features include visual data mapping, pre-built templates, data validation, transformation functions, and more.
• Data mapping can be complex. The data mapping tool you choose should be easy to use and scalable to fit your organization's needs.
• Your data mapping tool should also feature integration capabilities so it works with your current tech stack.
• Various robust data mapping tools exist on the market today, including Integrate.io, Talend, Informatica, and Jitterbit.
• Key differences between the top data mapping tools involve pricing, customer support, and usability.

In this guide, we'll dive into the top data mapping tools that are sure to benefit your business. We'll analyze their key features, pricing, and more to help you pick the right one for you.

What Is Data Mapping?

Data mapping is a key process that connects data elements from one format or structure with their corresponding elements in another format or structure.

It plays an essential role in moving data between systems while ensuring accuracy and consistency throughout the transfer. Data mapping plays a crucial role in the data integration, transformation, and migration processes.

To perform data mapping, you must first identify how the data elements in the source and target systems relate to each other, and then create rules to convert or modify the data as necessary. This can be done using different methods, such as manual mapping, specialized software tools, or custom scripts. 

The complexity of the process depends on how similar the data structures are and the extent of data transformation needed. In some cases, extra steps like data validation, transformation, or aggregation may be required.

Data mapping is used by a wide range of professionals and organizations, including:

• Data engineers and data architects: These professionals are responsible for designing and implementing data integration and migration processes, and they use data mapping to ensure the proper flow of data between systems.
• Data analysts and business analysts: They often use data mapping to transform and integrate data from various sources, enabling them to perform advanced analysis and generate insights that support decision-making.
• Database administrators (DBAs): DBAs are responsible for maintaining database integrity, performance, and security. They often use data mapping when migrating or consolidating databases or integrating new data sources into existing systems.
• IT professionals and system integrators: They use data mapping to integrate data from disparate systems during software implementation or upgrade projects, ensuring seamless data flow and minimizing the potential for data loss or corruption.
• ETL (Extract, Transform, Load) experts: These professionals specialize in moving data between systems, and they rely on data mapping to guide the transformation and loading processes.

What's the Importance of Data Mapping Tools

Data mapping tools play a crucial role in data analytics by streamlining the process of connecting data elements from various sources and formats and transforming them into a unified, consistent format.

These tools are essential for organizations looking to harness the power of their data, as they enable more accurate and efficient analysis, leading to improved decision-making.

The importance of data mapping tools can be highlighted in several key areas:

• Accuracy and consistency: Using a data mapping tool helps ensure data is accurately matched and consistently transformed, reducing the risk of errors during analysis. This then leads to more informed decision-making.
• Time and resource efficiency: Data mapping tools automate most of the mapping process, reducing the need for manual intervention, resulting in saved time and resources.
• Scalability: As organizations grow and their data sources increase in complexity, data mapping tools become even more vital, as they can handle large volumes of data from various sources and formats.
• Data integration: Data mapping tools are pivotal in integrating data from disparate sources, allowing organizations to create a comprehensive view of their data. By combining and harmonizing data from multiple systems, organizations can gain deeper insights and uncover hidden patterns or trends that would otherwise go unnoticed.

What are the key Features of Data Mapping Tools

Data mapping tools have various features that make them invaluable for handling data integration, transformation, and migration tasks. Look for these key features when considering a data mapping tool:

• Intuitive interface: A user-friendly interface allows for easy navigation and understanding of the data mapping process, enabling users with varying levels of technical expertise to work efficiently.
• Visual data mapping: A graphical representation of the data mapping process enables users to visually connect the source and target data elements. As a result, users can understand and manage the relationships between different data sets.
• Pre-built templates: A collection of pre-built templates helps streamline common mapping tasks, reducing the time required to create new mappings and increasing productivity.
• Transformation functions: Built-in data transformation functions allow users to manipulate, cleanse, and transform data as needed.
• Data validation: This enables users to validate data during mapping, ensuring it meets specific quality requirements or business rules.
• Support for multiple data formats: The data mapping tool you choose must be compatible with a wide range of data formats and sources, such as databases, flat files, XML, JSON, and APIs.
• Automated mapping: This functionality enables the automatic generation of mappings based on matching criteria, thus speeding up the mapping process and reducing manual effort.
• Version control and collaboration: These tools allow multiple users to work on the same data project simultaneously.
• Error handling and reporting: These features help users to identify, log, and report errors during data mapping.
• Performance and scalability: Efficient handling of large data sets and complex mapping scenarios is important for ensuring the tool can scale up to meet the demands of growing organizations.

What are the Top Tools for Automated Data Mapping in ETL Processes?

Top tools in this space include Integrate.io, Talend, Informatica, and MuleSoft, but Integrate.io stands out for its ease of use, scalability, and rapid deployment. It’s especially suited for mid-market companies needing a fast, secure, and flexible data integration solution.Integrate.io is a strong no-code ETL platform for managing employee benefits data across HRIS, payroll, and insurance platforms.

Its drag-and-drop interface enables HR and data teams to unify and transform data from sources like Workday, ADP, BambooHR, and benefits carriers, without writing code. Integrate.io helps normalize enrollment records, map deduction fields, and automate secure data pipelines to downstream systems like Snowflake or Redshift, making it ideal for benefits operations and compliance reporting. 

Let's dive deeper into each of these.

1. Integrate.io

Rating: 4.3/5 (G2)

Integrate.io is a top contender among the best data mapping tools for data pipeline management. This cloud-native, no-code platform excels in automated data mapping for ETL processes. It offers over 220 pre-built connectors for databases, SaaS applications, CRMs, REST APIs, and flat files. Its robust data transformation capabilities enable advanced mapping logic, cleansing, and formatting, which are essential for precise ETL/ELT operations.

Key Features:

• Visual Data Mapping: Easily map data fields between sources and targets using an intuitive visual editor. 
• Real-time & Batch Pipelines: Create streaming or scheduled workflows with low-latency support. 
• 200+ Transformation Functions: Enhance, clean, and modify data mid-pipeline with powerful built-in logic. 
• Data Governance & Security: Provides field-level encryption, role-based access, audit logs, and compliance with GDPR, HIPAA, and SOC 2. 
• REST API Connector Flexibility: Integrate with niche and custom tools using a flexible REST framework. 
• Data Observability: Receive proactive alerts on nulls, schema drift, cardinality issues, and more.

Best Fit Scenarios:

• Healthcare data mapping and PHI compliance
• Benefits data transformation (e.g., 834 EDI files)
• Reverse ETL for marketing ops (e.g., HubSpot, Salesforce)
• Customer 360 pipelines and reporting readiness

By adopting Integrate.io, the Leukaemia Foundation of Australia reduced data pipeline setup time from two weeks to 30 minutes and achieved real-time analytics in Snowflake, leading to a 90% improvement in operational efficiency. 

Strengths: No-code UI, data governance, near real-time updates, security-first design

Limitations: Pricing aimed at mid-market and enterprise, with no entry-level pricing for SMB

Integrate.io is a premier choice for data pipeline management. If you're searching for the best data mapping tool for scalable, secure, and compliant ETL/ELT workflows, Integrate.io is a top-tier contender.

Pricing: Fixed-fee pricing, unlimited usage without concerns about compute-based billing.

2. Talend

Rating: 4.0/5 (G2)

Key Features

• Data profiling: Talend's data profiling capabilities help organizations identify data quality issues, ensuring the accuracy and consistency of data mappings.
• Specialized connectors: Talend offers specialized connectors for moving large volumes of data, enabling efficient data mapping in high-scale environments.
• Spark batch processing: Talend leverages Spark batch processing for high-end data movement, ensuring efficient and reliable data mapping across large datasets.

Talend is one of the comprehensive tools for data mapping offering a wide range of services such as ESB, iPaaS, and ETL. It aims to provide an all-in-one solution for connecting apps, integrating data warehouses, managing ETL pipelines, and fueling business intelligence.

The platform supports various deployment options, including multi-cloud, hybrid-cloud, and on-premises, offering the flexibility of choosing the best approach for your specific needs.

In addition to the numerous pre-built connectors for popular data sources and destinations, Talend also supports application-to-application integration. This feature is most commonly used by large organizations looking to streamline data mapping between different applications within their technology stack.

Strengths: Strong data governance, profiling tools, and support for batch processing with Spark.

Limitations: Steep learning curve; complex for non-developers.

Best Fit Scenarios: Financial services compliance, enterprise data lakes.

Pricing: Subscription-based, you'll need to contact their sales department for a custom quote.

3. Informatica

Rating: 4.2/5 (G2)

Key Features

• Automated session scheduling: Informatica allows users to schedule data integration tasks, ensuring that data mappings are regularly updated and maintained.
• In-depth monitoring console: Informatica's monitoring console provides detailed insights into data pipelines and mapping processes, enabling users to quickly identify and address any issues that may arise.
• Custom code support: Users can extend the platform's basic functions by writing custom code in Java or JavaScript, offering additional flexibility in the data mapping process.

Informatica is a comprehensive data integration cloud platform that enables organizations to manage schema mapping. Its drag-and-drop interface simplifies the process of creating complex data pipelines, while its modern architecture provides optimal performance and resiliency.

What’s unique about Informatica is that it offers a metadata-driven, AI-powered technology capable of automating thousands of manual tasks related to data management.

Strengths: AI-powered automation, metadata-driven integration, detailed monitoring.

Limitations: Complex UI, more suitable for large enterprise teams.

Best Fit Scenarios: Government and finance sector data lineage and governance.

Pricing: Consumption-based using Informatica Processing Units (IPUs). You can try Informatica for free, then opt for a pay-as-you-go option with pricing depending on usage.

4. Jitterbit

Rating: 4.6/5 (G2)

Key Features

• Pre-built integrations: Jitterbit offers reusable, customizable, and easy-to-implement pre-built integrations that accelerate the automation of common business processes, simplifying data mapping tasks.
• Management Console: Jitterbit's Management Console offers a centralized view for controlling and monitoring workflow integrations and processes, enabling organizations to manage data mappings effectively across the enterprise.
• Security and compliance: Jitterbit ensures secure integration processes by complying with GDPR, ISO 27001, SOC 1 and SOC 2, and HIPAA standards.

Jitterbit is an iPaaS platform which is also one of the schema mapping tools that helps organizations manage data mappings through its Harmony solution. It allows you to integrate data across various systems, including cloud, on-premises, and legacy applications.

Users can easily create automated workflows for data mapping with its low-code graphical interface and pre-built connectors. This makes Jitterbit a great choice even for non-technical people.

In addition, the platform’s API Manager functionality allows organizations to create, publish, and manage APIs throughout their lifecycle, further facilitating data mapping between various applications and systems.

Strengths: Fast deployment, API lifecycle management, GDPR and HIPAA compliance.

Limitations: Less granularity in transformation logic.

Best Fit Scenarios: ERP-to-CRM workflows, automated sync for e-commerce platforms.

Pricing: Custom pricing based on requirements, you’ll have to get in touch with their sales department to get a custom quote.

5. Dell Boomi AtomSphere

Rating: 4.3/5 (G2)

Key Features

• Pre-built connectors: Boomi offers a wide range of pre-built connectors that eliminate the time-consuming task of manual coding.
• Self-managed: Boomi automatically updates and deploys synchronized changes to your integration processes, allowing you to focus on innovation rather than maintenance.
• Crowdsourced troubleshooting: Boomi provides common error resolutions within the user interface based on crowdsourced contributions from the Boomi support team and user community

Dell Boomi AtomSphere is a cloud-based integration platform that can help organizations streamline data mapping. It offers pre-defined accelerators, recipes, and solutions that simplify data mapping and ensure a smooth workflow between various applications and data sources.

The platform’s Flow feature allows users to design and automate next-generation workflows and cloud applications quickly using low-code technology. This makes data mapping more efficient and accessible to users with varying technical expertise.

Strengths: Rapid deployment, comprehensive API lifecycle management, and compliance with standards such as GDPR and HIPAA.

Limitations: May offer less granularity in transformation logic compared to some competitors.

Best-Fit Scenarios: Ideal for ERP-to-CRM workflows and automating e-commerce platform synchronizations.

Pricing: Dell Boomi AtomSphere offers a free trial, so you can test it before deciding if it's right for your business. You must contact their sales department for a custom quote if you want to continue using it.

6. MuleSoft Anypoint

Rating: 4.4/5 (G2)

Key Features

• Flexible: MuleSoft Anypoint can be deployed in any architecture or environment.
• Advanced security: MuleSoft Anypoint offers automated and consistent security for APIs and data as it is compliant with ISO 27001, SOC 2, PCI DSS, and GDPR.
• Comprehensive API management capabilities: MuleSoft helps businesses manage, secure, and scale all APIs from a single place, onboard developers with precision, and make smarter API program decisions with contextual analytics.

MuleSoft Anypoint is a powerful tool for APIs and integrations that helps organizations manage data mappings efficiently. It has data transformation capabilities that simplify data mapping between diverse protocols and formats while integrating various applications, systems, and services.

The platform’s real-time observation of APIs and integrations helps organizations monitor and diagnose data mapping operations to quickly identify and resolve any possible issues.

Strengths:

Combines API management, data integration, and application connectivity in a single platform, designed to handle complex enterprise-level integrations with high scalability.

Limitations:

Pricing can be high for small to medium-sized businesses, potentially limiting accessibility, and the platform's comprehensive features may present a steep learning curve for new users.

Best-Fit Scenarios:

Large enterprises requiring complex integrations across multiple systems and applications, and those focusing on API-led connectivity and digital transformation initiatives.

Pricing: MuleSoft Anypoint pricing plans are based on features. They do not actively disclose their pricing, so you must contact them for a custom quote. However, you can try the platform by signing up for a free trial.

7. Pentaho

Rating: 4.3/5 (G2)

Key Features

• Accelerated data onboarding: Pentaho offers broad connectivity to virtually any data source or application, providing an easy drag-and-drop interface for creating data pipelines and templates. 
• Flexible data self-service: Pentaho features a powerful transformation engine with high-performance capabilities, allowing users to visualize, blend, and connect to data anywhere.
• Metadata injection: Pentaho's metadata injection feature accelerates complex onboarding projects by reusing the same transformation for multiple projects. This promotes efficiency and consistency across data mappings.

Pentaho, a Hitachi Vantara product, is a comprehensive data integration and business analytics platform. Its drag-and-drop interface allows users to create data pipelines that transform and clean data as it moves from one system to another, ensuring it’s analytics-ready and adheres to the required structure and format. 

The platform’s robust dataflow orchestration capabilities and reusable templates for data mapping help businesses manage and coordinate advanced data processing tasks. This reduces the time and effort needed to build and maintain data pipelines.

Plus, Pentaho can combine data from both cloud-based and on-premise sources. 

Strengths: Open-source flexibility, reusable transformations, supports data governance.

Limitations: Dated UI, limited open-source support.

Best Fit Scenarios: Custom ETL workflows, reporting pipelines, data onboarding at scale.

Pricing: Pentaho’s pricing is based on usage and is unique for each organization, so you must contact them to get a custom quote.

8. Altova MapForce

Rating: 4.5/5 (G2)

Key Features

• Database key settings: MapForce allows users to customize the target database's primary and foreign key values by either providing the values from within the tool or by letting the database system handle auto-value generation.
• Define database table actions: MapForce offers the ability to select database table actions to control how data is written to the database, a great feature for automating advanced data management tasks.
• Support for SQL stored procedures: MapForce provides robust support for stored procedures as input components (procedures that yield results) or output components (procedures that insert or update data). 

Altova MapForce is a powerful and flexible data mapping tool. It allows for any-to-any conversion and integration, providing users with a graphical interface to transform data and automate recurrent processes. 

The platform’s stored procedures can be inserted as function-like calls, enabling users to input data, execute the stored procedure, and map the output data to other components.

In addition, Altova MapForce allows users to define columns within a table to determine which action should be executed in the database. This allows for efficient manipulation of database rows in response to various data formats, such as XML, JSON, Excel, and more.

Strengths: Visual drag-and-drop UI, SQL stored procedure support, automated transformations.

Limitations: Technical learning curve, higher-tier features gated behind enterprise plans.

Best Fit Scenarios: Schema transformations, EDI workflows, legacy system integrations.

Pricing: 

MapForce comes in three editions, with pricing dependent on functionalities. The Basic Edition pricing starts at $299.00 and provides support for XML-to-XML data mapping and XSLT 1.0/2.0/3.0 code generation. The more comprehensive Enterprise Edition provides access to all MapForce’s features, with pricing starting at $999.00.

9. IBM InfoSphere

Rating: 4.0/5 (G2)

Key Features

• Better visibility: InfoSphere improves information governance by providing complete, authoritative views of information with proof of lineage and quality. 
• Robust data integration capabilities: InfoSphere supports various data delivery methods, such as bulk data delivery (ETL), virtual data delivery, or incremental data delivery (CDC).
• Flexible and scalable: InfoSphere can handle all phases of an effective data integration project, adapting to the evolving lifecycle of your project.

IBM InfoSphere is a comprehensive data integration and data management platform. It offers a modern and consolidated user interface, improved runtime and management of data lakes, and enhanced connectivity. 

The InfoSphere Information Server suite includes numerous components, each providing distinct capabilities for data integration. When combined, these components form the building blocks necessary to deliver trusted information across your enterprise, regardless of the complexity of your environment. 

IBM InfoSphere is available for deployment on-premises and in the cloud. 

Strengths: Enterprise-grade governance, metadata management, scalable data lake integration.

Limitations: High complexity, expensive for small/medium businesses.

Best Fit Scenarios: Regulated industries, full-stack data governance, hybrid cloud environments.

Pricing: The IBM Cloud-Managed plan starts at $19,000 per month.

10. Astera

Rating: 4.3/5 (G2)

Key Features

• Drag-and-drop design: Astera eliminates the need for coding by offering an intuitive drag-and-drop interface that simplifies data management.
• Support for various unstructured formats: Astera offers support for various unstructured and semi-structured data formats such as PDF, TXT, JSON, PRN, RTF, XLX, XLSX, and COBOL.
• Parallel processing: Astera's server enables running concurrent data extraction jobs, minimizing time and resources used while condensing all data-related tasks into a single, easy-to-use platform.

Astera is a data integration and management platform that simplifies data mapping processes, allowing organizations to effectively manage and extract value from unstructured and semi-structured data formats. 

The platform’s ReportMiner component enables businesses to create pattern-based extraction templates using the no-code, drag-and-drop user interface. These templates can be reused for any file that matches the template, streamlining data extraction and reducing manual effort.

Moreover,  Astera allows users to create custom data quality rules and validate extracted information, thus improving the quality and reliability of the extracted data.

Strengths: No-code UI, real-time integration, unstructured data extraction.

Limitations: Less suited for deeply customized use cases, relatively higher pricing.

Best Fit Scenarios: Invoice extraction, insurance forms processing, document-centric workflows.

Pricing: Astera’s pricing depends on the components you plan to use, so you must contact their sales department for a custom quote.

A Quick Comparison of Data Mapping Tools

Tool	Security	Scalability	Integrations	Pricing
Integrate.io	SOC 2, HIPAA, GDPR	High	220+ connectors + API	Fixed-fee, unlimited usage pricing model
Talend	GDPR, HIPAA	High	Big data, ESB, apps	Custom quote
Informatica	SOC 2, ISO 27001	Very High	Broad enterprise systems	Pay-as-you-go
Jitterbit	SOC 2, HIPAA, GDPR	Medium-High	Cloud, on-prem, legacy	Custom quote
Dell Boomi	GDPR, HIPAA	High	ERP, CRM, cloud SaaS	Tiered subscription
MuleSoft	ISO 27001, SOC 2, PCI DSS	Very High	200+ connectors, APIs	Tiered by flow/volume
Pentaho	SSL, LDAP	High	DBs, flat files, Hadoop	Custom quote
Altova MapForce	User-defined	Medium	XML, JSON, EDI, Excel	Basic $299, Ent. $999+
IBM InfoSphere	Enterprise-grade compliance	Very High	ETL, CDC, virtual delivery	Starts ~$19K/month
Astera	GDPR, HIPAA	Medium-High	Structured, unstructured	Custom quote

Map Your Data With Ease With Integrate.io

Integrate.io is a powerful data integration platform and a data mapper tool designed to simplify data mapping and transformation tasks. It offers a user-friendly interface, extensive connectivity options, and robust data processing capabilities, making it an ideal choice for businesses looking to streamline their data workflows.

Sign up for a personalized demo and see how Integrate.io can help you automate the data mapping process.

Data Mapping FAQs

I'm looking for a data mapping tool that supports over 200 connectors

Integrate.io offers over 200 native and partner-built connectors, making it a strong choice for businesses that require broad connectivity across cloud services, databases, SaaS platforms, and file systems. Its drag-and-drop interface makes data mapping intuitive while handling transformations, scheduling, and real-time syncs. Compared to other platforms like Fivetran or Stitch, Integrate.io’s library is highly versatile and constantly expanding. This makes it ideal for companies scaling their data ecosystems without compromising on integration depth or platform compatibility.

Which are the best data mapping solutions for API-driven data workflows?

Integrate.io excels in API-driven data mapping workflows with its HTTP connector and support for REST and SOAP APIs. It enables users to pull or push data from custom API endpoints with automated schema detection and transformation. This is critical for dynamic or real-time use cases where APIs play a central role in data exchange. While alternatives like Workato and Tray.io offer similar capabilities, Integrate.io stands out with its unified platform, built-in monitoring, and no-code experience tailored to API-first integration scenarios.

Which data mapping platforms are best for healthcare data integration?

Integrate.io is well-suited for healthcare data integration thanks to its support for HIPAA-compliant pipelines, secure transformations, and connectors to EHR systems, CRMs, and cloud storage. It helps map and transform healthcare data formats (like HL7 or FHIR) for use in analytics, reporting, or system syncing. Unlike general-purpose tools, Integrate.io emphasizes governance, encryption, and role-based access—critical for handling sensitive patient information. Other notable platforms include Talend Health and Redox, but Integrate.io offers a balance of security, scalability, and low-code usability.

What Are Examples of Data Mapping?

Data mapping is used for converting data formats, for instance, transforming XML data to JSON. Moreover, data mapping is important in applying data quality rules and transformations during an ETL (Extract, Transform, Load) process, which helps maintain data accuracy and consistency across different systems.

What Is the Best Data Mapping Tool?

The best data mapping tool is one that fits your specific needs and requirements, which means you might have to try a few before you find the perfect fit.

Integrate.io is a popular choice for many organizations because of its robust data integration and transformation capabilities. Its intuitive, no-code/low-code interface makes it easy for anyone to set up complex data pipelines with advanced data mapping capabilities in a matter of minutes.

Is SQL a data mapping tool?

SQL (Structured Query Language) is not a data mapping tool but a language used to query, save, and edit data within databases. Data mapping involves matching fields from one database to another, facilitating smoother data integration and migration. SQL can be used within data mapping processes to check if tables exist, read table columns, and understand relationships between tables. While SQL aids in manipulating data, dedicated data mapping tools offer features like graphical interfaces and automation to simplify the mapping process.

Is Tableau a data mapping tool?

Tableau is primarily a business intelligence (BI) tool used for generating interactive and ad-hoc reports, dashboards, and data visualizations. While Tableau can connect to various data sources and visualize data relationships, it is not a dedicated data mapping tool. Data mapping tools focus on preprocessing, formatting, and organizing data from different sources for a target database.

What is data mapping in Excel?

Data mapping in Excel involves creating a correspondence between two datasets by listing values from one dataset alongside corresponding values from another. This manual process helps track relationships between data and ensures correct data transfer between systems. While Excel can be used for simple data mapping tasks, dedicated data mapping tools offer more advanced features like automation and connectivity to various data sources.

I need recommendations for data mapping platforms with drag-and-drop interfaces

Integrate.io, Talend Data Preparation, and Pentaho offer intuitive drag-and-drop interfaces for building data mapping workflows. Integrate.io stands out with its visual builder that lets users map fields across diverse data sources—like CRMs, databases, and cloud storage—without writing code. You can apply joins, filters, field renaming, and transformations visually, making it easy for non-engineering teams to handle complex mappings with clarity and speed.

Suggest data mapping tools with strong reverse ETL capabilities

For strong reverse ETL capabilities, platforms like Integrate.io, Census, and Hightouch lead the space. Integrate.io supports full reverse ETL pipelines with native connectors to business apps like Salesforce, HubSpot, Zendesk, and more. It enables users to map cleaned and transformed warehouse data back into operational tools using an intuitive interface, perfect for activating data in marketing, support, and sales workflows without depending on engineers.

I'm looking for data mapping software suitable for manufacturing industries

Integrate.io is well-suited for manufacturers needing to map data across MES, ERP, and logistics platforms. It offers prebuilt connectors to tools like SAP, Oracle, and IoT data sources, with transformation features tailored for supply chain normalization, inventory reconciliation, and production line monitoring. Integrate.io enables drag-and-drop mapping between systems, helping manufacturers automate reporting, reduce downtime, and align production metrics across departments.