SAP data integration is the process of connecting and synchronizing data between SAP and other systems, applications, or databases to ensure consistent and reliable information across the entire IT landscape.
SAP data integration and data migration are often confused. In this article, we clarify the difference and explain how integration works.
Many organizations confuse data integration with data migration, but they serve very different purposes.
Integration focuses on keeping systems in sync over time, often in real time.
Migration, on the other hand, is about moving data from one system to another, typically as part of a transformation, system replacement, or consolidation project.
At Hopp Tech, we specialize in data migration.
However, Hopp Tech can support some integration scenarios where data is transferred at scheduled intervals such as weekly or monthly batch processes.
If you're planning a migration project and want a fast, transparent, and structured process, visit Hopp Techs to learn more about how Hopp Tech can help.
How Does Data Integration Work with SAP?
SAP Data Integration
- Definition: Data integration refers to the ongoing connection between SAP systems and other platforms or data sources. The goal is to ensure that data remains synchronized and consistent across systems, so that changes made in one system are quickly reflected in others.
- Purpose: The main purpose of data integration is to support daily business operations by keeping all relevant systems up-to-date with the latest information. This allows organizations to make informed decisions and automate processes across multiple applications.
- Scope: Data integration typically includes real-time or scheduled (batch) data exchanges between SAP and non-SAP systems. These exchanges may involve customer data, transactional updates, inventory levels, or any other business-critical information that needs to flow between systems.
- Typical Tools: Common tools used for SAP data integration include SAP PI/PO, SAP Business Technology Platform (BTP) Integration Suite, SAP Data Intelligence, as well as APIs and custom batch processing frameworks designed to move data efficiently between systems.
- When It Happens: Data integration is a continuous process. It operates in the background as part of regular business operations - often running in real-time or at frequent intervals to maintain system alignment.
How is SAP Data integration different from SAP Data Migration?
Although the terms are often used interchangeably, data integration and data migration serve different purposes in the SAP ecosystem.
SAP Data Migration
- Definition: The one-time transfer of data from a legacy system or source into a SAP system (e.g., during a move to SAP S/4HANA).
- Purpose: Usually, part of a larger digital transformation or system upgrade.
- Scope: Focuses on cleaning, mapping, and loading historical and master data into a new environment.
- Typical Tools: SAP Migration Cockpit (LTMC), IDocs and LSMW.
- When It Happens: Before go-live, during system transitions, mergers, or consolidations.
In Short:
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Data Migration
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Data Integration
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Frequency
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One-time (project-based)
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Continuous (operational)
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Goal
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Move historical data into SAP
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Keep systems in sync
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Use case
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System upgrade, consolidation
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Daily operations, cross-platform syncing
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Tools
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Hopp SAP, LTMC, IDocs
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PI/PO, BTP, APIs, Batch Pipelines
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Hopp SAP: A Purpose-Built Approach to SAP Data Migration
While many tools aim to handle SAP data migration through generalized or highly complex platforms, Hopp SAP takes a different path: one that’s focused, structured, and built for batch-based data processing.
By using business objects instead of rows and tables, Hopp SAP aligns technical data flows with real-world business logic.
This unique approach ensures that organizations can:
- Accelerate SAP migration projects without writing custom scripts or relying on external consultants.
- Simplify transformation and mapping through low-code, business-friendly interfaces.
- Ensure transparency and compliance with built-in validation, version control, and audit-ready reporting.
- Handle scale with ease, from small template-based uploads to multi-terabyte enterprise migrations.
Hopp SAP supports the entire lifecycle from source extraction and transformation to structured, validated loading, giving you a streamlined, scalable way to connect, consolidate, and move data in and out of SAP systems while reducing risk, effort, and time-to-value.
Why is SAP Data Integration Important?
SAP data integration is essential for businesses to ensure seamless data flow across systems, improving efficiency, decision-making, and scalability.
By integrating SAP with other systems, companies create a centralized data repository, providing a single source of truth and insights for better strategic decisions.
It enhances operational efficiency by automating data transfer, reducing errors, and speeding up processes.
Data integration also supports better data governance and compliance, ensuring secure and accurate handling of information.
Additionally, it streamlines reporting, analytics, and customer experience, providing businesses with accurate insights and a unified view of customer data. Ultimately, SAP data integration drives cost savings, reduces manual effort, and supports business growth in a dynamic digital landscape.
Step-by-Step Process for SAP Data Integration
- Data Extraction: Data is pulled from various sources such as legacy systems, cloud platforms, or databases typically in batches. This is often handled through secure connectors, flat file exports, or pre-configured templates.
- Data Transformation: Before loading, data is cleaned, mapped, and formatted to match SAP’s structures. Hopp Tech supports transformation logic that ensures the data aligns with the target environment.
- Batch Data Loading: The transformed data is uploaded into SAP systems such as S/4HANA or BW at defined intervals, using tools like SAP Migration Cockpit or IDocs.
- Validation and Monitoring: Built-in validation and monitoring help catch errors early.
Step-by-Step Process for SAP Data Migration
While data integration and data migration may seem similar at first glance, their differences become clear when you look at the process step by step.
- Scope & Analyze: Define the data objects and volumes to be migrated. Identify dependencies, risks, and data quality issues early.
- Extract: Pull legacy data from source systems using flat files, database queries, or built-in extractors.
- Cleanse & Transform: Clean, validate, and format data to meet SAP target structures and business rules.
- Load into SAP: Use tools like Hopp SAP, LTMC, or IDocs to securely import data into SAP.
- Validate & Reconcile: Run pre- and post-load validations to ensure data accuracy, completeness, and auditability.
- Dry Runs & Cutover: Perform test migrations, fix errors, and prepare a final cutover plan for go-live.
Most Important Tools for SAP Data Integration
While there are many tools available for SAP data integration, the most crucial ones stand out for their ability to streamline processes, improve accuracy, and ensure seamless connectivity between SAP and other systems.
Below are the most important tools that organizations should prioritize when working with SAP data integration:
SAP Migration Cockpit (LTMC)
Used primarily for migrating data to SAP S/4HANA with pre-configured templates, automation, and error reduction.
SAP Process Integration (PI/PO)
Middleware that enables real-time data exchange between SAP and non-SAP systems, automating complex cross-system communication.
SAP Data Services
A powerful ETL tool with capabilities for data extraction, cleansing, validation, and transformation from diverse sources.
SAP Business Technology Platform (BTP) Integration Suite
A cloud-based platform for flexible, scalable integration using APIs, event-driven architectures, and pre-built connectors.
SAP Data Intelligence
Combines integration, data governance, and AI/ML to manage and optimize large-scale, multi-source data pipelines.
IDocs (Intermediate Documents)
Standard SAP format for structured, secure system-to-system data exchange, usable in both batch and real-time contexts.
Best Practices for SAP Data Integration
- Define Clear Objectives : Set clear integration goals, such as improving data accuracy, real-time reporting, or operational efficiency, to guide the integration process.
- Data Quality Management : Prioritize data cleansing and validation before integration to ensure accurate and reliable data in the SAP system.
- Use Standardized Tools and Templates : Leverage standardized SAP tools like LTMC, PI/PO, and BTP Integration Suite for seamless integration, reducing errors and improving efficiency.
- Automation : Automate repetitive data processing tasks and workflows to reduce manual errors and speed up processes.
- Test and Monitor : Conduct extensive testing during integration and continuously monitor the integration processes to identify issues and ensure smooth operations.
- Documentation and Compliance : Maintain detailed documentation of the integration process, configurations, and data flows to ensure compliance and traceability.
Challenges in SAP Data Integration
- Data Quality Issues : Inconsistent, incomplete, or inaccurate data can cause integration errors and disrupt business processes.
- System Compatibility : Integrating SAP with legacy systems, third-party software, or cloud platforms may pose compatibility challenges, requiring additional customization.
- Real-Time Data Processing : Ensuring real-time integration and data synchronization can be complex, especially when handling large volumes of data across multiple systems.
- Complexity of Data Governance : Managing data security, privacy, and compliance across different systems and regions can be challenging without proper governance frameworks.
- Resource Constraints : Data integration projects can be resource-intensive, requiring significant time, expertise, and budget allocation.
- Scalability Issues : As businesses grow, their integration needs evolve and ensuring that the integration infrastructure can scale to handle increasing data volumes can be a challenge.