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As manufacturing companies adopt more advanced technologies and systems, seamlessly migrating data from legacy systems becomes crucial for business continuity and minimizing downtime. However, data migration can be complex in industrial environments with hardware dependencies and proprietary protocols.
Recent studies have highlighted the common struggles with data migration projects, with 55% exceeding their budget and 62% encountering greater challenges than anticipated, leading to either difficulty or outright failure.
How to avoid these pitfalls? The answer lies in understanding the fundamentals of data migration in manufacturing.
What is Data Migration in Manufacturing?
Data migration refers to the transfer of data from one storage system or application to another. In manufacturing, companies may need to migrate data when upgrading enterprise resource planning (ERP) platforms, building new data warehouses and analytics tools, or moving systems to the cloud. The goal is to transfer all relevant historical and current data so it remains available in the new environment, facilitating processes such as big data analytics in manufacturing.
The global data migration market is experiencing exponential growth, with an estimated projected value of almost $23 billion by 2026. It is increasingly crucial for businesses to ensure they are equipped with the appropriate data migration tools and strategies to navigate this evolving landscape.
The Role of Data Migration in Manufacturing
- Enables Smart Manufacturing and Industry 4.0: Data migration allows manufacturers to consolidate data from disparate systems into centralized systems. This creates unified data lakes that enable advanced analytics, supply chain optimization, predictive maintenance, and other smart manufacturing use cases.
- Supports New Technologies: New technologies like IoT sensors, industrial wearables, and automated machines rely on integrated data platforms. Migrating legacy data into these new systems, facilitated by data management service, allows manufacturers to gain more value from their technology investments.
- Minimizes Downtime: As machinery and systems age, seamlessly migrating the data to newer platforms minimizes downtime events. This data transition allows production workflows to continue uninterrupted.
- Globalization and Supply Chain Needs: As manufacturing supply chains become more complex and globalized, consolidated, real-time data, managed through comprehensive data integration in manufacturing, enables better coordination and responsiveness across the value chain.
- Sustainability Goals: Unified manufacturing data systems allow for improved yield projections, waste reduction, energy optimization, and quality control – helping manufacturers meet their environmental impact objectives.
- Competitive Differentiation: Manufacturers that modernize their systems and processes through successful data migrations position themselves to be more data-driven, efficient, and responsive to customer needs.
Hence, by supporting critical initiatives like smart manufacturing, sustainability, and globalization, seamless data migration helps manufacturers gain a competitive edge while unlocking more value from their operations data. Moreover, according to Gartner’s projections, over 45% of IT expenditures on infrastructure management, business process outsourcing, and application software are expected to shift from conventional to cloud computing solutions by the year 2025, signaling a significant shift toward digital transformation in manufacturing.
Best Practices for Data Migration in Manufacturing
Migrating data across manufacturing systems presents complex integration and transition hurdles that can lead to budget overruns and failures. By following several best practices, manufacturers can achieve smooth data transitions.
Perform Extensive Data Analysis
Before planning a migration, compile a comprehensive catalog of all essential data across systems. Identify data relationships, dependencies, gaps, and inconsistencies. Evaluating data types, access controls, and security protocols in current systems allows the establishment of effective migration procedures. Conducting thorough analysis, facilitated by a robust Data Management Service in manufacturing, reduces risk and prevents data loss.
Prioritize and Stage Migrations
Not all data needs to move simultaneously. Prioritizing by production sequence and system dependencies allows for controlled, sequential transitions. Mapping data migration to operational procedures and batch processing stages minimizes migration points and technology hand-offs. Staging migrations over time with testing at each stage ensures minimal disruption.
Standardize Data and Protocols
Standardizing data schemas, structures, naming conventions, interfaces, and communication protocols between old and new systems eases migrations. Data standardization requires cross-functional input to meet needs across operations, analysis, and reporting. Documented data standards enable reusable migration plans.
Validate Extensively
Validating migrated data meets precision and integrity requirements and reduces faults propagating across connected manufacturing systems. Testing migrated data at each stage ensures information accuracy and reliability, with a key emphasis on meticulous data management in manufacturing practices. Validation also confirms properly mapped data relationships and dependencies.
Institute Fail-safes
Despite best efforts, some migration issues can still arise. Instituting backup systems and fail-over procedures limits downtime events. Failure identification, notification, and rollback protocols minimize disruption. Offline testing migration procedures reduce troubleshooting needs during cutover events.
Why Choose Intone?
In conclusion, data migration in manufacturing emerges as a pivotal process, driving the industry toward enhanced efficiency and competitiveness. As the manufacturing sector navigates the complexities of data migration, a strong emphasis on data integration emerges as a key enabler, ushering in a new era of interconnected systems and data-driven decision-making. Hence, we at Intone take a people-first approach to data optimization. We are committed to providing you with the best data integration and management service possible, tailored to your needs and preferences. We offer you:
- Knowledge graph for all data integrations done
- 600+ Data, and Application and device connectors
- A graphical no-code low-code platform.
- Distributed In-memory operations that give 10X speed in data operations.
- Attribute level lineage capturing at every data integration map
- Data encryption at every stage
- Centralized password and connection management
- Real-time, streaming & batch processing of data
- Supports unlimited heterogeneous data source combinations
- Eye-catching monitoring module that gives real-time updates
Contact us to learn more about how we can help you!