BEST PRACTICES OF MIGRATING YOUR LEGACY SYSTEM DATA TO SAP BUSINESS ONE The session talks about the basics of data migration and takes you through a practical example by migrating data to SAP Business One
PRESENTED BY
ABHISHEK SUR Solution Architect, InSync Solutions Microsoft MVP
AGENDA
• Introduction to Data Migration • Why you need data migration • Types of migration • Different Phases of Data Migration • DEMO • Best Practices to ensure data quality and assurance.
• References
WHAT IS DATA MIGRATION
• Data migration is a set of activities that moves data from one or more legacy system to new application. • Data migration is generally necessary when support of legacy system expires or there is a need of changing of existing systems or infrastructure because of change in business scope or scale. • The objective of data migration is to ensure improvement in corporate performance and deliver competitive advantage. • Data migration is in general iterative process such that data quality can be maintained • ETL is the most preferred tool for data migration
BETTER DATA MIGRATION ACHIEVE
AVOID
• Better data quality into the new system
• High risk implementations from a business perspective
• A systematic approach to prioritize data to be moved to the target location • The ability to run both the systems together to minimize risk. • Ability to trace the flow of information across the systems
• Issues with reconciling common data across all systems.
• Inefficiency of time tested migration tools that increase cost and slows overall delivery. • Design flaws on delivering consistent data across platforms.
WHY DO YOU BOTHER ABOUT DATA MIGRATION? • Data is critical to a business • Technology is ever changing (Change is constant) • Adaptation to changing technology is important for any business. • Migration is inevitable because data creation is not a choice. • Data cleansing is sometimes important to ensure proper business growth. • Your legacy software solution does not solve your existing set of problems.
TYPES OF DATA MIGRATION
• Storage Migration • Database migration • Application migration • Business process migration
In this presentation, we will primarily restrict our talk on Business process migration processes.
LIMITATIONS OF DATA MIGRATION
• Transactional data is generally associated with a workflow, which is difficult to migrate. • Migration is data centric and prone to errors. If not specialized toolset is used for data quality analysis, data migration can create sleepless nights. • Data migration needs detailed understanding of the platforms which are considered for migration, the technology stack where they belong and the business process which they follow. • With changing policies it is hard to validate the migrated data against compliance.
DIFFERENT PHASES OF DATA MIGRATION SOURCE
EXTRACT START
DESIGN
TRANSFORM LOAD (ETL)
TARGET
TEST
SIGN OFF
START
• In Start, the data in the two or more application is performed. The business processes which the two application follows are analyzed and documented.
• During this phase the planning of data migration is performed, identification on What and How. • In this phase the project scoping is also done such that budget and timeline can determined. • The cost benefit analysis is performed
DESIGN
• In design phase the data is mapped to perform transformation. Data mapping is a set of rules applied for the designated source to accurately fit to the target.
• Data migration is designed in form of increments and each of the increments are separately audited. • The Dependency between data is objects are identified. • Sometimes mapping functions needs to be created to ensure fuzzy matching can be performed.
EXTRACT, TRANSFORM, LOAD (ETL)
• ETL is the execution mode of the data migration where data extraction, transformation in target format and loading back to the target is performed.
• ETL step is performed in loop such that during one iteration a small increment of data is synched. • Data is cleansed while it is being loaded on the target system.
TESTING
• Unit, system, volume, and batch application tests need to be carried out before finalizing the migration. • Ideal scenario is to upload a full volume chunked data sliced according to the business process into staged target location before testing approaches are performed. • According to the business process, the testing determines the data flaws and perform preventive measures.
SIGN-OFF / MAINTENANCE
• During this phase the entire dataset is transferred to the destination app and the project is considered as live. • In this phase, data is in high quality and both source and target is ready for production use. • Future data migration is considered for further enhancements.
DEMO
BEST PRACTICES OF DATA MIGRATION • Project scope should be clearly defined. • At each stage the project need to be profiled and audited to refine the scope • Minimizing the amount of data to be migrated is the key. • Defining a realistic budget and timeline is important.
• Prioritization should be made with top-down or target – driven approach. • Allow time for volume testing and issue resolution. • Manage migration in segments and incremental chunks. • Code focus needs to be on business objective and cost / benefits.
• Eliminate 11th hour fire fights. • Do not be in hurry to unplug the legacy platform
REFERENCES • Point 1 • Point 2
Q&A
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