Webinar: Best Practices of Migrating your Legacy System Data to SAP Business One

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

THANK YOU

For more such webinars ,visit :

www.appseconnect.com/webinars

/appseconnect

/company/insync

/insyncsolutions