Webinar: Do’s and Don’ts: Data Migration to Oracle Cloud

Abstract:

Data migration plays a significant role in cloud project efforts, often constituting a substantial portion of the overall workload. Without a thorough understanding of both the source and target applications, the process of transferring data into cloud applications can exacerbate several challenges, leading to amplified negative impacts on the project.

The Significance of Data Migration in Cloud Projects

Data migration, accounting for a considerable 25% to 30% of cloud project efforts, is a pivotal phase that demands meticulous attention. Insufficient comprehension of both the source and target applications during data transfer into cloud platforms can intensify various challenges and pose potential risks to the success of the project.

Challenges Faced in Data Migration to Cloud Applications:

1. Data Quality and Relevance: Inaccurate or irrelevant data transferred into cloud applications can lead to compromised data quality. The integration of flawed or obsolete information might perpetuate hidden legacy issues, adversely impacting operational efficiency and decision-making within the cloud environment.

2. Amplification of Legacy Problems: Migrating data without addressing underlying issues in the source data can amplify existing problems. Flaws, inconsistencies, or inaccuracies within the legacy data might persist and potentially magnify in the new cloud environment, disrupting processes and functionality.

3. Increased Project Risk: Inadequate understanding and planning for data migration can escalate project risks. These risks may include project delays, cost overruns, operational disruptions, compromised data security, and unsatisfactory user experiences within the cloud system.

Mitigating Project Risk in Data Migration:

1. Comprehensive Assessment and Planning: Conduct a thorough assessment of both source and target applications before data migration. Develop a meticulous plan that encompasses data cleansing, transformation, mapping, and validation processes to ensure data integrity.

2. Data Cleansing and Quality Checks: Prioritize data quality by cleansing, enriching, and validating the data set to be migrated. Eliminate redundant, obsolete, or inaccurate data and establish protocols for ongoing data maintenance in the new cloud environment.

3. Testing and Validation: Perform extensive testing and validation post-migration to ensure data accuracy, completeness, and compatibility within the cloud applications. Create robust data validation processes to detect and rectify any discrepancies promptly.

4. Training and Change Management: Invest in training and change management initiatives to empower users with the skills and knowledge required to handle data effectively within the new cloud platform.

While data migration can pose significant challenges, a proactive approach centered around comprehensive planning, data quality assurance, rigorous testing, and ongoing maintenance can substantially mitigate risks. By addressing these challenges effectively, organizations can harness the full potential of their cloud environments while minimizing potential pitfalls associated with data migration.

Join this webinar to learn about:

->  Do’s and don’ts in cloud data migrations
->  Migration strategies
->  Ways to migrate data into Oracle Cloud
->  Testing strategies
->  NexInfo’s Data Migrator – A cloud-based automation tool to migrate data from EBS