Data Migration Need, Strategy, Challenges, Methodology, Categories, Risks, Uses with Cloud Computing, and Improvements in Its Using with Cloud Using Suggested Proposed Model (DMig 1)

Abstract

Data Migration is a multi-step process that begins with analyzing old data and culminates in data uploading and reconciliation in new applications. With the rapid growth of data, organizations constantly need to migrate data. Data migration can be a complex process as testing must be done to ensure data quality. Migration also can be very costly if best practices are not followed and hidden costs are not identified in the early stage. On the other hand, many organizations today instead of buying IT equipment (hardware and/or software) and managing it themselves, they prefer to buy services from IT service providers. The number of service providers is increasing dramatically and the cloud is becoming the preferred tool for more cloud storage services. However, as more information and personal data are transferred to the cloud, to social media sites, DropBox, Baidu WangPan, etc., data security and privacy issues are questioned. So, academia and industry circles strive to find an effective way to secure data migration in the cloud. Various resolving methods and encryption techniques have been implemented. In this work, we will try to cover many important points in data migration as Strategy, Challenges, Need, methodology, Categories, Risks, and Uses with Cloud computing. Finally, we discuss data migration security and privacy challenge and how to solve this problem by making improvements in it’s using with Cloud through suggested proposed model that enhances data security and privacy by gathering Advanced Encryption Standard-256 (ATS256), Data Dispersion Algorithms and Secure Hash Algorithm-512. This model achieves verifiable security ratings and fast execution times.