Design of multi-intelligent data migration strategy based on SDN secondary mode

2018 ◽  
Author(s):  
Haiyang Zou ◽  
Mingdong Li ◽  
Zhenhua Li ◽  
Jianqing Gao
Keyword(s):  
Data Migration ◽  
Migration Strategy ◽  
Secondary Mode

Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems

2019 ◽  
pp. 137-145
Author(s):  
Zhenjing Cheng ◽  
Yaodong Cheng ◽  
Lu Wang ◽  
Qingbao Hu ◽  
Haibo Li ◽  
...  
Keyword(s):  
Storage Systems ◽  
High Energy ◽  
Data Migration ◽  
Migration Strategy

scholarly journals Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems

2020 ◽  
Vol 1525 ◽  
pp. 012042
Author(s):  
Zhenjing Cheng ◽  
Lu Wang ◽  
Yaodong Cheng ◽  
Gang Chen
Keyword(s):  
Storage Systems ◽  
High Energy ◽  
Data Migration ◽  
Migration Strategy

scholarly journals Multi-tenant Data Migration Strategy in SaaS Platform

2014 ◽  
Vol 7 (12) ◽  
pp. 2421-2426
Author(s):  
Yongqing Zheng ◽  
Xiaojun Ren ◽  
Lanju Kong
Keyword(s):  
Data Migration ◽  
Migration Strategy

scholarly journals Implementation Planning

2003 ◽  
pp. 461-480
Author(s):  
Len Asprey ◽  
Michael Middleton
Keyword(s):  
Action Plan ◽  
Data Migration ◽  
Acceptance Testing ◽  
Migration Strategy ◽  
Execution Plan ◽  
Communication Plan ◽  
Test Specifications ◽  
Covering System ◽  
Implementation Planning ◽  
System Acceptance

In this chapter, we provide guidelines for implementation planning, along with techniques that can be used during the implementation process to facilitate a successful project outcome. This includes satisfying the operational, technical, and financial objectives of the IDCM initiative, and providing guidelines for postimplementation review. Our objectives in this chapter are as follows: • Discuss the development of an Implementation Strategy. • Discuss the requirements for a Project Execution Plan. • Review the requirements for a Quality Plan to support the processes involved in development and implementation of an IDCM solution. • Consider an initial set of risks that can be useful to capture at the commencement of an IDCM implementation, and discuss the requirements for an Issue Register and Risk Register. • Review the requirement for the development of an effective Change Management Strategy and action plan. • Consider the contents of an effective Communication Plan for an enterprise IDCM implementation. • Discuss the typical requirements for a Data Migration Strategy to migrate existing (relevant) document registers and objects to the IDCM. • Consider scenarios for backfile conversion of (relevant) hard-copy documents and the development of a Backfile Conversion Strategy. • Consider the typical requirements for training and development of a Training Plan. • Define a strategy for testing the configured IDCM, covering System Integration Testing and System Acceptance Testing strategies, and the development of Test Specifications and Test Plan(s). • Review the importance of the Postimplementation Review study in the evolutionary deployment of an IDCM solution.

scholarly journals Without Data Quality, There Is No Data Migration

2021 ◽  
Vol 5 (2) ◽  
pp. 24
Author(s):  
Otmane Azeroual ◽  
Meena Jha
Keyword(s):  
Data Quality ◽  
Data Storage ◽  
Business Processes ◽  
Data Migration ◽  
Quality Data ◽  
Migration Strategy ◽  
Data Intensive ◽  
Migration Strategies ◽  
The One ◽  
The Cost

Data migration is required to run data-intensive applications. Legacy data storage systems are not capable of accommodating the changing nature of data. In many companies, data migration projects fail because their importance and complexity are not taken seriously enough. Data migration strategies include storage migration, database migration, application migration, and business process migration. Regardless of which migration strategy a company chooses, there should always be a stronger focus on data cleansing. On the one hand, complete, correct, and clean data not only reduce the cost, complexity, and risk of the changeover, it also means a good basis for quick and strategic company decisions and is therefore an essential basis for today’s dynamic business processes. Data quality is an important issue for companies looking for data migration these days and should not be overlooked. In order to determine the relationship between data quality and data migration, an empirical study with 25 large German and Swiss companies was carried out to find out the importance of data quality in companies for data migration. In this paper, we present our findings regarding how data quality plays an important role in a data migration plans and must not be ignored. Without acceptable data quality, data migration is impossible.

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