The Repository @ St. Cloud State

Open Access Knowledge and Scholarship

Date of Award


Culminating Project Type

Starred Paper

Degree Name

Engineering: M.E.M


Mechanical and Manufacturing Engineering


College of Science and Engineering

First Advisor

Hiral Shah

Second Advisor

Ben Baliga

Third Advisor

Balasubramanian Kasi

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

Legacy Systems, Modern Database, UAT, SDLC, Agile methodology


Many businesses which use mainframe systems are unreliable these days and are facing the problem of data inconsistency and inaccuracy. Moreover the costs incurred in maintaining these systems keeps on increasing. As the competitors are migrating over to the new technologies and tools available in the market, it is necessary for these businesses to migrate to new environment which is efficient, consistent and reliable to stay in the market and the technologies used in the current environment have become obsolete or no longer serve the business purpose. This report summarizes the various methodologies, procedures and techniques involved in successfully migrating the data to modern systems. The practical work carried out for the capstone project is the development/building of application for data migration that is tailor-made for the client and their specific needs. In the process of data migration, we profile the existing data which helps in determining the structure and completeness of the data, in turn results in improved data quality. This report also contains data analysis that are carried on basis of profiled data and transforming the data accordingly to meet the new business needs. Agile software development life cycle is followed in the application building process as it uses iterative and incremental approach, bridging the gap between business owners and application developers as the end users are involved in each iterative phase. This report concludes with results that are obtained from successful data migration from the perspective of business needs and recommendations that could be implemented in the process of scaling of application



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