Bringing Higher Efficacy, Agility and Predictability for Data Migration Success

Data & Analytics

August 6, 2015

As the competition is getting stiffer day by day, businesses and brands are striving hard to differentiate themselves from the competition. “Customer centricity” has become a way of life while delivering services/products to end users. Digitization has made it easy and possible for businesses to create ever lasting impression in customers’ minds.

While it may sound facile on high-level, a lot has to be done from the back-end. Enterprises need to realign/enhance their systems, processes, applications to meet strategic and operational goals. This phase of “realignment”necessitates replacing legacy systems/applications with new ones, consolidating few applications into a single application etc. In the process, “Data” has to be migrated from source to target system, which is often over-simplified and under-budgeted, thus resulting in failure of projects in meeting the requirements. In one of the Oracle’s whitepapers, it has been mentioned that 75% of the data migration projects fail due to flaws in the migration process.

It would require clear understanding of source data, proper planning, and proven processes to perform successful migration. Following are the key reasons for the failure of data migration projects.

Lack of awareness on importance of Data migration: Many a time data migration is seen as a regular, mundane administrative task and is deprived of proper planning & budget allocations. Little is understood about importance of having clean and reliable data in achieving the corporate goals.

Less involvement of Business users: Data is created and used by business users. But getting the involvement of these users during migration is a really tough job organizations facing. As IT people, who are performing, are not experts in interpreting the data, chances are high that any anomalies are left unnoticed, and unattended in the earlier stages.

Improper planning and over-budgeting: Quite often migration projects exceed timelines and budget due to no clear planning during the initial stage. Same has been echoed in one of the Gartner’s report on ill-preparedness of enterprises for high risk migration projects, which results in cost overruns and schedule delays

Poor data quality in legacy systems: Poor data management practices lead to poor data cleaning, data governance and storage issues and probability of the same is high in legacy systems. Identifying and fixing these issues during migration is critical

Data governance and compliance issues: Lack of good data governance practices makes it tough for organizations on overall management of availability, usability and security of data. This also leads to compliance and regulatory issues.

Hexaware’s Data Modernization helps organizations to transition data smoothly from heterogeneous, legacy systems/platforms to high-performance modern platforms with its data management best practices, innovative tools, and state of the art technology.

Data Modernization