![]() ![]() In many cases, it also entails a storage migration. Cloud migration. The process of moving data, application, or other business elements from either an on-premises data center to a cloud or from one cloud to another.Offers significantly faster performance and more cost-effective scaling while enabling expected data management features such as cloning, snapshots, and backup and disaster recovery. Storage migration. The process of moving data off existing arrays into more modern ones that enable other systems to access it.However, the type of migration undertaken will determine how much IT staff time can be freed to work on other projects.įirst, let’s define the types of migration: Companies using cloud are hoping that they can focus their staff on business priorities, fuel top-line growth, increase agility, reduce capital expenses, and pay for only what they need on demand. For many firms, this is a very natural evolution. There are numerous business advantages to upgrading systems or extending a data center into the cloud. To ensure that the project gets the attention it needs, focus on the most provocative element of the migration – the fact that the legacy system will be turned off – and you’ll have the attention of key stakeholders, guaranteed. ![]() Given this complexity, consider promoting data migration to "strategic weapon" status so that it gets the right level of awareness and resources. And, although the workaround may have been necessary at the time, this technical debt must eventually be addressed during data migration or integration projects. This forces application administrators to sidestep ideal and simple workflows, resulting in suboptimal designs. Therefore, application design, data architecture, and business processes must all respond to each other, but often one of these groups is unable or unwilling to change. Business processes use data in isolation and then output their own formats, leaving integration for the next process. ![]() ![]() The main issue is that every application complicates data management by introducing elements of application logic into the data management tier, and each one is indifferent to the next data use case. By making time at the beginning of the project to sort out data and application complexities, firms can improve their data management, enable application mobility, and improve data governance. To move applications and data to more advantageous environments, Gartner recommends "disentangling" data and applications as a means overcoming data gravity.
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