5 Key Points of Big Data Cloud Migration

Cloud computing is here. However, data migration in the cloud is becoming annoying. According to McAfee's survey, 97% of organizations use public or private cloud services. Big data is also beginning to surpass the local deployment/cloud computing gap. IDG found that 41% of companies have migrated storage, archiving, backup, and file servers to the cloud, and 21% of companies plan to migrate storage, archiving, backup, and file servers within the next year.



These numbers are good news for cloud computing adoption rates and cloud computing big data providers. Because at that time people will see that 59% of companies have not migrated, or 79% of companies have no migration plans. People want to know that storing big data near applications that generate and use data has many benefits. Why are few companies able to get ahead?



It turns out that the answer is simple: it's really hard.



Why data cloud migration is in trouble



To use existing models and tools to migrate big data to the cloud, very strong technical capabilities are required and a lot of funds are required.


IT stakeholders tend to ignore the fact that physics is still involved, even in the digital world. Current methods try to store large amounts of mobile data of products through digitally equivalent containers, ignoring the fact that the data is not static cargo. It keeps changing. Business will not stop during the migration. Even if companies migrate data to cloud platforms, data will continue to flow into existing local storage. This makes it very complicated to maintain data integrity during migration. Since common solutions are often not satisfactory, many migrations are in trouble.



Avoiding Pitfalls: Five Key Points of Data Cloud Migration



In order to avoid the trap of big data cloud migration, avoid using violent means. Take a more refined and complex approach, and remember the following five key points of big data cloud migration.



Point 1: Need to know your own data



Before starting the migration project, make sure that the company truly understands the data source. Create a system process to identify data sources that are candidates for migration. Then, for each source, ask yourself:



(1) Is this data valid and/or actually used for anything?



(2) How high is the migration priority from 1 to 10?



(3) From a priority of 1 to 10, how much work will the migration involve?



(4) What are the costs and risks of maintaining data during and after the migration?



Point 2: Cannot promote and transfer



To put it bluntly, the promotion and transfer method represents the ultimate violent cloud migration, in which applications and related data are "upgraded" and "transferred" from the on-premises environment to the cloud platform. The problem is that the local environment and the cloud environment are the difference between apples and oranges. Of course, they are all round. Just because the enterprise architecture works well locally does not mean it makes sense in a distributed computing environment.



Point 3: Look for ways to save costs



Migrating big data to the cloud offers many advantages: it is a productivity turbocharger; it is a deep source of unprecedented business insight; it is a new way of understanding customers and trends, close contact and personalizing data. However, this is not a way to save money. Enterprises can and should control migration and operating expenses, but do not expect to obtain the huge advantages of cloud-based big data at a lower price.



Point 4: Need to invest in internal teams



Due to limited IT resources and busy teams, most SMEs lack the internal bandwidth and expertise needed to manage cloud migration. Of course, outsourcing is a solution, but consider internal training as an investment. Distributed computing requires a specific combination of skills. An enterprise's cloud computing investment should not only be in the service, but also in its employees.



Point 5: Don’t treat data as a responsibility



With the tremendous effort and complexity of effectively migrating to the cloud, IT stakeholders, employees, and managers can all begin to regard organizing big data as a more responsibility than wealth. Don't let this happen. Don’t just store what the company needs and throw away the rest, there is hidden value. When companies migrate, they need to better preserve such important things as data.



The bottom line of data cloud migration



As big data moves to the cloud, the most important thing is not to cut it. Lifting and shifting and other powerful migration techniques leave problems with data integrity, and eventually increase migration overhead, sometimes even prohibitive. The new round of migration methods are more gentle, more staged, and user- and cost-friendly. With the right tools, an enterprise's cloud adoption strategy does not take much time.