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This article mainly explains the "five main points of big data Cloud transfer". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought and go deep into it slowly. Let's study and learn the "five main points of big data Cloud transfer".

Point 1: need to know your own data

Before you start the migration project, make sure that the enterprise really understands the data source. Create a system process to identify the data source as a migration candidate. Then, for each source, ask yourself:

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

What is the priority of migration from 1 to 10?

With priorities from 1 to 10, how much work will be involved in the migration?

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

Point 2: cannot be promoted or transferred

To put it bluntly, the promotion and migration approach represents the ultimate violent cloud migration, in which applications and related data are "promoted" and "transferred" from the internal deployment 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 doesn't mean it makes sense in a distributed computing environment.

Point 3: look for ways to save costs

Moving big data to the cloud offers many advantages: it is a productivity turbocharger; it is a deep source of business insight; and it is an entirely new way to understand customers and trends, close contact, and personalize data. However, this is not a way to save money. Companies can and should control migration and operating expenses, but don't expect to gain the huge advantage of big data based on cloud computing at a lower price.

Point 4: need to invest in an internal team

Because IT resources are limited and the team is already busy, most small and medium-sized businesses lack the internal bandwidth and expertise needed to manage cloud migration. Of course, outsourcing is a solution, but internal training is seen as an investment. Distributed computing requires a specific skill set, and an enterprise's cloud computing investment should be not only in services, but also in its employees.

Point 5: don't treat data as a responsibility

With the great effort and complexity of effectively moving to the cloud, IT stakeholders, employees, and managers can all begin to see the organization big data as more responsible than Wealth. Don't let that happen. Don't just store what the business needs and throw away the rest, there is hidden value. When an enterprise migrates, something as important as data needs to be better preserved.

Thank you for your reading. The above is the content of "the five key points of big data Cloud Migration". After the study of this article, I believe you have a deeper understanding of the five key points of big data Cloud Migration. The specific use of the situation also needs to be verified by practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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