It’s tempting to just replicate all the databases in the cloud, but it’s a much better approach to getting your data home in order as part of the move.
Last week, I discussed database standardization as a best practice in multicloud architecture. Let’s also look at this concept as part of the migration to the cloud.
Don’t confuse database standardization with data standardization. Data standardization is about reducing redundancy and defining a more optimized structure. Maybe you, the database administrators, are aware of this process. I taught it at the university more than 30 years ago.
Database standardization is the process of reducing the redundancy of the databases themselves to create a set of databases that are more focused on the needs of business applications, data scientists and those conducting data analytics.
The challenge is that databases and data to migrate to the cloud are too complex and full of redundancy (some unique sources of truth). Plus, most people moving that data to the cloud just want to replicate the databases to the public cloud destination – a huge mistake, and here’s why.
I understand that most budgets are limited and that the cost of moving and combining data to native and non-cloud cloud databases is much higher than simply transferring bad database architectures to the cloud. However, I also understand that you’d better understand this when you switch to the cloud, rather than having to fix it later.
If you don’t, you’ll have to migrate the data twice: first lift and move to a public cloud or clouds, then go back and fix things once you understand that the database architecture in the cloud is not optimized (because it’s too complex, or redundant or too expensive).
What should people in charge of migration to the cloud do? Here’s the perfect process:
- Get stakeholder support. This is primarily because you will spend at least twice as much on migration and standardization, including changing applications to process the new database stack. If executives are not willing to invest money, explain the risks and future costs. (Try sending an email. You can remove it from your mail folder sent to prove that you tried to warn against the folly of doing nothing.)
- Make sure you have the necessary human resources. You’ll need people who understand the stack of databases in place, native cloud database options, database design and data migration processes. Include data security and governance, as well as data operations.
Spend enough time on planning. Much of this work is about migration planning, including how databases will change and new or existing ones to use. The devil is in the details. If you are missing a middleware or data compliance system, it will need to be redone.
It’s really not as difficult as it sounds. We have gone from platform to platform and have simultaneously changed databases in the past. What is new is that we are now looking at the data in a more strategic way. This should be basic analytic data, as well as training data for AI systems. Data is really everything for the company now. Treat it like one.