A Foolproof Process to Move and Improve Cloud Data


To take full advantage of the cloud’s efficiency and agility, organizations cannot simply “migrate” their existing applications from an on-premise environment to a cloud environment. Such approach will slow down their innovation capacity and performance significantly due to inefficient consumption of resources and simply unsuitable code. But it is not for all that a question of wiping out what already exists and rebuilding everything would be extremely costly in terms of time and money.

One of the most frequently asked questions is, “How can I relocate data to the cloud and improve databases and applications, security, governance, and data loops?” Everyone is looking for shortcuts or magic tools to migrate data and automatically improve data health. Unfortunately, there is no such magic. On the one hand, the migration process, not magical, provides the highest possible number of successes. Before we discuss the process, I have something to tell you in advance.

First, we don’t use the cascading methodology to relocate data to the cloud. Some tasks need to be completed before moving on to the next, but not all. Of course, there are dependencies, but you can do whatever you want in any of the following series of tasks.

Second, to get it right the first time, you need to have the right people and follow the process. You need experts in databases, security, operations, governance, and cloud services, but such a person is hard to find right now. Finally, here is a generalized approach. So some need to be added or removed based on the actual environment. For example, in a medical institution, you need to be more concerned with governance and compliance issues when using, migrating, and distributing data.

With these three things in mind, follow the process below.

  1. Evaluate the current state of the data. Evaluates from model (object, relational, in-memory, special use, etc.) to metadata, application connectivity, and requirements (security, governance, BC / DR, management).
  1. Find areas that can reduce redundancy and increase efficiency. This process can greatly impact migration from one model to another (from a relational database to an object database). This is because it requires refactoring the application, generalizing all data structures, and defining a single trusted source. Security, governance, and data loops also need to be considered and, to be clear, apply redundantly to all processes.
  1. Define the target data state by applying the changes and requirements defined in the previous process. The method I recommend is to develop a Common Metadata Model (CDM). CDM essentially provides a single, trusted source for most data, sometimes all data that exists within the company. CDM is made up of many databases with different database structures and models but appears to the user as a single, unified database, and when a query is requested, it provides consistent responses.
  1. Define a migration and deployment plan with a focus on the target cloud platform. ‘The devil is in the details’ and some will still change on the fly, but it will be trivial.
  1. Create test and staging platforms for applications and databases. This can include a CI / CD link. Additionally, this environment must be managed by the DBA and the DevSec operations team. You have to plan this maintenance.
  1. Perform batch tests on the test and staging platform to determine performance, security, governance, and purpose. Repeat for each application and database.
  1. The tests provide the data you need to determine operating costs and plan costs for the next few years. Now that you have a true cost indicator, this makes this easy. The cost plan saves you from receiving shocking bills.
  1. Define the operational plan. Monitoring and management approach, guidelines, and tools should be included. The benefits of abstraction and automation should be used to minimize operational process labor.
  1. Start a step-by-step deployment, starting with the smallest and least important applications and databases, then moving on to the largest and most important. Take the flexible deadline. There is no need to worry. You will learn and improve as you go through the process. There are many cases where this process fails quickly. This is because there are cases where important tasks are skipped to meet the deadline.
  1. Perform acceptance checks at each step.
  1. Start data operations.
  1. Go on vacation.

On average, this process takes about 3 weeks per database. If you have 100 databases that need to be migrated, it will take between 42 and 52 weeks. This process of transferring and improving data is neither magical nor automatic. However, it can melt into the migration process.

What are the main benefits of cloud migration?

Scalability: Cloud computing can scale to larger workloads and more users much more easily than on-premises infrastructure, which requires businesses to purchase and install physical servers, network equipment, or additional software licenses.

Cost: Companies moving to the cloud often reduce their IT expenses significantly, as cloud providers take care of maintenance and updates. Rather than keeping things running, companies can focus more resources on their core business needs – developing new products or improving existing products.

Performance: For some companies, moving to the cloud may allow them to improve the performance and overall user experience of their customers. Suppose their application or website is hosted in cloud data centers rather than various on-premises servers. In that case, data won’t have to travel such a long distance to reach users, reducing latency.

Flexibility: Users, whether employees or customers, can access the cloud services and data they need, wherever they are. This makes it easier for a company to expand into new territories, offer its services to an international audience, and let its employees work flexibly.

Final word

The effort to move and improve cloud data is a slow and steady process. You can choose to rely on your current storage and cloud development if you are a startup. But suppose you’re an established organization with a complex IT environment and a range of in-house applications on cloud platforms and services. In that case, it can be difficult to homogenize everything into a single architecture. Slowly follow the tips explained above on how to move and improve cloud data to be better and increase productivity.

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