Cloud Data Modernization: Where to Start?

[shukla7789]

Learn how to approach a cloud data modernization project to achieve a 360-degree view of the business with relevant and quality information.
When we've been working with data for a while, taking a new step feels like stepping out of our comfort zone again. But what if we know that there are good reasons to take that push to modernize in the cloud and go in search of that long-awaited growth?

Companies have been digitalizing at a rapid pace in recent years and have learned what it feels like to be “full-life migrants.” This is a behavior of maximum flexibility in which change is prioritized as a strategy to not stop the evolution of the business.

However, in order to move towards modernized car owner database data management, each step of this migration process must be well standardized in order to properly align the team's efforts.





84% of companies have already started their journey towards data modernization, and 34% have already completed it.

Source: Delloite



Steps to a successful data modernization
As companies implement new applications and new products, cloud integration is absolutely necessary to stay connected. Over the years, this allows for the implementation of a wide range of tools to grow. However, in this process, it is necessary to analyze the structure and understand what things are useful and what we need to optimize or change. That is why, to carry out this passage thoroughly, we recommend a series of steps:



Evaluate: For any cloud modernization initiative, we need to do nothing less than evaluate in order to understand the baseline state, the starting point where the company is. See the status of the data mapping repositories, going to the mapping metadata records, assets, sessions, workflows, connection logs, property configuration and other well-detailed details. The objective is to consider everything in order to have an idea of ​​what you want to migrate or modernize.
Clean: It is quite normal that over time there are mappings that become unused, that are no longer a priority or are not needed at all. Therefore, it is key to identify and clean everything that is no longer needed. This will save time and space, as well as clear the area to better understand where this migration is starting from.
Convert/migrate: There are tools that intelligently and automatically convert data mappings. This is part of what is called Migration Factory , which automatically converts most of the repository mappings. It is logical that there is a small portion of data that must be migrated manually, but we are talking about approximately 10%. For this reason, evaluating a tool with these characteristics is highly recommended.