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IT is at the Heart of the Work of a Data Architect

Data has been an integral part of Saska Saarioja's life for at least the last seven years, and programming since his teenage years. Saska, who has a background in demography, previously worked with population statistics and forecasts, but these have since shifted to data processing, transfer, modification, and analysis tools. Now, as a data architect at Cloud1, Saska has the opportunity to focus purely on cloud technology and the latest Azure services.

Room to Experiment in Cloud

Interest in cloud technology took over when I got to work with Azure in practical projects. The efficiency of the cloud environment opened my eyes, and there was no going back to the old ways. 

"After working with Azure and the cloud, I realized that this is an area that requires more focus."

The efficiency of the cloud is evident not only in the more effective use of resources but also in direct cost savings. For example, computing capacity can be utilized as needed, just as much as necessary. Fixed infrastructure costs are replaced with targeted resource deployment, making operations easier.

"I see it this way, that except for certain critical functions, everything else will move to the cloud. Overall, it's just so much more efficient," Saska states.

In addition to making development and operations easier, the cloud environment also offers a key advantage: the experimentation with things is much faster and easier. Saska advocates for a "fail fast" mentality in developing new products and services: it's better to quickly realize the ineffectiveness of a solution through experimentation, before investing huge amounts of time and money. Thanks to the cloud, agile experimentation is risk-free.

Automatic Data Processing must be Automatic

Saska is particularly interested in how different environments can be automated. The basic principle is: everything that can be automated, must be automated.

"Everything that can be automated, should be automized"

Automation leads to speed in development and deployment, as well as the sensible management of costs. Most standardizable operations can be automated with little effort. Examples include the deployment of new services, setting up servers, or duplicating a development environment into production and testing environments. For instance, if there's a need to expand operations to a different geographical area, automation can significantly ease scaling.

As a practical example, Saska mentions, for instance, if a company wants to expand its computing capacity from European data centers to those in North America. In such a case, the same setup that was implemented once could be automated to work in another location with minimal effort.

Thus, for the customer, automation can bring significant cost savings and the opportunity to scale operations agilely. The concept of automatic data processing remains highly relevant.

Cloud1 Enables Focus on Azure Expertise

Cloud1 was not a company familiar to Saska beforehand. However, conversations with the founding members of Cloud1 convinced him that it was the right fit for him. Expectations have been met, and Saska has been able to focus on the things he has wanted to. Going forward, he wants to delve deeper into Azure and its constantly evolving new services.

At Cloud1, it's easy to get involved in new projects, as the work is guided by a structured approach and standardized working methods. This is evident in both small details and larger strategies. Uniform naming standards, best practices for component selection, data processing, or storage lay a good foundation for work.

"Without the conceptualized structure of the Cloud1 Data Hub model, implementations would to some extent always bear the imprint of their creators – and not always in a good way," Saska points out.