Modernizing On-Premise Infrastructure: Cloud Migration and Future Innovations

About our Client

A Peruvian basket fund management company with over 30 years of experience in the market. They have an IT team (there is no top management in IT) with around eight people (Chief Systems Engineer, four developers, and four people in technical support).

The Challenge

The main challenge in tackling the issue is that the IT department needs cloud services specialists or knowledgeable staff to develop cutting-edge software or even the industry's recent trends.

01.
The Client
A Peruvian basket fund management company with over 30 years of experience in the market. They have an IT team (there is no top management in IT) with around eight people (Chief Systems Engineer, four developers, and four people in technical support).
02.
The Challenge
The main challenge in tackling the issue is that the IT department needs cloud services specialists or knowledgeable staff to develop cutting-edge software or even the industry's recent trends.
03.
The Solution
The solution was initially divided into 3 phases: The first phase was to migrate databases and main applications to the cloud (completed). The second phase (ongoing) consists of providing initial migration support and developing a new basket funds system that supports new technologies and good industry practices. The following steps (in the future) will consist of migrating other applications and the implementation/use of a data lake to better use the company’s data through data scientists and analysts, and even machine learning or AI.

The Solution

The solution was initially divided into 3 phases: The first phase was to migrate databases and main applications to the cloud (completed). The second phase (ongoing) consists of providing initial migration support and developing a new basket funds system that supports new technologies and good industry practices. The following steps (in the future) will consist of migrating other applications and the implementation/use of a data lake to better use the company’s data through data scientists and analysts, and even machine learning or AI.
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