Our goal is to ensure profitability in your data engineering projects, to achieve this we follow the following steps:

1. Define the project roadmap, identifying access and technical, business, data restrictions, among others; in addition to the expected economic impact of the project (profitability)

2. Establish project schedule with tracking milestones

3. Implement the project with continuous monitoring of milestones

4. Delivery of the final project aligned to the needs of the company

5. Team training as required

6. Continuous support for the final solution

Some types of projects that we have managed throughout more than 6 countries are the design, implementation and deployment of:

- Data Lake

- Machine learning models

- Machine Learning Operations Architectures (MLOps)

- Data warehouses

Within our team we have:

- Data engineers with more than 5 years of experience

- Data scientists with more than 7 years of experience

- Systems engineers with more than 6 years of experience

- Software quality assurance team

We have experience in such companies like:

- Bank of the Republic of Colombia

- Mondelēz International (Ecuador)

- One of the largest retailers in Panama (handling more than 70.000 GB of data)