Brenda Surra

Agile frameworks have revolutionized the way teams approach their work. These methodologies allow teams to adapt to rapid changes, collaborate effectively, and deliver value continuously. Among the most popular frameworks are Kanban, Scrum, and Extreme Programming (XP). Although they all share the agile philosophy, each has unique characteristics that make it ideal for different contexts […]

A significant part of a project’s success depends on its ability to be deployed efficiently in production. The process known as deployment is not just a final phase of development but an ongoing practice that ensures applications reach users quickly, securely, and reliably. In this article, we’ll explore what deployment is, the essential elements for

The rise of AI and machine learning has brought an increasing dependence on data. However, not all data is useful in its raw form. This is where the ETL process in machine learning comes into play a key methodology that transforms raw and unstructured data into information ready for analysis and predictive model development. In

In the field of machine learning, choosing the right framework can significantly influence the success of a project. Two of the most popular frameworks are TensorFlow and PyTorch, each with its own features, advantages, and disadvantages. This article delves deeply into their benefits and drawbacks, as well as the use cases where each framework excels,

In modern web development, speed, efficiency, and scalability are essential for the success of any application. In this context, Node.js and Express.js have emerged as key tools for building back-end applications, allowing developers to create fast, flexible, and robust solutions. In this article, we’ll explain what Node.js and Express.js are, their advantages and disadvantages, and

The roles of architect, tech lead, and CTO (Chief Technology Officer) are fundamental for ensuring the direction, planning, and execution of technological projects. While they share the common goal of optimizing processes and outcomes, their responsibilities and approaches differ. In this article, we will explain in detail the differences between these roles, defining each one

AI in the financial sector is transforming how banking and financial institutions operate, make decisions, and protect their customers. From predictive analytics to anticipate market trends to fraud prevention, artificial intelligence has become a fundamental pillar for innovation and improving efficiency in the industry. In this article, we explore the role of AI in the

Asset tokenization is emerging as one of the most disruptive applications of blockchain technology. This process is changing the way people and companies manage, exchange, and own assets, from real estate to artwork or commodities. In this article, we explain what asset tokenization is, how it works, its advantages and disadvantages, as well as its

Organizations often seek tools and frameworks that enable them to build robust, scalable, and efficient applications. In this context, Spring Boot stands out as one of the most popular options, offering an agile and simplified approach to development with Java and Spring. Here, we explore this technology, its definition, advantages, disadvantages, and applications. What is

The success of projects doesn’t rely solely on tools or algorithms but also on a structured and well-defined process that guides each stage of development. This is where the CRISP-DM methodology (Cross-Industry Standard Process for Data Mining) comes into play. This methodology provides a clear and systematic framework that enables data science teams to successfully