About Me

Greetings, I'm Ivanubia, commonly known as Iva, a seasoned professional with over a decade of experience in software development, data engineering, and solutions architecture. My journey has equipped me with extensive knowledge in full-stack software development, database design, and data analysis, showcasing proficiency in a variety of programming languages and databases.

From an early age, my enthusiasm for technology, problem-solving, and self-directed learning has been a driving force shaping my academic and professional path. Starting with my first computer at the age of eight, my initial fascination with technology has evolved into a comprehensive understanding of web development and various programming languages. I initially studied mathematics at the Federal University of Goias in Brazil immediately after high school, but my enduring dream of pursuing higher education in the United States  has remained steadfast.

Beyond programming, my expertise spans across cloud computing, distributed systems, system architecture and design, leadership, DevOps, and the complete software development life cycle. I take pride in seamlessly navigating the complexities of technology.

With a keen eye for detail, I specialize in identifying design patterns within the applications I work on, showcasing a commitment to precision and dedication to creating robust and efficient solutions.

Emphasizing teamwork and leadership, I actively contribute to team success through mentorship and coaching. My commitment to continuous learning has led me to explore areas such as big data, machine learning, artificial intelligence, and solution engineering.

CL/CD Pipeline: Continuous Learning / Continuous Development

Looking ahead, I'm eager to pursue a Master in Business Administration degree to deepen my understanding of business aspects and further bridge the gap between technology and strategic business goals. With a motto of "Think Big and Chase your Dreams," I approach my professional journey with ambition and dedication, aiming to elevate both my skills and the organizations I work for to new heights.

Beyond the tech world, I'm also an avid traveler with a passion for exploring new places. I've had the opportunity to visit various countries, including England, Scotland, the Netherlands, Italy, and Germany. My love for travel not only broadens my horizons but also enriches my perspective, contributing to a well-rounded approach in both personal and professional aspects.






Top Posts

Popular Methods for Machine Learning

Image
Machine Learning involves the programmatic training of applications to predict outcomes. Numerous algorithms and techniques are available for addressing prediction challenges in machine learning. In this discussion, we will explore three popular methods: Logistic Regression, Decision Tree, Random Forests, and Neural Networks. Logistic Regression Logistic Regression, a supervised machine learning algorithm, employs a binary classification approach, yielding a result based on two possible values while outputting only one, such as a Boolean (true or false). Despite its historical roots dating back to the 19th century, this method remains popular in machine learning. The resulting function displays an "S"-shaped graph, utilizing the logit function to constrain probabilities between 0 and 1. For instance, consider the scenario where we are trying to predict the likelihood of a person being approved for a mortgage based on their credit score and income. In the provided colored data...
Read more

Big Data Characteristics Explained

Image
Big Data is a hot topic in business, and it's not just a buzzword – it's a part of our daily lives everywhere. It goes beyond just having heaps of data; it includes how the data is structured, how fast we can process it, and, most importantly, what we can achieve with it. Two major factors driving the surge in data are improved computer capacity and increased data generation. Nowadays, our hard drives are not only bigger but also faster, allowing us to handle more data at lightning speed. This has led to a significant rise in data from various sources over the past decade. The value of Big Data for businesses today is immense, as it allows for improvements in various departments by recognizing common patterns, analyzing data, and delving into artificial intelligence and machine learning. Big data has four key characteristics, known as the 4 Vs: Volume: Receiving large amounts of data from various sources, often posing challenges when processed on personal compu...
Read more

Planning a Data Warehouse

Image
Setting up a data warehouse is a strategic move for businesses aiming to leverage historical data for informed decision-making. In this blog post, we'll dive into the essential planning phase, emphasizing the need for efficient data extraction, transformation, and loading processes to ensure optimal functionality. Let's explore the key steps to plan a data warehouse successfully. 1. Defining and Documenting Requirements for Data Warehouse During the planning phase, it's imperative to define and document requirements meticulously. This not only sets clear expectations for stakeholders but also facilitates seamless onboarding for new team members. The documentation should encompass various aspects, with a focus on the sources of data.  Key details include: Historical Data : Identify the duration of available historical data, spanning from months to years, providing valuable insights into the business's evolution. Data Sources : Specify diverse sources, such as websites, m...
Read more