The Important Role of AI in Data Science

Based on your experience… Could you briefly tell us about your professional background and what your current job entails?

«Thank you very much for the opportunity to discuss these fascinating topics and to share my experience and expectations. I have gradually gained experience in the the world of transforming data into insights For strategic decision-making, I currently have More than 17 years working with data, I currently work as Regional Data Scientist for one of the leading telecommunications companies in Latin America, Milicom.«

In recent years, we have seen exponential growth in the amount of data generated worldwide. What do you think are the main challenges companies face when trying to manage and capitalize on this enormous volume of data?

«In 2017, the BBC published an article whose title asked whether… Is data the new oil? With the statement “think again,” the author draws an interesting comparison in the text, saying: “Data is more like sunlight—it is abundant and Our main concern should be what we do with them, rather than how to get more of them”. That is the main area of focus where companies should direct their efforts. How can I make the most of my data in a holistic way? Historically, the BI (Business Intelligence) It was a postmortem analysis; today, with the shift to the BA (Business Analytics) The analysis focuses on the best-case scenario, but little is said about the Data monetization: Can I make my data architecture self-sustaining?«

Speaking of Big Data, it was recently reported in the news that a leading health technology company used Big Data analytics to identify patterns of emerging diseases… Can you share an example of how big data analysis has had a significant impact on a specific sector, and what are the key lessons we can learn from it?

«The first thing we need to clarify—for those who aren't familiar with the term "Big Data"—is precisely what we call Big Data, we're not talking strictly about large volumes of data—this is just one "V" among the many "Vs" of Big Data—we're talking about variability, speed, accuracy, value, among others.

The use of big data analytics provides a unique competitive advantage, for example, in the financial system Specifically in the banking sector, this is extremely interesting because it allows banks to better understand their customers and offer better services and/or products that are truly of interest to the customer based on their preferences and most recent behavior. Banks no longer wait for customers to come to their branches; instead, banks now approach customers with a reasonable degree of certainty to offer their services or products, such as with the pre-approval of credit cards or loans, where the creation of machine learning models to establish a credit score and determine income reduces the risk of default and increases approval rates.«

One of the buzzwords in the field of business analytics is «Artificial Intelligence.». How do you view the relationship between Artificial Intelligence and Data Science in business decision-making? What role will AI play in the future of Business Analytics?

«The artificial intelligence, understood as the broad set of tools and techniques that are driving Industry 4.0 is essential for making data science more efficient, since data science draws on the various options offered by AI, primarily in the Machine Learning or Automated Learning (Machine Learning, an artificial intelligence application with algorithms that analyze data, learn from that data, and ultimately apply what they have learned to make informed decisions) and the Deep Learning (considered an evolution of machine learning. A subfield of machine learning that organizes algorithms into layers to create an “artificial neural network” capable of learning and making intelligent decisions on its own).

In past decades, business intelligence was the competitive advantage; today, The benefit is the proper implementation of Business Analytics, and AI plays an important role here, because whoever understands and makes the best use of resources will gain the upper hand much more quickly.«

In recent years, data ethics and consumer privacy have become hot topics. What are the most important ethical considerations that data science and business analytics professionals should keep in mind in their daily work?

«Privacy and anonymity, Data scientists and business analytics professionals have access to a vast amount of data, much of which is sensitive and personal. Much of this information must be uploaded to the cloud and is therefore exposed; it is best to encrypt the data and upload only what is truly necessary.

Currently, already There are government regulations that set the minimum requirements for addressing these issues; unfortunately, this is not yet the case in Latin America.«

With the growing demand for professionals in data science and analytics, many people are pursuing careers in this field. What advice would you give to someone who is just starting out in this field and wants to succeed in their career?

«Let them seek a formal academic education; let them not worry about learning all the programming languages and all existing textbooks—since these continue to grow and change every day—that they focus on mastering the concepts and understanding the various solutions available to address a problem, that they identify the industry they are passionate about or interested in, and undertake personal, practical, and common projects in that industry to gain experience and knowledge.«

In a world of constant change and technological evolution. What do you think will be the most important trends in the fields of data science, big data, and business analytics over the next five years? How should companies prepare to embrace these trends?

«First, must prepare to migrate to the cloud, As soon as possible, the computing power and scalability offered by the cloud are benefits that provide a competitive advantage in fast analysis at reasonable operating costs, But there must be a clear strategy for that migration.

Second, data monetization, »Data doesn't just provide information; companies now have a new source of revenue at their disposal."

We'd like to know…What was your experience like after receiving an OAS-Structuralia scholarship? And… What benefits did receiving this scholarship bring you?

» 1. My professional career was significantly enriched by having taken and completed the Master's Degree in Big Data and Business Analytics, hold a master's degree It has helped me gain access to some great job and academic opportunities.

2. Participating in the scholarship application process was a very enriching experience, I was able to assess myself and rethink the future of my professional career. Once I received the scholarship, I felt much more at ease because It was a significant source of financial support that allowed me to study without the financial worries that come with it.«

And finally… Why would you recommend applying for OAS scholarships and studying at Structuralia?

«In my experience, it is extremely valuable to have an academic degree that validates the knowledge, skills, and interests we possess as individuals and professionals; to earn a degree that is Backed by an academic institution with a long and distinguished history, with faculty members who have incredible academic and professional experience, plus the support of an international organization like the OAS, it adds value to anyone’s resume, he adds., », this empowers us to keep improving."

From Structuralia, we would like to thank our former student from the Master's Degree in Big Data and Business Analytics, Walter Rivas Orellana. He has shared with us his professional expertise and valuable insights into artificial intelligence and its crucial role in big data and business analytics.  We encourage you to comment on this interview!