Javier Contreras Gaillard, Director of Analytics and Data Science, At Home Group Inc.
Javier Contreras Gaillard, Director of Analytics and Data Science, At Home Group Inc.
While data analytics may have been around for thousands of years, it wasn’t until about 30 years ago that business intelligence emerged as a new promise in the corporate world. Technology is changing the way the world does business, with a massive shift in business thinking from analog to digital. Not only was this new brave digital word difficult, it was also deeply misunderstood and intimidating to those with decades of experience whose top game was suddenly shaken and challenged.
Financial institutions are pioneers in solving this problem, understanding that it is now possible to identify not only receipts, transactions and dollars, but also customers, even if they choose not to do so. So the data is out there, being stored in vast quantities and growing every second. Business wisdom is everywhere, like the giant pile of ones and zeros that accumulate in your local bank’s servers. When did it happen? It’s hard to say, but the demand for talent, engineers and experienced people who can understand this invisible world is scarce. This requires a lot of manpower and a lot of processing power because not all technologies are ready for it, and it’s moving very quickly.
I was lucky enough to study programming in college as a chemical engineering student. Managing, adapting and interpreting large amounts of complex and often abstract concepts is in my DNA. Business acumen has been the brains at the heart of the companies I’ve worked for for many years. I am always in close contact with the C-suite, eager to learn more and keep their eyes engrossed on a wealth of insights that not only challenge the status quo but give them a whole new edge against their competitors and not only move the business forward to the next level, and within the next few years first.
But no one could foresee what would happen next. It’s not just the top leadership that’s looking for more; Mid-level managers, analysts, and field personnel also maintain ongoing contact with customers. Everyone wants to be a part of it, understand data, and understand how it can improve, change, and evolve faster than ever before. This revolutionary new era is not just evolving; It’s exploding faster than available talent, and the tools to access the data are struggling to keep up.
This is why the need for more layers and layers triggered a split into at least three different types of approaches for the benefit of the data world. Business intelligence is at the core of IT, and software engineers, programmers, and a variety of data-educated developers are responsible for maintaining the health and harmony of the system. Business analytics is front and center of business needs and is mostly made up of various analysts who know how to pull, modify and transform data in simple ways, while data science is the new hot topic and the shining golden boy in any field . Organizations, putting the other two groups aside, occupy a special place at the table, gifted geniuses answer impossible questions and respond to challenges accurately, and educated statisticians and programmers can outperform the other two groups. , but possesses unique and complex knowledge and features that are hard to find when working with material.
Since then, data scientists have made tremendous efforts to make themselves valuable and set new standards for what business analytics means. Ability to transform the challenge of C-suite inaccuracies into tangible, approachable, and easy-to-understand insights that can be implemented and directly impact any company’s revenue, traffic, and profits. Understanding what generates engagement with endless data points and what creates loyalty has been a thirsty, ever-evolving question, driving the need for more data and data scientists fighting for it.
The story doesn’t end there. The pandemic has challenged businesses in new ways not just to thrive but to survive. Break through all limitations and known ways, take a giant leap and change everything forever. While artificial intelligence (AI) and machine learning (ML) have always been around and have been used, they have become buzzwords. The birth of many apps caused shock and was widely reported by various media, especially ChatGPT, which caused a new kind of enthusiasm among the older generations due to the sudden and almost immediate adaptation of Gen Z and the almost complete lack of understanding by others. fear.
For someone like me who is new and growing in the world of analytics, artificial intelligence and machine learning are just coined terms for methods and algorithms that have always been around, theorized and implemented. Just to put it in terms, as an umbrella, a lot of researched and experienced knowledge, technology has just made it easy to adapt, and it seems like everyone is making investments that may not really impact their business, but that’s just because Worry about missing out again. Maybe we failed to coin a term early in the game, or missed creating a disruptive, flashy app like ChatGPT to promote our work. Regardless, we are here for this; we breathe data and models and solve challenging problems while maintaining our own value in the organizational world.
