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DCE Magazine

Winter 2022

Exploring the World of Data Science

Insights into the tech tools students need to succeed in the dynamic field of data science and analytics.

In today’s digital economy, Big Data is king, and knowing how to mine, process and analyze it is essential for organizations to thrive in the global business community. Making sense of the trillions upon trillions of raw data bits that power the world is inarguably the key to developing the most effective strategies in the 21st century.

It’s no surprise that data science and analytics have evolved into dominant disciplines for tech-savvy professionals in virtually every industry imaginable, enabling organizations to make the most informed decisions internally and externally, whether it’s in marketing, engineering, product development — you name it.

Clearly the data science ecosystem has grown from a luxury of sorts to a necessity for any business hoping to remain competitive. Enhanced by advanced technologies such as Artificial Intelligence and Machine Learning, the field has grown exponentially more sophisticated in the past decade or so, branching out with a broad range of specialized applications.

To get a better understanding of this dynamic and innovative field, a trio of DCE instructors explored the current state of data science in a wide-ranging webinar discussion, highlighting the tools students need to launch a successful career.

“Right now, if you’re going to be a data scientist in the data analytics field you have to know Python — you can’t get away from it.” Dursun Delen, Data Science instructor

Science vs. Analytics

Professionals with a strong background in data science and analytics are in high demand, all three experts agree. But what’s the relationship between the two? Think of the latter as a specific application of the former.

Data analytics is sort of a new term for what we used to call data mining or decision-support systems about 20 years ago,” said Dursun Delen, Data Science instructor. “The idea is, how can we use this most valuable asset of organizations — the data itself — to make smarter and faster decisions? That’s what data analytics stands for: making smarter, faster decisions using evidence-based information you get from data both inside and outside the organization.”

A good way to visualize the relationship between data science and analytics is to draw a large circle with a smaller one within it, said Majed Al-Ghandour, Data Science instructor. “I’ll draw two circles, with the big circle being data science and a smaller inner circle representing data analytics.”

In a business setting, the role of the data analyst is quite similar to that of the project manager, Delen added. “I actually teach a course on project management in analytics that covers basic project management skills.”

Building your toolkit

To succeed in this space, it’s a good idea to start building a solid foundation in data science and develop a range of versatile analytic tools based on your career goals. Don’t become overly dependent on whichever tool or application that happens to be trending at the time.

“The trick is, if you’re too tool-focused your perspective becomes too narrow,” said Keith McCormick, Predictive Analytics instructor. “It becomes the career equivalent of trying to manage a hedge fund, and that can be a dangerous game.”

The landscape can change quickly, he warned, and if a candidate goes into a job interview banking on their expertise with a buzzworthy analytic tool, that can backfire big time. It’s much more advantageous to gain expertise in a handful of essential tools, he added.

Perhaps the most essential skillset of all is a background in Python Programming, Delen added. “Right now, if you’re going to be a data scientist in the data analytics field you have to know Python — you can’t get away from it. Python is going to be your default scripting program if you’re going to be a data scientist.”

Along with Python, Delen stressed the need for mastering at least three to five tech tools that can be used interchangeably, “depending on what the constraints are.”

A path to success

DCE offers four certificate programs that cover the full range of data science disciplines and specializations, each providing a wealth of essential tools for aspiring professionals. Together they form a path to success in every area of data science; separately they can bolster expertise in any single specialization.

Data Analysis for Business teaches an array of tools and skills for driving strategic business decisions. Students learn fundamental concepts behind collecting, storing, and analyzing data to accurately forecast trends and behaviors, covering predictive, prescriptive, and descriptive analytics. Elective courses include introduction to Python Programming and SQL, as well as data warehouse development.

Data Science lays the foundation for students seeking a broad background as a data scientist, covering statistical and computer science techniques for exploring and analyzing data. Students learn how to use common data science tools along with basics in cloud computing, R Programming, and introduction to Machine Learning and Python.

Predictive Analytics teaches how to develop actionable plans from corporate data and initiatives to increase sales, reduce marketing costs, and improve customer retention. Students are provided key tools for solving business problems with predictive analytics, while taking a deeper dive into R Programming and Big Data.

Machine and Deep Learning focuses on Natural Language Processing, the current state of the art in Artificial Intelligence, as well as data mining and data analysis. The curriculum includes introductory and intermediate Python, as well as a background in Artificial Neural Networks and Big Data analysis.

A strong background in any area of data science can be a gold ticket to a lucrative career. Often overlooked, however, is that working in this field can be, well, fun. “I’m very lucky because what I’ve been doing got more and more popular, and now it’s the pinnacle of almost all professions,” Delen said. “I’m enjoying it every day. It’s fun to turn raw data into something that makes sense, something that solves a question that is seemingly unsolvable and then helps an organization move forward.”

Learn more about DCE’s technology programs.