Realizing Potential: Joining the Data Science Wave

2016-2017 Issue 1

Data science professionals are unlocking the potential of exponentially increasing volumes of data to solve business problems – and you could become one of them. The field of data science is on the rise, reaping the benefits of large data sets and new innovations.

Entering the industry has never been more desirable. The field of data science will continue to experience an upsurge through 2020, with IBM predicting an increase of 28% in demand. Part problem solvers, part quant whizzes, data science professionals take on challenges in a wide range of industries.

Nathanael Weill is a data scientist at mnubo, a key global player in Internet of Things (IoT) analytics, with extensive experience solving business problems, such as the ideal amount of water needed for farms to succeed.

“[Data scientists] are the most suited to handle complex data using their strong background in both statistics and computer science,” explains Weill. Predicting exactly what is needed and when, from water to product modifications, is of great value to every kind of operation.

The IoT data analytics market alone is expected to grow globally at a rate of more than 25% from 2016 to 2022, according to Market Research Future. IoT includes data created by any device connected to the Internet, providing inexhaustible fodder for analysis. Weill has worked to harness this data and extract actionable insights for businesses.

The complexity of processing real-time, and often unorganized, data requires a firm understanding of how data operates. Along with technical skills, creative problem solving is at the root of data science. “Those with a computer science background are well-suited to the field, but it still requires a new way of thinking,” elaborates Weill.

The data science field requires a leap into the unknown and the bravery to test hypotheses. Weill recommends testing the waters by taking part in hands-on projects or competitions. A great place to start is joining a competition on Kaggle, where you can work on projects like creating an algorithm to optimize U.S. Transportation Security Administration (TSA) security screenings for shorter wait times.

Those who learn best in a structured environment can attend data science or data analytics programs. The McGill School of Continuing Studies is now offering two new programs to help professionals develop in-demand skills. The two programs offer separate yet complementary paths – one oriented to data science and machine learning with an added focus on technical competencies, and the other designed to prepare business leaders to excel in data-driven decision-making and data strategy implementation.

To ensure the programs align with the needs of the job market, consultations with industry experts, academic specialists and practitioners shaped program content and goals. Nabil Beitinjaneh, a leading consultant, businessman and member of the School’s Advisory Board, notes the rigorous consultation process as key to incorporating a variety of local industry perspectives.

“We had open discussions to create learning solutions that work for industry partners,” explains Beitinjaneh. “The two programs aim to build different yet complementary skills and allow for collaboration between student cohorts through a common course and a capstone project.”

Weill was also part of the expert team of professionals that guided the programs’ creation. “I had to learn [the needed skills] all by myself, so I would have loved to have taken the new program,” says Weill. Overall, entering the field requires a certain degree of self-starter tendencies and curiosity, but the complexity of navigating tools and methods is streamlined by taking a professional program.

Khaled Tannir, a big data architect and data scientist, who also contributed to the creation of the new McGill programs, recommends that those interested in data science reflect on how deeply they wish to invest in needed technical competencies. The demand for data science professionals will continue to increase, as well as the demand for data analysis literacy in other professions.

“All industries are going to experience an increase in demand, especially larger companies,” notes Tannir. “The financial, insurance and telecom industries will see the biggest need for data science [expertise].” Whether you wish to be at the front lines of Big Data, or at the sidelines ready to interpret and implement analysis, data science will only continue to shape business innovation and the success of organizations.



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