With the arrival of what has been called the Industrial Revolution 4.0 — marked by heavy reliance on real-time big-data processing using machine learning — many businesses have started to integrate data science into their operations.

Many professionals, too, want to upgrade their skills by learning data science — how it operates and how they can apply it to make their day-to-day work easier while boosting their employability along the way.

Andreas Liu, a 28-year-old management consultant with a background in information technology (IT) is one of them.

He said while working for various consulting firms, he became aware of just how important data science was to boost the accuracy and efficiency of overall business processes.

“For instance, businesses analyze a large pool of transaction data to create more sophisticated customer profiles [to determine] their seasonal shopping intensity to identify low and high seasons in order to avoid product stockpiling with precision during certain times of the year,” Andreas told The Jakarta Post in a phone interview.

“At the same time, I noticed that analytics software was in very high demand on the marketplace. Also, simultaneously, I noticed that many job vacancies on the market right now demand that candidates have data science skills in order to analyze big data,” he said.

Andreas noticed that the data analysis skills required of professionals were much more sophisticated than the simple data analysis often conducted on Microsoft Excel. “We have to also learn how to work with a large pool of aggregated data using machine learning, while also creating data visualizations and communicating all this in a language that people understand.”

That is a different set knowledge altogether, so in order to advance his career, Andreas decided to join a data science course offered by the Algoritma Data Science Education Center in Jakarta.

The education center was opened in July 2017 in the Menara Kadin Indonesia office building in Kuningan, South Jakarta, by cofounders Samuel Chan and Nayoko Wicaksono, who currently work as Algoritma’s director and course producer and managing director respectively.

“Simply put, we teach people how to manage a large volume of data to gain knowledge and insight from it. The Industrial Revolution 4.0 era, especially when it has been equipped with 5G internet connections with speeds of 10 gigabytes per second, will further accelerate the use of big data,” Nayoko said, adding that the context explained why data science would become essential for businesses to thrive in the era.

Basic data science skills are also important for professionals to boost their careers and to stay abreast of the digital transformation of workplaces, according to Nayoko.

Nayoko pointed out how human resources (HR) departments could analyze multiple factors from salary trends to proximity from employees’ homes to the office to predict the likelihood that employees were going to resign from their jobs.

“From there, the HR department can devise some interventions to prevent them from leaving,” he continued, perhaps if not by raising their salaries then by providing them accommodations nearer to the office.

“This is how big data works. We can no longer rely on intuition to run businesses. Yet to analyze a large volume complex data we need to use new tools such as R and Python [software] — these are the new Microsoft Excel spreadsheets for the future,” Nayoko explained.

This is where Algoritma comes in. Its instructors teach students how to use new software in order to analyze various types of data to inform specific business decisions.

Number crunching: A student at the Algoritma Data Science Education Center studies material on his laptop during a class. Data analytics can help businesses analyze a large volume of data to create more efficient and accurate business solutions. (JP/Arief Suhardiman)

In a nutshell, according to Nayoko, data science skills consist of several pillars: descriptive skills (explaining post-factum events), diagnostic skills (using post-factum data to diagnose a problem), visualization skills (to make sense of data), predictive skills (to forecast future events) as well as prescriptive skills (to know how to achieve certain goals based on predictions).

To help students acquire these skills, Algoritma currently has 22 full-time instructors with backgrounds in computer science, economics and communications. These instructors are graduates of the Bandung Institute of Technology, Bina Nusantara University, Padjajaran University and the University of Indonesia, among others.

When they are not teaching, these instructors work as onsultants for Algoritma’s clients, who eed data science solutions. This enriches their classroom teaching. To date, Algoritma has had 600 graduates — about 100 sent by their companies and about 500 independent students.

Algoritma has conducted many short workshops, which have been joined by about 7,000 students so far.

One alumnus is Andreas, who took a course in September 2019.

“The emphasis of the course is to use data in order to solve a particular business problem. So, at its core, you have to be able to identify a business problem you want to solve. From there, you can start to define the data that you need to collect and how to analyze it,” Nayoko said.

He said he was helped by the various assignments given by his instructors, which allowed him to translate business needs into proper data analytic solutions across various work lines. He also learned some presentation skills in order to articulate visual data to clients.

“For instance, [we learned] how to create a bank-credit risk analysis application which can help remove logjams in banking operations by helping risk analysts work faster,” Nayoko said.

Windaru, a 29-year-old technical support officer at an IT company, said he had joined the course in September 2019 because he believed his skills would accelerate his work handling government clients, which required a huge volume of data, between 3,000 and 4,000 documents in five years.

“I learned how to use Python software to read sentence patterns faster,” he said.

Windaru said that learning certain new statistical calculations related to data analysis could be difficult. Yet the assignments and one-on-one coaching sessions he got with his instructors had made it easier for him to grasp the new knowledge.

Andreas, meanwhile, said that with the right mindset, he could eventually tackle his learning challenges — which included the fact that he attended the night course three times a week after he had finished more than eight hours of work. “Getting headaches when learning new things is good. It is a sign that our brains are stretching,” he said.

Nayoko said equipping students with a “growth mindset” was important to help them push through the pain of learning. Eventually, Andreas and Windaru were able to reap the fruits of their learning efforts.

“Now, I’ve been able to better advise my clients on how to analyze their business needs, regarding transactions, etc.,” Andreas said.

Windaru said the data science skills he acquired at Algoritma had helped him support his wife’s cookie business using data-driven digital marketing to inform her business decisions more accurately.