The sexiest job of the 21st century
BREAKTHROUGH - Elfren S. Cruz (The Philippine Star) - May 26, 2019 - 12:00am

Data science and data analytics are topics that I never thought would be the topic of my column. These are topics best left to technology sections. But I was definitely intrigued when I saw a Harvard Business Review article that had the title “Data Scientist: The Sexiest Job of the 21st Century.” If that is the case, then this is a topic the average readers should start familiarizing themselves with. I also discovered that two of the Philippines’ major educational institutions – De La Salle University and the Asian Institute of Management – have started offering graduate courses in Data Science.

The HBR article defines the “data scientist” as a high ranking professional with the training and curiosity to make discoveries in the world of big data. Data science has been defined as the use of scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Another well known writer on modern science, Jim Gray, described data science as the “fourth paradigm of science,” explaining that the first three paradigms of science were “theoretical, empirical and computational.” The latest paradigm is now “data-driven.” For those who are regular watchers of the television series Big Bang Theory will remember that Sheldon prided himself on being a “theoretical physicist,” the apex of scientific fields. Well, a new replacement series could replace him with a data scientist.

Like all the other new technologies, the term data science was coined only recently – 2008 – by D.J. Patil and Jeff Hammerbacher, then the respective leads of data and analytic efforts at LinkedIn and Facebook. Today, thousands of data scientists are already working at both start-ups and well established companies. Here is what the HBR article wrote:

“Their (data scientists) sudden appearance on the business scene reflects the fact that companies are now wrestling with information that comes in varieties and volumes never encountered before. If your organization stores multiple petabytes of data, if the information most critical to your business resides in forms other than rows and columns of numbers, or if answering your biggest question would involve a ‘mashup’ of several analytical efforts, you’ve got a big data opportunity.

Much of the current enthusiasm for big data focuses on technologies that make taming it possible, including Hadoop (the most widely used framework for distributed file system processing) and related open source tools, cloud computing and data visualization. While those are important breakthroughs, at least as important are the people with the skill set (and the mindset) to put them to good use. On this front, demand has outpaced supply. Indeed, the shortage of data scientists is becoming a serious constraint in some sectors.“

Any understanding of data science requires also knowledge of another term, data analytics. This is the science of analyzing raw data in order to make conclusions about that information. These techniques can reveal trends that would otherwise be lost in the mass of information. Any type of information can be subjected to data analytic techniques to get insight that can be used to improve processes or spot trends. For example, manufacturing companies often record downtime, runtime and work queue for various machines and then analyze the data to better plan the workloads so the machines operate closer to capacity.

Gaming companies use data analytics to set reward schedules for players that keep the majority of players active in the game. Content companies, like social media companies, use data analytics to keep a person clicking, watching or reorganizing content to get another view or another click.

There are new slang words that have arisen due to the rise of this new science. The term “quant” is slang for an expert in the use of mathematics and related subjects, particularly in investment management. But what happens if you are a “non-quant,” can you still exploit data analytics? HBR has another article that shows how to make “Analytics Based Decision Making in Six Easy Steps:

1. Recognize the problem or the question. Frame the decision or business problem, and identify possible alternatives to the framing.

2. Review previous findings. Identify people who have tried to solve this problem or similar ones – and the approaches they used.

3. Model the solution and select the variables. Formulate a detailed hypothesis about how particular variables affect the outcome.

4. Collect the data. Gather primary and secondary data on the hypothesis variables.

5. Anayze the data. Run a statistical model, assess its appropriateness for the data, and repeat the process until a good fit is found.

6. Present and act on the results. Use the data to tell a story to decision makers and stakeholders so they will take action.

In this new world of data analytics, businessmen must learn to combine the science of analytics with the art of intuition. Warren Buffett once said: “Beware of geeks...bearing formulas.” But, the HBR article contends that in today’s data driven world, one cannot afford to ignore “geeks.” Instead, the advice is to be a manager who knows the geeks, understands their formulas, helps improve their analytic processes, effectively interprets and communicates the findings to others, and makes better decisions.

Hal Varian, the chief economist at Google, said: “The sexy job in the next 10 years will be statisticians. People think I’m joking, but who would have guessed that computer engineers would’ve been the sexy job of the 1990s?”

The inevitability of data science and data analytics as basic tools in business is inevitable. There will come a time – very soon – when even small and medium sized firms in all industries will need to apply these tools to remain competitive – to survive. The advance of big data shows no sign of slowing. It is in fact accelerating. As Professor Thomas Davenport wrote: “Think of big data as an epic wave gathering now, starting to crest. If you want to catch it, you need people who can surf.” You will need people who understand data science.

Creative writing classes for kids and teens

Young Writers’ Hangout on June 1, 8, 15, 22 (1:30 pm-3 pm; stand-alone sessions) and for the Adult Series, Writing with Humor and Satire with John Jack G. Wigley on June 29 at Fully Booked BGC. For details and registration,  email writethingsph@gmail.com.

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Email: elfrencruz@gmail.com.

ANALYTICS BASED DECISION MAKING DATA SCIENCE
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