By Marilyn Courtois Perin,
Data professionals are a source of value creation and innovation for businesses, in turn driving a customer-centric approach.
Whether referred to as a data scientist or data analyst, a “data specialist” is someone who can enhance customer knowledge by extracting information from raw data. In retail, for example, analyzing available data gives companies better insight into behaviors so they can put predictive strategies in place.
Different jobs towards a single purpose
The names of the data professions have evolved alongside the technology itself. Whereas we once spoke of “data miners,” the terms “data scientist” and “data analyst” are now more common. The changing terminology can be explained by the evolution of the profession itself, with new technologies such as AI and vastly increased amounts of big data.
As well as these changes, the increasing complexity of data processing has given rise to other roles. We need professionals who can handle the incredible volume of data. While nuances exist between different approaches to data in business, they are all aimed at optimizing analyses in specific sectors. As useful as it is in business, data science also plays a vital role in scientific fields.
A new, data-driven business paradigm
In the last few years, the terms “AI” and “Big Data” have entered the mainstream. Meanwhile, the demand for hiring data analysts and data scientists has continued to grow. But businesses didn’t need the current wave of new technologies to make use of their data. They had always done so, albeit on a smaller scale. The difference lies in the size of the task at hand—thanks to even stronger tools, the process of treating large volumes of raw data has been automated.
The real transformation has more to do with the new approaches companies have taken. The need for data organization has broken down silos and reversed the paradigm. Where offers were once built from products or services, today’s approach must be customer-centric. The large-scale influx of data has led to a significant paradigm shift in business. Since they are known and understood through their data, customers today are finally being seen as unique individuals.
Innovation and diversity: an intrinsic link
While the data professions have had a profound impact on businesses, they have themselves been transformed by the widespread arrival of artificial intelligence, which automates certain aspects of data processing. Creativity is necessary for the increasingly important role being played by machines, whose requirement for relevant data can only be met by recognizing the incredible diversity of human beings.
In fact, diversity and innovation go hand in hand; the lack of female data professionals is a major problem. Only 21% of today’s data teams are gender-balanced. It would be wrong to believe that the lack of representation itself is the only drawback. By not exploiting their potential for innovation, companies—and the entire tech ecosystem itself—will lose out. The initiatives launched in response to gender imbalance have accelerated the entry of women into the digital market. The balance should gradually be restored as future data scientists and data analysts continue to enter the workplace. As the data industry expands, we are now seeing women enter the field through different channels. As well as those from traditional engineering or science backgrounds, 21% of women in the data industry are business school graduates.*
As disruptive as they themselves are, the data professions will themselves be disrupted by the influx of artificial intelligence in the field. The AI tools now entering the market can be used to visualize data and create predictive models without the level of mastery it takes to become a data scientist or a data analyst. This is good news for data analysts. As they spend less time on the role’s technical aspects, they will rediscover their creativity and decision-making will become more human again.
* Infographics from Women in Tech Club, conducted by the Turing Club, November 2019.