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There’s more to Data Science than Technology: Role of Human Talent and Diversity

The heated debate is here! Who is more important to our dear Data Science? Technology vs. human and men vs. women

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Recently, just how many times have you heard the terms ‘Data Science’, Artificial Intelligence’, ‘Big Data’, or ‘Data Analytics’? Well probably a lot. Because literally every field on Earth sees bright prospects in the market of advanced analytics. 

Let’s hear the story of how Data Analytics has revolutionized lately.

Not long ago, a not-so-normal Covid-19 happened to the Earth, and which, though a sad tragedy, ironically became an impetus for the big data industry, changing it forever. The world gets more comfortable with the digital and machines get to eat and make massive data.   

More Investments in Technology Based Startups

Now the rich executives make an entry in the scene, who have a penchant for AI-focused startups and their interest lets them flow-in huge dollars thus changing the market dynamics. 

Investments in AI-based startups are happening with increasing intensity to create advanced and more efficient technologies that could solve problems across a variety of industries- including for example, financial services, government sector, health care, environment and sustainability, and retail. 

According to a research by the Organization of Economic Collaboration and Development- OECD, global venture capital VC investments in AI technology startups has reached US$75 billion as of 2020 which, in the last decade, indicates a ginormous 25x increase.

So what could possibly ruin the joy of this Data Journey? 

You may haven’t noticed yet but there’s a catch in this much impeccable scene. With analytics expanding to ever wide industrial range, the investments in the technologies are far more than in the area of human talent. Ouch! 

Good thing is that our heroes across the industry have entered the scene to offer us solutions. Phew! 

Leaders across the data analytics industry share their thoughts over the potentially increasing skill gap in the industry. Mary Purk, the Executive Director of Wharton Customer Analytics and AI for Business says: 

“It’s easy to characterize big data and AI as a technical field, when in fact it is highly interdisciplinary in nature and impacts almost every aspect of our lives.”

We agree with Purk, after all data is just data without any data engineers and data scientists to perform analytics, and so the skillset of the data workforce on duty would determine its usefulness to convert to actionable information.  

Now how to foster Human Talent?

Good question, and the answer is: ‘Let’s work on ourselves’

Photo by Min An from Pexels

Human talent in the field of data analytics means a good grasp on STEM (Science, Technology, Engineering, and Mathematics) education to allow individuals to understand the technical aspects of data analytics and machine learning. 

With a boost in the Big Data Analytics industry a pool of talent will be required to support the projected industrial growth. And which means encouraging individuals to pursue STEM studies in the field of Data Analytics, AI, Machine Learning, and Big Data. 

What can Gender Offer to Data Science?

Diversity we say. You ask how? Let’s dig deeper.

Photo by Magda Ehlers from Pexel

The inclusion of skilful women in the field of data analytics is equally important from the view of ‘diversity at workplace’ – a key element in supporting effective business strategic decision making and driving innovation. Men have already dominated the tech industry so for this reason we shall narrow our discussion to what’s missing, that is, women. 

And we say skillful women because aptitude matters too of course. Purk highlights the need for data scientists in which women should take part too:

 “First, Because we need more data scientists, but more importantly, we need a diversity of viewpoints to effectively solve problems with data.” 

Enabling diversity and inclusion in the workplace – or what we commonly refer to as a zero gender gap, doesn’t just mean filling up spaces for the sake of offering equal opportunity to skilful women, it is more than women empowerment. It also means enabling value creation within a business scenario where the variety of viewpoints offers new perspectives to solve problems within the domain.  Julie Roehm, a growth leader in the retail industry views diversity as a business impetus, and states it as: 

“When it comes to analytics, diversity is less about good HR policy and much more about business impact”.

As women participate in the analytics industry, the diverse viewpoints, skills, and understandability will function in improving work flows and creating better paths towards business stability. 

Pejoratively, there aren’t many women available to show up for data analytics job entries. As an example, within the U.S only 26% of data professionals are women reflecting a potential lag in opting for a STEM career after high school. 

According to the UN’s EQUALS research report 2019, young girls around the globe are less interested in STEM subjects during their secondary education and display low self efficacy towards ICT subjects leading only 35% of women to develop a career in STEM related fields. 

What has Caused Digital Inequality? And How to Cope With It?

The causes of digital inequality globally includes factors such as: 

  1. Lack of educational and functional literacy of digital skills.
  1. Lack of information about STEM education and related career paths during the decision of higher education. The choice of women’s career is greatly influenced by parents who are ill equipped with STEM knowledge and opportunities offered by such subject areas. 
  1. And lack of role models and existing underrepresentation which inhibits the participation of women in becoming successful computer scientists or engineers. As an example, consider the case of discrimination in Pakistan’s tech industry where a report find that:

Out of 100 directors across 13 tech companies listed in Pakistan Stock Exchange, only 11 are women with 3 companies with absolutely no presentation of female

The result is as the report states, a lack of perspective hindering the inclusive design of solutions in the tech industry.  

So what can we do? 

Well, all the great men and women out there can help create equal opportunities to involve the other half of the world’s population. 

Photo by Rodolfo Quirós from Pexels

The EQUALS study also reports policy initiatives across countries to encourage women towards STEM education that includes coding classes, bootcamps, and makerspaces along with other solutions such as- greater and safe access to internet and technology, career guidance on STEM education, inclusion of women in STEM related careers, and government and volunteer efforts in making policies on human rights.

Data is literally going to impact the gamut of our daily lives by the end of the decade, and solutions are to be enhanced to fulfill the promise of data which certainly, as we believe, comes from an inclusive and diverse workplace where human talent matters before technology.

Ayesha
Ayesha
I engineer the content and acquaint the science of analytics to empower rookies and professionals.
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Please enter your name here

Most Popular

There’s more to Data Science than Technology: Role of Human Talent and Diversity

The heated debate is here! Who is more important to our dear Data Science? Technology vs. human and men vs. women

Recently, just how many times have you heard the terms ‘Data Science’, Artificial Intelligence’, ‘Big Data’, or ‘Data Analytics’? Well probably a lot. Because literally every field on Earth sees bright prospects in the market of advanced analytics. 

Let’s hear the story of how Data Analytics has revolutionized lately.

Not long ago, a not-so-normal Covid-19 happened to the Earth, and which, though a sad tragedy, ironically became an impetus for the big data industry, changing it forever. The world gets more comfortable with the digital and machines get to eat and make massive data.   

More Investments in Technology Based Startups

Now the rich executives make an entry in the scene, who have a penchant for AI-focused startups and their interest lets them flow-in huge dollars thus changing the market dynamics. 

Investments in AI-based startups are happening with increasing intensity to create advanced and more efficient technologies that could solve problems across a variety of industries- including for example, financial services, government sector, health care, environment and sustainability, and retail. 

According to a research by the Organization of Economic Collaboration and Development- OECD, global venture capital VC investments in AI technology startups has reached US$75 billion as of 2020 which, in the last decade, indicates a ginormous 25x increase.

So what could possibly ruin the joy of this Data Journey? 

You may haven’t noticed yet but there’s a catch in this much impeccable scene. With analytics expanding to ever wide industrial range, the investments in the technologies are far more than in the area of human talent. Ouch! 

Good thing is that our heroes across the industry have entered the scene to offer us solutions. Phew! 

Leaders across the data analytics industry share their thoughts over the potentially increasing skill gap in the industry. Mary Purk, the Executive Director of Wharton Customer Analytics and AI for Business says: 

“It’s easy to characterize big data and AI as a technical field, when in fact it is highly interdisciplinary in nature and impacts almost every aspect of our lives.”

We agree with Purk, after all data is just data without any data engineers and data scientists to perform analytics, and so the skillset of the data workforce on duty would determine its usefulness to convert to actionable information.  

Now how to foster Human Talent?

Good question, and the answer is: ‘Let’s work on ourselves’

Photo by Min An from Pexels

Human talent in the field of data analytics means a good grasp on STEM (Science, Technology, Engineering, and Mathematics) education to allow individuals to understand the technical aspects of data analytics and machine learning. 

With a boost in the Big Data Analytics industry a pool of talent will be required to support the projected industrial growth. And which means encouraging individuals to pursue STEM studies in the field of Data Analytics, AI, Machine Learning, and Big Data. 

What can Gender Offer to Data Science?

Diversity we say. You ask how? Let’s dig deeper.

Photo by Magda Ehlers from Pexel

The inclusion of skilful women in the field of data analytics is equally important from the view of ‘diversity at workplace’ – a key element in supporting effective business strategic decision making and driving innovation. Men have already dominated the tech industry so for this reason we shall narrow our discussion to what’s missing, that is, women. 

And we say skillful women because aptitude matters too of course. Purk highlights the need for data scientists in which women should take part too:

 “First, Because we need more data scientists, but more importantly, we need a diversity of viewpoints to effectively solve problems with data.” 

Enabling diversity and inclusion in the workplace – or what we commonly refer to as a zero gender gap, doesn’t just mean filling up spaces for the sake of offering equal opportunity to skilful women, it is more than women empowerment. It also means enabling value creation within a business scenario where the variety of viewpoints offers new perspectives to solve problems within the domain.  Julie Roehm, a growth leader in the retail industry views diversity as a business impetus, and states it as: 

“When it comes to analytics, diversity is less about good HR policy and much more about business impact”.

As women participate in the analytics industry, the diverse viewpoints, skills, and understandability will function in improving work flows and creating better paths towards business stability. 

Pejoratively, there aren’t many women available to show up for data analytics job entries. As an example, within the U.S only 26% of data professionals are women reflecting a potential lag in opting for a STEM career after high school. 

According to the UN’s EQUALS research report 2019, young girls around the globe are less interested in STEM subjects during their secondary education and display low self efficacy towards ICT subjects leading only 35% of women to develop a career in STEM related fields. 

What has Caused Digital Inequality? And How to Cope With It?

The causes of digital inequality globally includes factors such as: 

  1. Lack of educational and functional literacy of digital skills.
  1. Lack of information about STEM education and related career paths during the decision of higher education. The choice of women’s career is greatly influenced by parents who are ill equipped with STEM knowledge and opportunities offered by such subject areas. 
  1. And lack of role models and existing underrepresentation which inhibits the participation of women in becoming successful computer scientists or engineers. As an example, consider the case of discrimination in Pakistan’s tech industry where a report find that:

Out of 100 directors across 13 tech companies listed in Pakistan Stock Exchange, only 11 are women with 3 companies with absolutely no presentation of female

The result is as the report states, a lack of perspective hindering the inclusive design of solutions in the tech industry.  

So what can we do? 

Well, all the great men and women out there can help create equal opportunities to involve the other half of the world’s population. 

Photo by Rodolfo Quirós from Pexels

The EQUALS study also reports policy initiatives across countries to encourage women towards STEM education that includes coding classes, bootcamps, and makerspaces along with other solutions such as- greater and safe access to internet and technology, career guidance on STEM education, inclusion of women in STEM related careers, and government and volunteer efforts in making policies on human rights.

Data is literally going to impact the gamut of our daily lives by the end of the decade, and solutions are to be enhanced to fulfill the promise of data which certainly, as we believe, comes from an inclusive and diverse workplace where human talent matters before technology.

Ayesha
Ayesha
I engineer the content and acquaint the science of analytics to empower rookies and professionals.
RELATED ARTICLES

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Most Popular