Data, Higher Education & Social Justice

My Interview with Tableau

Photo by ev on Unsplash

At Tableau, we feel that data skills are essential for the next generation of professionals and business leaders. The Tableau Academic Programs seek to arm students and instructors with the valuable analytical skills needed to think strategically and make an impact.

Data is such an important piece of the social justice puzzle, and using critical data skills can drive insights into real actionable change.

In our new series, Data and Education for Social Justice, we’re excited to spotlight people in the education community that is making a difference in the social justice world.

These spotlights will highlight five main principles of social justice:

  1. Access to Resources
  2. Equity
  3. Participation
  4. Diversity
  5. Human Rights

The Spotlight: Olushola Olojo

Our first spotlight is Data Consultant, Olushola Olojo, hailing from Lagos, Nigeria.

Olushola currently resides in London, United Kingdom, and holds a Bachelor’s degree in Economics from The University of Memphis.

Utilizing Tableau as his primary data visualization software, Shola has built a professional career as a Freelance Data Consultant. More recently, he has accepted a role to join Samsung UK as a Lead Insight Analyst.

We were keen to explore his thoughts on how data can be leveraged to drive positive social change.

Olushola Olojo, Lead Insights Analyst at Samsung UK

The Interview

JL: Should data be discussed in terms of Social Justice? If so, why?

OO: A resounding YES!

I once published a piece on Medium centered around the upsurge of the internet in recent years and how ubiquitous its use has become in our society.

When discussing the topic of “Social Justice” and how that is nested in our growing access to real-time information, I cannot help but recall the events surrounding the tragic death of George Floyd.

Live video footage shared through various social media platforms sent shockwaves across America, galvanizing an entire social justice movement against police brutality. This was a call to action with pockets of communities springing up to address issues of disparity embedded in race, gender, and class.

Technological advancements have made efforts of such communities, that may have previously been hidden in the shadows, quantifiable, and readily available for the public. This offers actionable insights that drive decisions required to create lasting social reforms in marginalized circles.

Rather than being deemed as mutually exclusive elements, data and science should be viewed in unison. And when coupled together becomes an unparallel force to enact real change.

JL: How do you see Academia supporting these efforts?

OO: This is a tricky question because the growth of the internet has impacted people’s perception of traditional brick-and-mortar institutions. Even more apparent in a field like Data Science, where a four-year degree is often not required to break into the industry.

Further compounding this issue is the emergence of MOOCs (massive open online courses). It has become increasingly difficult for universities/colleges to compete and offer credible, affordable courses that prepare individuals looking to make that leap into big data.

Nonetheless, academia can still serve an integral part in developing the next generation of “data handlers”.

As an undergraduate, I majored in Economics at The University of Memphis. You can only imagine my dismay when obligated to take courses like ECON 4351: International Monetary Policy or ECON 3320: Advanced Macroeconomic Theory, reiterating principles and policies dating back several decades. Sure, it was invaluable information but always a complete snooze fest.

Cue ECON 4220: Urban Economics taught by Dr. Jamein Cunningham. This was an exploratory course that examines issues relevant to cities, including the reasons why cities exist, how economic activity is organized within cities; transportation, poverty, crime, development, and public finance.

Dr. Cunningham placed the class right at the heart of real-world issues, citing live publications in his teachings.

One such example looked at Nashville’s recent economic boom and how that resulted in a detrimental decline of Memphis as Tennessee’s capital city. Mass outmigration increased unemployment and a higher crime rate. It was all prevalent in Memphis, and we had front-row seats to determine why this was the case.

Simple as that!

Drawing from this active teaching approach and employing internship/study abroad opportunities, academia can carve out new avenues to support efforts of data being used in terms of social justice.

All post-COVID, of course.

Given the current climate, traveling abroad doesn’t seem feasible but it would be interesting to observe how data is used to tackle social issues in different countries.

JL: What can instructors do?

OO: Curve the heck out of exams.

In all seriousness, I understand the importance of weekly assessments in ensuring that students understand the material, but this shouldn’t be a priority.

I am a strong advocate of instructors exploring real-life datasets with their students in an attempt to upskill their technical stack and learn how to work with big data.

My limited research on the Tableau Academic Program suggests that it is an initiative that champions this methodology and is actively putting the protocols in place to facilitate this style of learning for both instructors and students.

Furthermore, instructors can use their platform as educators to connect with public figures in the Tableau community. There are some wonderful initiatives available in the #DataFam circle.

Perhaps the most applicable initiative to the theme of social justice would be “Diversity In Data”, which was recently coined earlier in the year by Eve Thomas and Autumn Battani.

Instructors interested in learning how to combine data with social justice issues should certainly have a look.

JL: What can students do?

OO: Be a student.

I highly encourage students to be more aggressive with their learning, taking control when possible. Stealing a paraphrase from Alice in Wonderland,

“In my kingdom, you need to run as fast as you can just to stay in the same place.”

— Red Queen

The Red Queen was spot on. This statement is a very fitting description of what the journey into the world of data encompasses.

For starters, you are inundated with new information daily about what to actually learn. If it’s coding that you’re interested in, what is the ideal path to follow? Is it Data Science, Machine Learning, or Web Development?

Further compounding the confusion of your learning is the constant emergence of new technology in the tech space. It’s as though everywhere you look there is new software popping up, with claims of being the best in the business at streamlining data analytics.

This is exhausting even for seasoned data professionals, let alone newbies trying to find the door — many of which get lost in the shuffle and quit in less than a year.

Drawing from my own personal experience, I actively took control by seeking out content specific to my industry. I absorbed what was useful, discarded what I felt was irrelevant, and added what was uniquely mine.

More importantly, I adopted the mental paradigm shift of becoming a life-long learner and developed the ability to pivot at any moment. Although far from polished, this strategy has served me in surviving the noise and elevating myself to become a highly competent data user.

Whilst learning Tableau, I connected with Tableau Zen Masters and took detailed notes on not only how they manipulated certain datasets but their thought process behind arriving at their solutions. With extensive practice, I grew to devise my own unique way of creating compelling, insightful visualizations that sought to communicate information in a clear, intuitive format.

For students seeking to enact lasting change through the use of data albeit in terms of Social Justice, Sustainable Energy, or Nonprofit and Foundation, I would highly recommend playing with real-world data of your chosen field.

Furthermore, connect with industry leaders, and align your ideals with communities that share your interest.

Simply get stuck in.

“Don’t ask for advice, ask for feedback.”

JL: Data and Social Justice — Where should people get started?

OO: Certainly explore these Tableau community-led projects that are listed below. Real-world datasets are shared weekly for public use by renowned Tableau users in the #DataFam circle.

Notable Initiatives

  1. Makeover Monday
  2. Diversity in Data
  3. Project Health Viz

Start now.

Dive into this dataset curated by UNICEF: Gender Inequality in HIV Infections in Adolescents.

Here is a link to my visualization using this exact dataset: Have fun with it and please feel free to share what you manage to put together.

JL: And lastly, what is a personal motto that you live by?

OO: I actually live by two that resonate with me on multiple fronts.

“Journey happily as opposed to arriving successfully”


“Broken crayons still color”.

Connect with Shola

If you would like to learn more about Shola and the work he does, connect with him on his social platforms.

Jessica Lyon, Program Manager

Jessica Lyon

Senior Program Manager Tableau for Teaching

March 23, 2011

Ex-Division I Student-Athlete • Data Enthusiast • Full-Time Arsenal Supporter • Combatting Poverty & Bridging Inequality

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