From Baseball Cards to Big Data Analytics

by Dawn Holl, JD

I was honored to join Alteryx co-founder Libby Duane Adams, host Kimberly Branic, and the Women of Analytics (WoA) audience to talk about my data analytics career journey and the importance of upskilling and diversity in the field of analytics. I thoroughly enjoyed our lively conversation and exchange and appreciated the thoughtful questions posed by Libby and our audience. If you missed our fireside chat, you catch the on-demand recording here. Or, share it with your colleagues so they can be inspired to enhance workplace diversity, democratization, and upskilling.

Baseball, Bubble Gum & Analytics

As I shared with the WoA audience, my Dad was a professional baseball player who trained my brother and me to play hardball from a very young age, which led to my love of the game – and ultimately, a career in analytics.  Growing up in a New Jersey suburb of New York City, I knew every name and jersey number of the NY Yankees’ players. (Please don’t hate on me; I came by it honestly – Dad was a diehard fan.) When I saw my first baseball card among an impressive collection owned by my best friend’s older brother, I was amazed at the list of statistics compiled for each player. This data gave me valuable information about their past and predicted performance. Individual player stats helped me assess the likelihood of a player getting on base, striking out, or hitting a home run when there were two outs with bases loaded. The insights I took from the baseball card stats kept me engaged in the game – and made it even more fun to watch my favorite players on the field. Plus, each card came with a stick of bubble gum!

Faster Diagnosis with Advanced Analytics?

When I was in college, a close family member became seriously ill with a mysterious array of symptoms.  I accompanied her to doctor after doctor, and each one was puzzled by it all. After months of testing her for a wide range of conditions, doctors finally arrived at a diagnosis. She had Sarcoidosis, a severe autoimmune disease, for which there is no cure, only treatment for symptoms. The outcomes for patients afflicted with Sarcoidosis vary, death is a possibility and permanent physical damage is common, especially if the patient is not treated quickly. Her medical team was a bit shocked and said they refrained from testing her sooner because she didn’t neatly fit their profile of someone more likely to develop this disease. The irony is she displayed all the classic symptoms. While my family member waited for a diagnosis, her respiratory system sustained severe and irreversible damage due to delay of treatment. I realized then, if medical researchers and healthcare professionals had representative diagnostic data and better analytics tools, her doctors may have arrived at the diagnosis much sooner. Instead, they were unduly – and inadvertently – biased because my family member did not fit the “typical” patient profile.

Unrecognized Bias in Data & Analytics

This also brings to light the issue of unrecognized bias in data and analytics, which is a complex, widespread problem. The presence of overt and hidden bias in data and algorithms unduly influences decisions that negatively and disproportionately impact underrepresented individuals and populations. A recognized strategy to mitigate bias and the harmful effects it has on lives and livelihoods is to create diverse, cross-functional teams to build these algorithms and ensure the veracity of the data. We must make it our mission to continuously identify and neutralize bias so that data analytics solutions and insights are more accurate and equitable across all populations. Implementing hiring strategies that attract and retain a diverse workforce is a powerful step toward achieving this goal.

The world of technology is best served by creativity, innovation, and inclusion.  Data analytics must reflect various professional/education/life experiences, cultures, races, ethnicities, genders, ages, capabilities, psychosocial perspectives, backgrounds, and more. Constant curiosity, persistence, and critical thinking, despite any formal training and education, are minimum requirements for anyone interested in a career in analytics. While specific technical skills rightfully occupy a prominent place in analytics, leaders need to recognize the value of having a diverse cross-section of expertise and experience around the table. At Reveal, and in working with Alteryx and our clients, we witness extraordinary results coming from this commitment.

The Reveal team comprises folks from different walks of life, a range of cultures, ages, ethnicities, races, and gender, to name a few. We recognize a multiplicity of perspectives is crucial to creating highly-quality, innovative, and often groundbreaking work. A diverse “brain trust” enables our teams to work more effectively with clients and leverage their unique insights. We like to dig deep and “fall in love” with the problems our clients are facing and gain a deep understanding of the impact on their business, mission, and team. Only then can we effectively partner with them and create advanced analytics that deliver optimal value and solutions with integrity. A good example of this approach is the advanced analytics work Reveal is doing for the U.S. Census Bureau that leverages Alteryx’ robust technology.

Digital Transformation for Government Agency Big Data

The U.S. Census Bureau case study shared with the WoA audience underscores the transformative power of advanced analytics and process automation to modernize business processes and upskill the workforce. While most people know the Census Bureau as the official “people counter,” they may not know the Census is the nation’s leading provider of data and indicators that reflect the United States’ economic health. For example, Census reports on the status of residential, commercial, and public sector construction activity across the country. This is a critical economic indicator that impacts multiple industries and moves global financial markets. Historically, Census has primarily relied on resource-intensive survey data collection and reporting methods.

Census is in the process of modernizing its practices. It contracted with Reveal to re-engineer and automate processes in place for ~50 years using advanced analytics and best-of-breed technology. Our team worked with the Census staff, subject matter experts, and industry thought leaders to develop an innovative solution that harnesses the power of cutting-edge analytics and Alteryx technology. In addition to Alteryx’ robust analytics process automation (APA) platform, we leveraged emerging technologies, such as:

• Artificial Intelligence and Machine Learning;
• Reveal’s proprietary high-resolution image analytics;
• Convolutional Neural Networks (CNN); and
• Advanced visualization techniques to create an end-to-end solution.

The Census construction indicator solution ingests, parses, and analyzes structured and unstructured data, including Census data, 3^rd party building data, and satellite imagery. Throughout the transformation process, we closely collaborated with our Census team partners to eliminate tedious, manual workflows, upskill their capabilities, and enable them to focus their expertise and experience on higher-value activities and outcomes.

From my initial exposure to the power of data and analytics that began quite accidentally as a child to my current leadership role at Reveal, it is my great honor to play a part in leveraging the evolving world of technology to make contributions that benefit others. We all have a place in this world and each one of us holds an open invitation to make our own unique contributions to the analytics movement.