When we think of pioneers in data analysis, we often envision statisticians, machine learning engineers, and analysts diligently working through intricate datasets. However, after reading about Mary Anning, the 19th-century fossil hunter known for inspiring the tongue twister “she sells seashells by the sea shore,” I was struck by how her work exemplifies the core qualities of a data analyst.
Mary Anning’s story holds valuable lessons for anyone engaged in data work, investigation, and the quest for truth. Her journey is a reminder that great discoveries often come from those willing to question, dig deeper, and connect the dots [1]. Whether you’re analyzing fossils or datasets, the principles remain the same: look beyond the obvious, provide meaningful context and piece together a compelling narrative [2]. At its core, data analysis is about uncovering mystery, finding order in chaos and bringing hidden truths to light. This pursuit is often thankless and fraught with challenges, yet it is essential for advancing our understanding of the world [3]. Mary Anning, largely self-taught and was marginalized from the scientific community for being a woman, yet she kept working, one fossil at a time, with dedication and resilience, to profoundly change our understanding of prehistoric life. So next time you’re deep in a dataset, hunting for insights no one else has spotted yet, remember: you’re not so different from the woman who unearthed the past and rewrote history.
1. Uncovering the Unseen
Mary Anning was born in 1799 in Lyme Regis, a small coastal town in Southwest England. Her father, a carpenter, supplemented the family’s income by selling fossils he collected from the cliffs nearby. As a child, Mary often joined him and her brother Joseph on fossil hunts, helping them find curiosities like “snake-stones” (ammonites) and “devil’s fingers” (belemnites) to sell to tourists. But fossil hunting wasn’t just a fun pastime, it was survival. The work was dangerous, with cliffs prone to collapse, but a major discovery could mean the difference between eating well or going hungry. After her father died in 1810, Anning had no choice but to rely on her fossil-finding skills to support her family.
The first lesson Mary Anning learned was that although she could dig for fossils almost anywhere, the most transformative discoveries unfolded slowly over time. Mary used to discover approximatelly one sellable or study-worthy fossil per week, yet from these, she could only cumulate 10 major paleontological breakthroughs during her lifetime. Thus, the key to save time when unearthing insights is not merely knowing where to dig first but knowing where to dig deeper. In paleontology, you can’t predict exactly where the next fossil will be. You can only guess based on the geology, previous finds, erosion patterns, and local knowledge. However, once you spot something like a bone or a pattern in the rock, you need to know systematically where and carefully how to dig deeper to extract the full skeleton or preserve a specimen without damaging it.
It’s the same in exploratory analysis. Digging for insights where others see only noise is also time-consuming. Insights do not come neatly packaged. Data must first be located, extracted, cleaned and then interpreted. The most valuable information is often buried hidden within messy datasets, overlooked metrics, or unexpected correlations. Therefore, to save time when you explore a dataset, start with broad questions or hypotheses: these are your “guesses” about where insights might be hidden. Learn how to spot a correlation, an anomaly, or a pattern; this will guide you on how to refine these initial findings. Just as Mary Anning meticulously recorded the details of her fossil finds, including their stratigraphic locations, documenting the context and location of previous data findings can help you recognize patterns and seek similar ones in new data sets. This method not only aids in building a more comprehensive understanding of the data but also enhances the efficiency and accuracy of ongoing analyses.
Once you have established a foundation with initial insights, it is crucial to delve deeper with targeted questions and employ appropriate statistical tools and models to unearth and thoroughly understand the deeper meanings. Just as Mary Anning pioneered new techniques for extracting and preserving fossils without causing damage and thereby set the stage for many modern paleontological methods, analysts are encouraged to develop, refine, and pioneer innovative techniques in data handling and analysis. Anning’s process didn’t rely on pure intuition. Instead, it required a deep understanding of the geological cliffs _ aka data _ and a disciplined approach to digging _ aka analysis. By embracing her principles, data analysts can optimize their time and enhance the quality of their discoveries, ensuring that most “excavation” of data leads to meaningful and impactful insights.
2. Beyond Observation
At just 12 years old, Mary Anning made her first significant paleontological discovery: the first complete ichthyosaur skeleton ever found. While her brother initially discovered the skull, it was Mary who meticulously excavated the entire 17-foot-long skeleton. This groundbreaking find was sold for £23, equivalent to about USD 1,870 today. When displayed in London, the fossil caused a sensation: that’s the skeleton on the blog post picture. Mary’s contributions to paleontology continued to be significant. In 1823, she discovered the first complete plesiosaurus skeleton, enhancing scientific understanding of marine reptiles; in 1828, she unearthed the first British pterosaur fossil, providing key insights into the diversity of prehistoric flying reptiles this time. Finally, in 1829, she found a fossil fish, Squaloraja, notable for its intermediate characteristics between sharks and rays, further challenging existing perceptions of evolutionary biology.
Mary Anning was far more than a mere fossil collector. While discovering fossils was significant, comprehending their implications was another challenge altogether. She considered that each new puzzle piece of a skeleton discovered was not only helping her reconstruct creatures that had never been seen before but mostly rectontruct the past. She identified anatomical similarities between species and built models of prehistoric ecosystems that proved that species existed and went extinct long before biblical accounts of creation allowed. Her discoveries laid the groundwork for evolutionary biology, decades before Darwin’s On the Origin of Species was published. Sound familiar? Just like Mary Anning pieced together prehistoric creatures to change our understanding of the world, data analysts piece together insights from fragmented information. And raw data is just the beginning as a spreadsheet full of numbers is useless until it’s translated into something actionable.
So, how do we piece together insights from data? One of Mary Anning’s greatest strengths was her ability to see what others missed through simple fossil observation. She did so by actually adhering to a specific protocol consisting in carefully reviewing and recording the layers of rock in which they were found, the positions of the fossils, and their surrounding environment. This meticulous attention to context allowed her to make more accurate inferences about the age and environment of the fossils. Likewise in data analytics, whether it’s identifying customer behaviors, forecasting sales trends, or optimizing marketing strategies, true insights are derived from understanding the broader context hidden within the data. The best data analysts don’t merely scrutinize individual data points; they first consider the potential biaise rising from the sources of the data collected and the external factors affecting the data. Only then they actively search for patterns, correlations, anomalies, and trends that others might miss.
Finally, the culmination of this process is storytelling. Anning often had to educate her contemporaries about her findings, many of whom were skeptical at first. For instance, instead of merely presenting the ichthyosaur skeleton she discovered, Anning arranged it in a manner that depicted the creature in life, using her understanding of its anatomy and environment. This presentation not only made it easier for visitors to visualize the living animal but also provided a narrative context that explained its significance in the history of life on Earth. The real value of data analysis lies not only in uncovering insights but also in how effectively you communicate these findings. Crafting a compelling narrative that shifts perspectives and influences decision-making is crucial. This involves framing the data in a way that highlights its relevance and impact, persuading stakeholders to take informed action based on the insights provided.
3. A Legacy of Resilience
Mary Anning’s contributions to paleontology were nothing short of revolutionary, yet her work went overshadowed by the constraints of her social standing. As a working-class woman during the 19th century, she was barred from joining the Geological Society of London. Undeterred by these professional slights, Anning was self-taught in anatomy and geology, avidly read scientific literature, and built a reputation so formidable that the geological community could not ignore her expertise. However, even with this recognition, and despite her key role in numerous scientific discoveries, her contributions were not credited in scientific publications. Her only known written work was a letter published in The Magazine of Natural History in 1839, in which she just corrected the misidentification of a newly discovered fossil.
Anning confided to a friend, expressing her frustration: “The world has used me ill… These men of learning have sucked my brains, and made a great deal of publishing works of which I furnished the contents, while I derived none of the advantages.” Financial struggles also plagued her; she had no stable income, and during economic downturns, her fossil sales severely declined. By 1830, her financial situation had become so dire that she considered selling her furniture to pay her rent. In a show of support, Lieutenant-Colonel Thomas Birch, a long-time fossil collector, auctioned off his collection to provide her with financial relief.
Despite her contributions, it took decades for the scientific community to acknowledge her fully. The Geological Society of London, which had denied her membership during her lifetime, only published her obituary in 1847, a gesture filled with irony. It was not until 167 years after her death that she was honored with a species named after her, Ichthyosaurus anningae. Today, Mary Anning’s legacy is firmly established. She is celebrated as one of the most influential paleontologists in history. The Royal Society has recognized her as one of the ten most influential British women in science, and the Natural History Museum in Britain hails her as the greatest fossil hunter ever known. Her life and work continue to inspire and challenge our understanding of the contributions women have made to science.
Like Anning, data analysts often operate behind the scenes, shaping strategies, guiding decisions, and providing critical insights without always receiving the recognition they deserve. As a result, they learn to let their data speak louder than tradition. The true impact of their work is not measured in immediate accolades but in the long-term value it adds to decision-making and organizational progress. When Mary Anning discovered the first complete skeleton of a plesiosaur, she sent her findings to leading scientists in London, who predominantly dismissed them outright. In fact, Georges Cuvier, one of the most respected anatomists of the time, accused her of assembling the skeleton incorrectly, essentially suggesting it was a hoax. But Mary stood by her work. She had carefully documented the excavation site and preserved the fossil’s original structure. When Cuvier eventually reviewed her drawings and others confirmed the authenticity of the specimen, he admitted Anning was right all along.
Recognition arrives especially late when challenging the status quo, as evidenced by Mary Anning’s experiences. Data analysts often face significant challenges when their findings clash with existing assumptions, biases, or entrenched business strategies, especially when revealing uncomfortable truths. These challenges can involve demonstrating that a purportedly successful marketing campaign is actually underperforming, exposing operational inefficiencies, or challenging long-standing business models. However, unlike in Anning’s time, we now have the ability and the responsibility to change the passive dynamic. Mary Anning’s story should not teach us to wait patiently for recognition; rather, it should inspire us to assertively voice our findings, advocate for our evidence, demonstrate our impact, and secure our rightful place in the discourse, even when it leads to inconvenient conclusions.
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If you’re interested in reading Shelley Emling’s work, her book is titled ‘Mary Anning The Fossil Hunter: Dinosaurs, Evolution, and the Woman Whose Discoveries Changed the World’.