Just a few weeks ago (August 06, 2017), we organized a tech meetup in Hungary. The reason why we organized this event was so simple: there had never been such an event in the city, and the topic was so innovative. The main purpose was to ensure a place where people who were interested in data science and innovation could meet and discuss their problems and share their experience. Therefore, we decided to hold a meetup and, with this event, contribute to the scientific life of the region.
We can describe the event in two words: innovation and data science. However, what does data science mean? According to Wikipedia: “Data science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.” As we can see, it is a very complex and modern field of science where practitioners need knowledge of programming, data visualization, and statistics. Many scientists said it has a bright future and could be one of the most popular professions. As the Harvard Business Review called it, it is:
„The Sexiest Job of the 21st Century”
One of our colleagues gave a presentation about data science, focusing on the differences between correlation and causation. The first part of the speech was about the data science in general so that everybody could understand how it works and what we can use it for.
In the second part, we dissected the problem of correlation and causation. We emphasize the clarification of their definitions, because, most of the time, correlation and causation are mistaken. In a few words, correlation shows the mutual relationship between two or more factors. Contrarily, causation reveals the relationship between cause and effect.Here is a short example:
- Correlation: “The more firefighters that are sent out to a fire, the higher the value of the damage.” This is a correlation because the number of the firefighters doesn’t cause more damage.But the bigger is a fire the higher is the value of items damaged is a causation already because the size of the fire influences the value of items damaged.
- Causation: “The bigger the fire, the higher the value of the damage.” This is a causation because the size of the fire influences the number of items damaged.
At the end, our CEO was involved in a round-table discussion where he answered the audience’s questions, provided technical advice to the beginner startups, and acquainted them with AnswerMiner.
We can say it was a successful initiation to wake up minds about the field of data science and demonstrate that we can still trust numbers. More than 40 people – both young and old- participated in the event. We believe that these kinds of meetups and workshops must take place frequently to warrant the opportunity to get the new and innovative information.