This panel of data science experts at Stanford University were brought together to chat about the future of data science. This panel opened its discussion by highlighting one of the biggest achievements in the data science field. This achievement is in the million-fold reduction of the cost of analysis of the human genome. Research studies that once cost billions of dollars to implement now cost merely thousands of dollars. The benefit of this achievement is leading to drug companies developing an ability to complete their drug development and research with more analytical practices and less of ones that are empirical in nature (ie. putting the mouse at risk).
The panel goes on to discuss what makes a data scientist. A data scientist must be strong in mathematics, science, and analytical techniques. In my mind, a new data scientist is going to learn from writing procedural programs that support the traditional ETL process, but an advanced data scientist is going to be involved with automating the analytical process via machine learning as well as the development of new algorithms critical to the processing of unstructured data. I really took interest in the panel discussion on what the higher ed industry can do to produce tomorrow’s data scientists. The panel discussed how increasingly important it is to learn by actually doing this work. You can’t write a computer program by reading a book. You have to actually do this work in order to learn it. Likewise, you can read all about ETL, but you can’t imagine how the work gets done until you do actually do the work. The panel suggested that future class curriculum will have to be modified in order to promote advanced data science skills. Students will need labs that are necessary to complete hands-on work. Education will be most helpful if becomes more project-based as in the real world. Future courses need to have informative data sets, analytical goals, and real-world results which will stimulate student interest in this field. It is further noted that doctors aren’t just expected to be doctors anymore. They are increasingly exposed to analytical techniques, conclusions, and justifications for applied medical practices. So much so that doctors and nurses need more exposure in the data analytics field in their educational training and professional development. It is now interesting to observe why this field is being introduced to all of us in this class as tomorrow’s business managers. Don’t write-off your studies in this class. We need these skills in the real world. We once thought we would never need algebra, yet that science is an important part of our everyday life. If you have 37 cents in your pocket and want to know how much you need in order to possess a dollar … surprise … you are doing algebra. Welcome to the field of data science! In the next decade, all business managers are going to be scrambling to acquire these skills!