Do all data scientists think alike? Or are some of the world’s brightest data minds up for a bit of debate?
The topic of discussion? Popular questions about data science that have been searched online. Is data science a fad? Is data science computer science? Only a true data scientist would know. There was even a mention of one of the most unique job titles of all time, Chief Electricity Officer. We captured some of the best responses below.
Watch the full video above to hear the rest of Janet and Kirk’s insights!
POPULAR SEARCH: IS DATA SCIENCE COMPUTER SCIENCE?
KIRK: I believe that they’re absolutely distinct fields. You might say data science is a subset of computer science. Data science includes computer science, but it also includes traditional science modeling, creative hypothesis generation [and] statistics. So there’s a lot of other things.
JANET: I’d like to think of computer science as the foundation of data science. When you think of computer science, you think about programming, scale and implementation….. You need to be able to implement these large machine learning and AI systems in production.
POPULAR SEARCH: DATA SCIENCE AS A SERVICE
JANET: I think that data science will eventually be a service where you serve your users with the different models that they need to do their job. The people actually building the data models are going to be very different than the people who are actually going to use the models. The user plays a role in calibrating the learning and optimizing of results.
KIRK: I think that data science as a service might be realistic if what you’re talking about is a model as a service, or data access, or a prediction from data as a service. I like what Janet said about the idea that as a service with a little “s” not capital “S”. The data scientist has to serve a community, serve a stakeholder, and provide a business value.
POPULAR SEARCH: DATA SCIENCE NEXT BIG THING
KIRK: This field is evolving so rapidly! The next big thing really is the integration of contextual information and data from different sensors into models that help us understand why this person or process behaved this way. I guess you would just call that cognitive data science.
JANET: I feel like the next big thing along with what Kirk said about contextual data is about major infrastructure changes within big companies. Seamless, open, flexible architectures that can tap into the data that comes from your sensors. You need machine learning to live on those flexible architectures and then learning can happen in a continuous manner.
Thanks to Janet George and Dr. Kirk Borne for a fun and informative conversation. As it turns out, data scientists do (mostly) agree on data science!