Thoughts from Introduction to Data Science – Melbourne – June 2017
A team in Melbourne recently completed our Introduction to Data Science course with Altis’ Head of Data Science – Isaac Reyes. In this interview Richard Marris, a consultant from our Altis Canberra office, shares some of his takeaways on how analytics is adding to the skills and techniques that a modern analyst needs.
What is a data scientist and what do they do?
A data scientist cleans, massages and manipulates data sets (of all sizes) to perform analysis and apply statistical models. They generate insights from the data to help solve business questions. Sometimes described as part statistician, part data wrangler, part story teller – what a data scientist actually does, is use tools and techniques to turn a raw data set into something meaningful and valuable that offers new or different insights.
Where does data science fit with traditional Business Intelligence?
Data science sits happily side-by-side with more traditional business intelligence. Business intelligence enables access to and analysis of information to improve decision-making, typically with data visualisations. Data science builds on this by adding predictive and prescriptive analysis, to offer a deeper understanding of your data and the ability to ask (and answer) even more questions about your data. It is another key tool in the kit of a data practitioner.
Do you need a maths or stats degree to do analytics?
No, although a solid grounding in maths/statistics definitely helps your understanding and choice of which model to use. Many tools today offer an analytics plug-in which not only provides a user-friendly interface, but additionally guides the user through the different applications of models. They are quick to setup and use. Whether you create your model in R in a development environment, use a drag and drop tool like Azure ML Studio or another of the many options out there, it is becoming easier by the day to learn and apply data science skills. Of course, it’s still up to the end user to interpret the results and to present the analysis in a meaningful way that tells a story.
How will this course help you deliver tangible business outcomes in what you do?
I’m taking this back to my current project to correlate any data I can get my hands on. I’m going to include in my data profiling a quick regression analysis to see what interesting results may come out.
Any other thoughts on the course?
It was fantastic. Issac is a great teacher and he adapted his teaching to the level of the group, while still being happy to run a maths proof during the break when someone asked.
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