Last Updated on August 15, 2020
In a previous blog post we looked at the ebook of interviews with data analysts and data scientists put together by Liou, Tao and Lin.
In this blog post we look at the second book in the series titled The Data Analytics Handbook CEOs and Managers.
What are managers looking for in a Data Analyst and a Data Science position, what skills do they require and how do they define and compare these positions within a business?
Top 5 Findings
Like the previous ebook, it opens with the top 5 take aways from the interviews, which were:
- The information revolution is real.
- Data analytics is becoming increasingly accessible.
- Do your own projects to break into the industry.
- Statistics is more important than programming.
- The most important skill is being able to ask the right questions.
I think that last point is quite understated. A word repeated over and over again was curiosity. Interviewees stressed that technical skills like statistics and SQL can be taught, but curiosity and a love of data are innate.
The ebook is 43 pages long and again you will be able to read it very quickly. There are 9 interviewees from 8 companies, specifically:
- Derek Steer from Mode Analytics
- Dean Abbott from Smarter Remarketer
- Tom Wheeler from Cloudera
- Mike Olson from Cloudera
- Rohan Deuskar from Stylitics
- Mary Ellen Gorden from Flurry
- Greg Lamp from Yhat
- Ali Syed from Persontyle
- David Gerster from BigML
My favorite interviews were with Dean Abbott and David Gerster, perhaps because I took the most notes. Below are some key points from my notes taken from across the interviews.
- You can get a long way by counting and summing things, model building can be expensive.
- An analysis that does not turn into a decision in the business is basically a waste of time.
- When working or presenting work focus on the beginning (framing) and end of the problem (recommended actions).
- Data Analysts answer questions with provided data, Data Analysts define the problem and collect the data and deliver answers.
- Think about domains where business decision making is driven by intuition, they are ripe for disruption (sports, fashion, etc.)
Resources and books are not mentioned enough in these interviews. Dean did list off a few books he recommends, which were:
- Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst (Dean’s new book)
- Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
- Handbook of Statistical Analysis and Data Mining Applications
I recommend this quick read to any aspiring data scientists looking for insight from leaders in the industry.