A data scientist is a fancy job title alright. But what is the depth of understanding that every company has, on the everyday data they acquire from the various data tools?
Read more as doodleblue extrapolates on the importance of knowing your customers with numbers.
AirBnB Teaches Data Science
Data University is AirBnB’s effort to make its workforce data literate.
Online courses were not providing tailor made courses so AirBnB went ahead and created their own bunch of courses with three levels of instruction for varying employee strata.
Jeff Feng, product manager on the analytics and experimentation team wishes to establish three best practices:
Design an accessible curriculum for everyone
Work with leadership across the company to master the literacy expectations
Find success measurement parameters.
Why Data Science?
Regardless of whether the company wants to conduct a statistical analysis or require the services, it is imperative to understand the nature and potential of the data that the company is dealing with.
In most of the cases, organizations go for a recommender system, that analyses the demographics and purchase trends but ultimately the real power comes when this data is interpreted and followed to improve discount deals, marketing or even the user experience.
In both cases a data strategy can save the day! No organization can get it’s data strategy on point at it’s initial stages itself and it is reason enough to consider it as an integral plan of product/service roadmap and business plan as well.
We at doodleblue believe that the ability to design a well researched data strategy is what distinguishes a quality data scientist from someone who is a data analyser.
Experience, presence of mind, research on case studies and a generous flow of imagination make a worthy data scientist who is well versed with reading customer behaviour from numbers and stats!