A traditional data science department is comprised of Data Scientists, Data Engineers and Infrastructure Engineers. This model has a drawback that one role is always dependent on other and likely to criticize them for task failures because they didn't do their job well. These conflicts may reflect in the quality of final data product. So, what went wrong? You probably don't have big data. Jeff Magnusson (Director of Algorithms Platform at Stitch Fix) suggested a clever approach of forming a "High Functioning Data Science Department" which involves building an environment which allows autonomy, ownership, and focus for everyone involved yet at the same time clearly distinguishing the roles of Data Scientists and Data Engineers. Data scientist can't suddenly become talented engineers nor is that engineers will be ignorant of all business logic, the partnership is inherent to the success of this model. You can read more at: http://multithreaded.stitchfix.com/blog/2016/03/16/engineers-shouldnt-write-etl/

Need for Chief Data Officer (CDO) in boardrooms has increased now days. Importance of CDO is same as that of big data in companies, as a person in charge of data team. There has been increase in number of companies who are employing CDOs. At present 43% of executives reported that their firm had appointed CDO, while two years back it was only about 19%. During financial crises in 2008 many companies lost their significant amount of money after their data had been shown completely wrong. That gives rise to Chief Data Officer, a person that can be held responsible for validity of data. He can protect businesses from loss due to crises and also to help appease law makers who were going to require change within reporting and storage of data.  Read more at:

https://channels.theinnovationenterprise.com/articles/the-evolution-in-the-cdo-role