The data scientist is one of today’s most sought-after roles in business, but it’s often unclear what this role really involves, how it can work with the rest of our business functions, and how it best contributes to the work of our teams.
In this course, we describe more than the role of data science in our organizations. We go beyond that to look at how data science interacts with all the other parts of the business it touches. For example, how do we provision data, tools, and services for data science? How do we test and integrate the work of advanced analytics?
We will look at how to support data science effectively, taking account of what IT, business management, and even HR have to know in order to hire, retain, and get the best out of data science in the enterprise.
We’ll also look at the role of automated data science applications and how far you can go with what some analysts have described controversially as “citizen data scientists”—business users armed with a little knowledge and powerful tools.
You Will Learn
- What a data scientist is
- How you can hire and retain data science talent in today’s competitive market
- Why you perhaps do not need to hire a data scientist … yet
- What the role of the data engineer is
- How IT supports and provisions data science capabilities
- How business management should work with data science teams for maximum impact
- Business leaders looking to develop data science capabilities in their organization
- Data analysts and data scientists who need to work and communicate with business users
- IT leaders investing in platforms, tools, and training in analytics and machine learning
- BI and analytics architects designing and developing data science capabilities