A data scientist analyzes data to help a business gain a competitive edge. A data scientist represents someone who has evolved from a business or data analyst role. The training and education is similar, with a foundation in computer science, mathematics, programming, modeling, or analytics. Data scientist typically have a strong business acumen, and are able to communicate findings to both business and IT users in a way that can influence how an organization approaches challenges.
Data scientists have been described as “part analyst, part artist” by Anjul Bhambhri, vice president of big data products at IBM. He says “a data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization.”
What differentiates a data scientist from a traditional data analyst is the number of sources used to look at the data. A data analyst typically looks at data from a single source, and a data scientist will examine and explore data from multiple sources. He or she does not simply just collect and report data, but also looks at it from many angles and perspectives, determines what it means, and recommends ways in which the data can be applied.
As an interdisciplinary subject, data science draws out information from a broad range of areas including:
- Data mining
- Cloud computing
- Databases and information integration
- Signal processing
- Learning, natural language processing, and information extraction
- Computer vision
- Information retrieval and web information access
- Knowledge discovery in social and information networks
- Information visualization