Rising along side the relatively new technology of big data is the new job title data scientist.
While not tied exclusively to big data projects, the data scientist role does complement them because of the increased breadth and depth of data being examined, as compared to traditional roles.
So what does a data scientist do?
A data scientist represents an evolution from the business or data analyst role. The formal training is similar, with a solid foundation typically in computer science and applications, modeling, statistics, analytics and math. What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge. Good data scientists will not just address business problems, they will pick the right problems that have the most value to the organization.
The data scientist has to be a part analyst and part artist. Data scientist need to know the math and must have a curious mind and be inquisitive to discover mathematical relationships between different sets of data and trends.
Data scientists must be inquisitive to explore, ask questions & do "what if" analysis, Question existing assumptions and processes A data scientist should be curious to explore and examine data from multiple disparate sources. The data scientist will sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem. A data scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, then recommends ways to apply the data.
Armed with data and analytical results, a top-tier data scientist will then help automate various parts of decision making in organizations and help leaders take better decisions.
While not tied exclusively to big data projects, the data scientist role does complement them because of the increased breadth and depth of data being examined, as compared to traditional roles.
So what does a data scientist do?
A data scientist represents an evolution from the business or data analyst role. The formal training is similar, with a solid foundation typically in computer science and applications, modeling, statistics, analytics and math. What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge. Good data scientists will not just address business problems, they will pick the right problems that have the most value to the organization.
The data scientist has to be a part analyst and part artist. Data scientist need to know the math and must have a curious mind and be inquisitive to discover mathematical relationships between different sets of data and trends.
Data scientists must be inquisitive to explore, ask questions & do "what if" analysis, Question existing assumptions and processes A data scientist should be curious to explore and examine data from multiple disparate sources. The data scientist will sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem. A data scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, then recommends ways to apply the data.
Armed with data and analytical results, a top-tier data scientist will then help automate various parts of decision making in organizations and help leaders take better decisions.
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