The training for a data scientist is similar to that of a data analyst. They will have a solid foundation in computer science along with knowledge of applications, modeling, statistics, analytics and maths. A data scientist needs strong business acumen, coupled with the ability to communicate their findings in order to influence how an organisation operates.
How does a data scientist differ from a statistician or BI analyst?
Data scientists work with a mix of Big Data tools that stores or has data. They have a strong technology skill set because they are programmers, and also have very strong math skills, particularly statistics. They also have a strong understanding of business as they work directly with an organisation. A statistician interprets and analyzes statistical information to solve a range of issues. They use graphs, charts and tables of their statistical analysis for reporting their findings. They also develop software applications for graphic analysis and/or statistic modeling. A BI Analyst works with BI tools to perform analysis. They have knowledge of data warehousing and understands how a star schema is modelled. This allows them to perform analysis either through a reporting tool or using SQL to create the information that the business users require. .
The Big Data Science Certified Professional (BDSCP) qualification is a collection of courses concentrated on the fields of Big Data science, analysis, analytics, business intelligence, and technology architecture, as well as design, development, and governance. The curriculum is comprised of a series of courses and formal exams that can be completed to achieve one or more of the following certifications: • Certified Big Data Professional • Certified Big Data Science Professional • Certified Big Data Scientist.