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.
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.
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. .