A university degree: A strong educational background is needed for developing and absorbing the cross-disciplinary knowledge that Data Science professionals need. A bachelor’s degree in statistics, mathematics, econometrics or related fields will do the job.
R programming skills: Knowing R programming is essential because R is cut out for statistical analysis done in data science. Learning R becomes easier if one knows SPSS. Good certification programs like ABDA / SBDA include this in their curricula.
Coding skills: Python is the most common coding language deployed in data science, though Java, Perl, and C/C++ too undoubtedly have wide circulation. Good certification programs like ABDA/SBDA include this in their curricula.
Platform knowledge: Knowing Hadoop and cloud technologies is a strong must because data analysts must know the tools of sharing vast amounts of streaming data, and also techniques of data exploration, data filtration, data sampling, summarization and data visualization. Good certification programs like ABDA/SBDA include this in their curricula.
Knowing data visualization tools: Data analysts must be able to visualize data using data visualization tools such as ggplot, d3.js and Matplottlib, and Tableau. Good certification programs like ABDA/SBDA include this in their curricula.