Exploring the Skills Needed by the Data Science / Analytics Professional
Kirk Paul Lafler
As 2.5 quintillion bytes (1 with 18 zeros) of new data are created each and every day, the age of big data has taken on new meaning with a renewed sense of urgency to prepare students, young professionals, and other workers across job functions for todays and tomorrows analytics-roles along with the necessary analytical skills to tackle growing data demands. With the number of organizations embracing Data Science / Analytics skills and tools, organizations like LinkedIn, a leading professional networking and employment-oriented website and app, found that Data Scientists saw a 56% increase in the US job market in 2018. To keep up with the huge demand for analytics talent in 2019 and beyond, many colleges, Universities, and training organizations offer comprehensive Data Science / Analytics degrees and certificate programs to fulfill the increasing demand for analytical skills. This presentation explores the skills needed by the Data Science / Analytics professional including critical thinking; statistical programming languages such as SAS, R or Python; Structured Query Language (SQL); Microsoft Excel; and data visualization.
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