Data Scientist vs Data Analyst | Difference Between Data Scientist And Data Analyst | Simplilearn
This presentation talks about the two most interesting job roles in the field of data science, i.e., data scientist and data analyst. If you are wondering what the differences are between these two job roles, then this video is what you should be watching. Here, you will understand the job descriptions, the responsibilities, the various skills required, the companies hiring, and finally, the salary structure of a data scientist and that of a data analyst. 1. Job description 2. Responsibilities 3. Skill set 4. Salary 5. Companies hiring This Data Analyst Masteru2019s Program in collaboration with IBM will make you an expert in data analytics. In this Data Analytics course, you'll learn analytics tools and techniques, how to work with SQL databases, the languages of R and Python, how to create data visualizations, and how to apply statistics and predictive analytics in a business environment. Why become a Data Analyst? By 2020, the World Economic Forum forecasts that data analysts will be in demand due to increasing data collection and usage. Organizations view data analysis as one of the most crucial future specialties due to the value that can be derived from data. Data is more abundant and accessible than ever in todayu2019s business environment. In fact, 2.5 quintillion bytes of data are created each day. With an ever-increasing skill gap in data analytics, the value of data analysts is continuing to grow, creating a new job, and career advancement opportunities. The facts are that professionals who enter the Data Science field will have their pick of jobs and enjoy lucrative salaries. According to an IBM report, data and analytics jobs are predicted to increase by 15 percent to 2.72 million jobs by 2020, with the most significant demand for data analysts in finance, insurance, and information technology. Data analysts earn an average pay of $67,377 in 2019 according to Glassdoor. Who should take up this course? Aspiring professionals of any educational background with an analytical frame of mind are best suited to pursue the Data Analyst Masteru2019s Program, including: 1. IT professionals 2. Banking and finance professionals 3. Marketing managers 4. Sales professionals 5. Supply chain network managers 6. Beginners in the data analytics domain 7. Students in UG/ PG programs ud83dudc49Learn more at: https://bit.ly/2W87jsK
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