Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Simplilearn
This presentation on Data Analytics for Beginners covers all the basics and the concepts that will help you start learning data analytics. You will understand what data analytics and the need for data analytics. Then, you learn the different process steps in data analytics and the essential tools that are used to perform data analytics. Also, you will see a case study on how Walmart uses data analytics for running its business. Finally, we'll do some hands-on demo using linear regression in R to predict sales for the advertising budget. So, let's get started. 1. What is Data Analytics? 2. Steps involved in Data Analytics 3. Tools used for Data Analytics 4. Data Analytics Applications 5. Companies using Data Analytics 6. Case Study 7. Use Case Demo Why become 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/2x28p0m
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