An effective global leader is one who has the ability to master international business issues, set direction, effectively lead people from different cultures and nations, and align global resources.
In this course, you will learn about the various components of a modern data ecosystem and the role Data Analysts, Data Scientists, and Data Engineers play in this ecosystem. You will gain an understanding of data structures, file formats, sources of data, and data repositories. You will understand what Big Data is and the features and uses of some of the Big Data processing tools. This course will introduce you to the key tasks a Data Analyst performs in a typical day. This includes how they identify, gather, wrangle, mine and analyze data, and finally communicate their findings to different stakeholders impactfully. You will be introduced to some of the tools Data Analysts use for each of these tasks.
What Will You Learn
Explain what Data Analytics is and the key steps in the Data Analytics process
Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
Describe the different types of data structures, file formats, and sources of data
Explain the use for different types of data repositories, the ETL process, and Big Data platforms
Describe the process and tools for gathering data, wrangling data, mining and analyzing data, and visualizing data
List the different career opportunities in Data Analysis and resources for getting skilled in this domain
Buy Now Global Leadership and Human Resource Management
Importance and applications of data analytics in various domains.
Basic terminology and concepts in data analytics.
Introduction to Statistical Analysis
Key statistical concepts for data analysis. Descriptive statistics: measures of central tendency and variability. Introduction to probability and distributions.
Data Visualization
Importance of data visualization in data analytics. Principles of effective data visualization. Introduction to visualization tools and techniques.
The course will cover data import and export, data cleaning, data visualization, statistical analysis, machine learning basics, and real-world projects for hands-on experience.
Data analysts are in demand across various industries, including finance, healthcare, marketing, and technology, with opportunities for career growth and specialization.
Yes, most data analytics courses include real-world projects and case studies where you can apply your learned skills to practical scenarios using real datasets.
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