In this course, you will delve into the components comprising a modern data ecosystem and explore the essential roles of Data Analysts, Data Scientists, and Data Engineers within this ecosystem. You will develop a comprehensive understanding of data structures, file formats, data sources, and data repositories. Furthermore, you will gain insights into Big Data, including its defining characteristics and the applications of popular Big Data processing tools.

The course will introduce you to the fundamental tasks performed by Data Analysts on a typical day. This encompasses activities such as data identification, gathering, wrangling, mining, analysis, and effective communication of findings to diverse stakeholders. Throughout the course, you will also become acquainted with the tools commonly employed by Data Analysts for each of these tasks.

You will gain knowledge of relational and non-relational databases, data warehouses, data marts, and data lakes, along with their features and applications. Additionally, you will comprehend the Extract-Transform-Load (ETL) process, which converts raw data into analysis-ready data. The course will also shed light on specific programming languages utilized by data analysts to extract, prepare, and analyze data.

By the conclusion of this course, you will be well-informed about the various career opportunities available in the field of Data Analytics. Moreover, you will gain an understanding of the different learning paths you can embark upon to enter this field successfully.

To reinforce your learning, the course will conclude with practical exercises and a hands-on lab where you can apply your knowledge to perform basic tasks related to data gathering, wrangling, mining, analysis, and visualization.