This course covers a guide to automating ETL by reviewing each step and how this can be achieved. This course is designed for anyone who works in the data field - from employees to C-suite executives. With the demand for ETL developers increasing (per the Bureau of Labor Statisticsand the opportunity to become a data provider (for business owners), I highlight methods and architecture to minimize the work that must be done for ETL, so that you can spend more time working on enhancing skills.

This course covers:

• Understanding the extract process and constructing architecture to automate it.

• Understanding the load process, when change is necessary with loading, and how to automate it.

• Understanding different issues we may face in transform, how to minimize re-facing them with re-usable solutions.

• Understanding advanced techniques in ETL, the theory behind these, and applications with them.

• Completing code challenges in each of the ETL steps to help you learn as you do.

• Reviewing case studies of applied ETL techniques, especially useful for freelancers adding credibility to their business.

• Optional course tools of your choice:SQL Server, SSIS, PowerShell, MongoDB, Apache Spark.

To provide maximum learning for students wanting to master ETL skills, whether for business opportunity or employment, the course provides the following material:

• New content posted every year since this course began which offer students a look into the new challenges faced by ETLdevelopers.

• Q&A responses within 48 hours for students who need assistance along with ongoing discussions that students may find helpful.

• Tri-annual bonus material for long-term and successful students in this course based on several metrics provided by Udemy. Technology always changes which is why this course continues to be updated and built with rewards for long time students.

• Focused video lectures with demonstrations of ETL processes in action, the code/script used to make the process occur, and no distracting facial or background movements.

• Dynamic syllabus with extra content, such as links to articles and videosto enhance and increase your learning, as well as links to specific recruiters in desperate need for ETL developers (students wanting to become employees) and ways to uncover possible data providing opportunities for business owners.

• Scripts/code that are used in the video lectures, as well as additional tools that students can learn as they construct their own ETL architecture.

• Course material that we use in the course, such as files we import during the series.

• Course projects that you complete as well as your own project to develop.

• Feedback session for students who meet the requirements where you practice answering questions and presenting your own project.

Understanding, manipulating and transforming data will only become more important in the future. Those who can master this through automation will have an advantage over all their competition because when we see the results of our measurement, only then can we make the appropriate changes; this course shows you how to automate those steps.