
Explore data architecture as the blueprint for collecting, storing, securing, and using data, covering data integration, storage strategies, rbac, compliance, pipelines, data quality, and trade-offs between cost, speed, and security.
Learn how data lakes store raw data at scale for analytics and machine learning, while data warehouses offer structured, fast queries for business intelligence, and data marts serve department-specific needs.
Explore the modern data stack as a cloud-based, consumption-based philosophy guiding tool choices for data pipelines, highlighting ELT over ETL, open-source bias, and component-based architectures versus turnkey solutions.
Connect data from emails, databases, and external services into a data warehouse. Enforce standardized, consistent data flow that fails loudly and stops dependent processes when issues arise.
Explore relational databases, where data rests in tables of rows and columns; learn primary keys and foreign keys, and how SQL enables analysis.
Explore document databases, a flexible NoSQL style that stores JSON-like documents with schemaless structure, enabling fast development and horizontal scaling—yet limiting complex analytics without a relational layer.
Master shell scripting basics for data engineers to interact with the terminal, navigate remote systems with pwd, ls, cd, mkdir, and use ssh, scp, and ssh keys for AWS access.
Explore cron, the time-based job scheduler essential in data engineering, and learn to define schedules with five fields, where star means all and star slash 15 specifies intervals.
Explore containerization with Docker to encapsulate applications and dependencies into portable containers that run identically across environments, enabling isolation and simplified deployment in data engineering and ci cd workflows.
Explore conceptual, logical, and physical data models and learn how data engineers translate business processes into scalable database designs, including entities, keys, and ERDs.
Identify direct and indirect PII and apply data minimization, encryption at rest and in transit, and strict access controls. Emphasize transparency and training to prevent PII leakage with real-world examples.
Do you want to find out if Data Engineering is the right career path for you?
Are you interested in exploring one of the hottest tech professions?
If that’s the case, then our Intro to Data Engineering course is the perfect fit for you. Learn data engineering from course instructor Shashank Kalanithi, who has rich experience in the data and tech field. He has held roles as a data analyst, data scientist, data engineer, and currently works as a software engineer at Meta. Shashank is passionate about teaching and is eager to pass on his experience to you. His engaging teaching style combined with his notable professional experience make him the perfect tutor for you.
But what does a data engineer do? A data engineer designs, builds, and maintains systems for collecting, storing, and analyzing data.
Our data engineering course is perfect for people who are looking into a career in data engineering, as well as for those who have already landed a data engineering job but are still in the early days of their journey.
This the perfect course for data newcomers:
Be able to determine if data engineering is a career path that interests you
Understand the difference between common roles: data analyst vs data scientist vs data engineer vs software engineer (note: data engineering skills allow you to transition to any of the other roles as you advance in your career)
Learn fundamental data engineering concepts, how to become a data engineer, and how to land your first job
This the perfect course for entry level data engineers:
Gain a big picture understanding of the data engineering field and its requirements
Benefit from Shashank's years of experience and gain valuable insights to excel in your job
Understand the different paths you can take in your career progression
Discover methods to enhance data engineering processes within your company
What’s included in our data engineer training?
Intro to Data Engineering begins with an overview of the data engineering career path. You will learn about the data engineering role, the technical skills needed on the job, and the different potential paths for career development.
Then, you will learn about data architecture—a critical topic in data engineering. This field involves creating a structured framework for managing data. You'll also explore data orchestration, which is the automation of the flow and processing of data across different systems.
Our data engineering course also covers relational databases, non-relational databases, and the software engineering skills required for data engineering. You will learn about crucial data engineering tools and frameworks like SQL, NoSQL, Python, APIs, Version Control, Docker and Containerization, Hadoop, Spark, Kafka, and more. Finally, Shashank will wrap up the Intro to Data Engineering course with insights on important aspects like data security and privacy.
We hope you are very excited about this course! Click "Buy Now" and start your data engineering journey today!