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Big Data for Data Engineering

Track Course
Advanced
Fully Ready

About the Course

This course introduces big data principles, distributed computing with Apache Spark, and modern architectures like data lakes and lakehouses. It emphasizes using Databricks for large-scale data processing, covers NoSQL and schema-on-read, and explores real-time streaming.

Learning Outcomes

By the end of this course, participants will be able to:

  • Explain the principles of big data and distributed computing, including the role of Apache Spark in processing large-scale datasets.
  • Design and implement data lake and lakehouse architectures using tools such as Azure Data Lake Storage, Delta Lake, and open table formats.
  • Build scalable data processing workflows on Databricks, leveraging Spark for batch and real-time structured data.
  • Integrate NoSQL databases and schema-on-read designs into modern data architectures to support unstructured and semi-structured data at scale.

Curriculum

  • Chapter 1: Big Data Foundations

    Overview:

    In this chapter, learners will understand the principles of big data, distributed systems, and MapReduce concepts, and get introduced to Apache Spark on Databricks.

    Topics:

    • Big data significance and distributed computing concepts
    • Hadoop ecosystem: HDFS, YARN, Hive, HBase, Sqoop, Zookeeper, Kafka, NiFi
    • Introduction to Apache Spark
    • Databricks: workspace setup, Spark cluster creation, DBFS, ADLS integration
    • Labs: Spark DataFrame and Spark SQL exercises
    • Mini Project
  • Chapter 2: Data Lake Architecture

    Overview:

    This chapter covers the design and implementation of data lakes for semi-structured and unstructured data, including NoSQL databases.

    Topics:

    • Advantages of data lakes
    • NoSQL databases: Cosmos DB, MongoDB, Cassandra
    • Unstructured and semi-structured data modeling
    • Schema-on-read strategies
    • Labs: ingest and process unstructured data, ETL in data lakes using Spark, Azure Data Factory
  • Chapter 3: Lakehouse Architecture

    Overview:

    Learners will explore lakehouse concepts and architectures, combining features of data lakes and warehouses.

    Topics:

    • Data lakehouse vs. data warehouse
    • ACID in data lakes
    • Open table formats: Hudi, Iceberg, Delta
    • Key lakehouse attributes: schema-on-read, schema evolution, time travel
    • Structured streaming with Databricks Spark
    • Labs: streaming data ingestion, upserts, deletes, merges, and copy operations in Azure Synapse/Fabric

Tools

Apache Spark, Databricks
Azure (Data Lake Storage, Synapse Analytics, Data Factory)
Delta Lake, Open table formats (Hudi, Iceberg, Delta)
NoSQL databases ( Cosmos DB, MongoDB, Cassandra)
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STUDENT REVIEWS

What our graduates are saying

I had an incredible experience at this data science bootcamp! Coming in with no prior knowledge, I was amazed at how quickly I gained a solid understanding of the field. The curriculum is intensive and hands-on, allowing me to learn real, applicable skills through working on real client projects. The staff are exceptionally supportive and always ready to help. This bootcamp truly transformed my career path, and I couldn’t be more grateful for the knowledge and confidence I’ve gained. Highly recommended for anyone looking to break into data science!

My experience was awesome. I was taught by professional data engineers who shared their insights based on their professional experience. The topics covered are relevant to what employers are looking for and I enjoyed hands-on projects. I learned all the skills I needed to be a data engineer and I got a full-time offer as a data engineer, thanks to the mentors from WecloudData. I highly recommend this program. I was able to land interviews at Amazon, Yelp, CI Financial e.t.c

Deciding to go with WeCloudData was one of the best decisions I made during my career switch. Their Bootcamps are intense but they get you where you need to go. The instructors are amazing and the TAs very knowledgeable. Their client projects taught me a lot even after the bootcamp was done. I was able to land my current job thanks to the skills and training from the course.

I had the pleasure of attending WeCloudData’s Data Fundamentals bootcamp, which was fantastic. The highly qualified instructors used cutting-edge teaching techniques that greatly facilitated understanding the logic of coding and programming. They carefully progressed us from fundamental to more complex subjects, avoiding any feeling of overload. I wholeheartedly endorse this course for anyone hoping to become a data analyst—it’stheonly one you’ll need. The teachers are very outstanding!

This bootcamp provided me with the necessary technical skills and industry knowledge to secure a data job. The instructors are knowledgeable and shared everything they know to help me achieve my goals. The TAs are resourceful and patient answering my questions. The projects in the bootcamp enhanced my knowledge and impressed interviews. This is a wonderful bootcamp if you are looking to either imporve your skills or switch career!

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Common Questions

Find answers to your questions about the Learning Track
  • Standard Courses: Focused, short courses that build foundational or intermediate skills through hands-on exercises, enabling you to apply what you learn immediately.
  • Track Courses: Structured learning paths that guide you from beginner to advanced levels. They include practical projects that integrate multiple tools and workflows, aligned with industry best practices, helping you gain the skills and confidence to tackle real-world challenges.

No. Track Courses are only accessible through the Professional or Unlimited+ subscription plans.

  • Standard Plan gives you access to all Standard Courses.
  • Professional Plan gives you access to both Standard and Track Courses within your chosen domain.
  • Unlimited+ Plan provides full access to all courses — both Standard and Track — across all domains.

 

Yes, all courses are designed to be self-paced. Learn when it fits your schedule.

Each course includes prerequisites if needed. Many Standard Courses are beginner-friendly.

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