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Industry
e-commerce
general
Skills
approach
data-storage
data-quality
data-wrangling
batch-etl
data-governance
data-understanding
Tools
databricks
spark
python
Learning Objectives
Basic Knowledge of Data Stores such as Data Lake & Database
Understand why PySpark is better than Python for handling large-scale data processing and building efficient data pipelines.
Overview
This masterclass highlights the challenges of managing data from multiple sources like data lakes, databases, and APIs, resulting in a lack of a single source of truth and complex transformations. Python struggles with scalability for these tasks due to its single-threaded nature. The module introduces PySpark as an efficient alternative, leveraging distributed computing for scalable, fast data processing, ensuring consistency and a unified data foundation.
Prerequisites
- Understand the fundamentals of ELT (Extract, Load, Transform)
- Basic Knowledge of Python & Pyspark
- Familiarity with Distributed Computing Concepts