Databricks

Advanced

Databricks is a unified data analytics platform designed to help organizations process large amounts of data and perform advanced analytics tasks. It provides a cloud-based platform for data engineering, data science, and analytics, offering a range of tools and services such as data processing, machine learning, and real-time analytics.

This competency includes understanding data lineage, delta live tables, autoloaders, optimization of spark, multi-hop architecture, and RDDs.

Key Competencies:

  1. Data Lineage with Unity Catalog - Ability to understand the data flow and dependencies between different data sources using this feature.

  1. Delta Live Tables - Ability to build and manage reliable batch and streaming data pipelines using this feature.

  1. Autoloaders - Ability to automate the process of loading data from different sources, such as files or databases, into Delta tables, reducing the need for manual configuration and management. 

  1. Optimization of Spark - Ability to improve the performance and efficiency of Apache Spark by optimizing configuration settings, tuning the Spark cluster, and using advanced techniques such as partitioning and caching. 

  2. Multi-hop Architecture (Medillon Architecture) - Understanding this architecture to build complex data pipelines that can process and analyze data across multiple hops, enabling advanced analytics and machine learning. 

  3. Resilient Distributed Datasets (RDDs) - Ability to handle and process large-scale data efficiently and fault-tolerantly using this data structure.