Databricks
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:
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Data Lineage with Unity Catalog - Ability to understand the data flow and dependencies between different data sources using this feature.
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Delta Live Tables - Ability to build and manage reliable batch and streaming data pipelines using this feature.
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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.
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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.
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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.
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Resilient Distributed Datasets (RDDs) - Ability to handle and process large-scale data efficiently and fault-tolerantly using this data structure.