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 dataframes, Apache spark data transformation, notebook configuration, spark SQL fundamentals, data handling, and the databricks workspace.
Key Competencies:
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Databricks Dataframes - Ability to handle big data efficiently and provide a high-level API for performing data manipulation and analysis.
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Apache Spark Data Transformation in Databricks - Ability to convert raw data into a more structured format using Apache Spark, a distributed computing framework, in the Databricks environment
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Databricks notebook configuration - Ability to create, run, and share notebooks which in turn is essential for data exploration, analysis, and visualization.
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Spark SQL fundamentals in Databricks - Understanding the usage of Spark SQL, to query and manipulate data in Databricks using SQL/Pyspark commands
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Data Handling - Ability to manage and process data in different formats like CSV, JSON, PARQUET, etc
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Databricks Workspace - Understanding how to navigate and utilize the Databricks Workspace to create and manage notebooks, data objects, jobs, and clusters.