Azure Databricks was launched in 2017 as a result of a collaboration between Microsoft and Databricks, the company founded by the creators of Apache Spark. It was developed to integrate the capabilities of Apache Spark with Azure's cloud services, aiming to provide a unified analytics platform that facilitated big data processing and machine learning tasks.
Azure Databricks
Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services. It provides a collaborative environment for data engineers, data scientists, and business analysts to process data, build machine learning models, and perform big data analytics efficiently.
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About Azure Databricks
Strengths of Azure Databricks include its seamless integration with Azure services, optimized performance for Apache Spark workloads, and collaborative environment for data teams. Weaknesses may involve a learning curve for new users and potential cost considerations for large-scale deployments. Competitors include AWS Glue, Google Cloud Dataproc, and Cloudera Data Platform.
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How to hire a Azure Databricks expert
An Azure Databricks expert must have strong skills in Apache Spark for data processing, proficiency in programming languages such as Python, Scala, or SQL, and experience with Azure cloud services. Knowledge of data engineering and machine learning workflows, as well as familiarity with tools like Azure Data Lake Storage and Azure Synapse Analytics, is also essential.
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