Shubham Kumar on LinkedIn: #part1 #databricks #azuredatabricks #linkdinlearning #dataanalyst… (2024)

Shubham Kumar

PA@Cognizant | 4x Azure| 1x AWS| 1x Informatica| 1x GCP| 1x Databricks| 1x Oracle Cloud Certified

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#Part1🚀Let's Discover Databricks : Sharing some key Databricks terms to give an overview of the different points that will use when running Databricks environmeent:🔆Workspace: This is the central place that will allow you to organize all the work that’s being done. You can think of it as a ‘folder’ structure where you can save Notebooks and Libraries that you want to operate on and manipulate data with, and then share them securely with other users. Workspace is not meant for storing data; data should be stored in the data storage.🔆Notebooks: This is a set of any number of cells that allow you to execute commands with a programming language, such as Scala, Python, R or SQL; you can specify the language when you open a cell at the top of the Notebook. Here you can also create a dashboard that allows the output of the code to be shared rather than the code itself, and they can be scheduled as jobs for running pipelines, updating models or dashboards.🔆Libraries: Librariesare the plugins of Databricks, providing additional functionality. Whether you’re using a data manipulation package in Python or a machine learning library in Scala, libraries can be installed on clusters to enhance your code’s capabilities.🔆Tables: This is where the structured data is stored that you and your team will use for analysis. They can live in cloud storage or in the cluster that’s being used or store them in memory for faster processing of the data.🔆Clusters: Clustersprovide the computational horsepower needed to analyze data. Customizable based on your needs, you can configure clusters by specifying the type of machines to use, autoscaling options, and more. Clusters can be controlled via access policies using Active Directory integration.🔆Jobs: In Databricks,Jobsare scheduled or triggered tasks that are run on Databricks clusters. These can be notebook workflows or JARs.#databricks#azuredatabricks#LinkdInLearning#dataanalyst#dataengineer

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Shubham Kumar on LinkedIn: #part1 #databricks #azuredatabricks #linkdinlearning #dataanalyst… (35)

Shubham Kumar on LinkedIn: #part1 #databricks #azuredatabricks #linkdinlearning #dataanalyst… (36)

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Shubham Kumar on LinkedIn: #part1 #databricks #azuredatabricks #linkdinlearning #dataanalyst… (2024)
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