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Gorgoras/README.md

Hola!! 👋

Welcome to my profile! :D My name is Martin Zurita and I'm an Azure Data Solutions Architect.

I have previous experience working as a dev, Bi consultant and some Data Science, but Data Engineering is where I'm most comfortable at and what I love to do. I'm currently designing data architectures based on business requirements and leading a small (but powerfull!) team at the company I'm working at. I am passionate about everything that involves data movement, cleaning, ETL processes, orchestration, integration and automation of data coming from different sources.

More about me:

  • 🌱 Always learning something new on Azure Azure, Python Python and DatabricksDataBricks!! I have some useful repos and gists (and some not so useful), so feel free to use anything you find here.

  • Azure Certified Data Engineer and Administrator! https://www.credly.com/users/martin-zurita

Data-Eng Data-Admin

Pinned Loading

  1. AzureTableStorage-Api AzureTableStorage-Api Public

    Azure Functions Python - Operations on Azure Table Storage

    Python 2

  2. PandasAzureTables PandasAzureTables Public

    This is a simple library that makes it easy to get a Pandas DataFrame from a table in Azure Table Storage (Azure Data Lake's Table service)

    Python

  3. Flask-Azure-Wrapper Flask-Azure-Wrapper Public

    Just an excuse to learn flask framework, and save time at work easily creating the most common Azure resources.

    Python

  4. Call ADF pipeline with parameters, a... Call ADF pipeline with parameters, authenticating with a user or with a service principal.
    1 
    from azure.mgmt.datafactory import DataFactoryManagementClient
    2 
    from azure.common.credentials import UserPassCredentials #To login with user and pass, use this.
    3 
    from azure.common.credentials import ServicePrincipalCredentials #To login with service principal (appid and client secret) use this
    4 
    
              
    
              
    
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    subscription_id = "subsID"
    
              
    
          
    
    
    
  
    

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        Check for Datasets not being used in...  Check for Datasets not being used in any Pipeline in Azure Data Factory. Just clone the repo, then set repo_path, ADF name, and run!      
    

          
    
              
    
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    import os
    
              
    
              
    
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    # set repo location and ADF name
    
              
    
              
    
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    repo_path = "D:/Work/Python/Azure"
    
              
    
              
    
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    dataFactory_name = "Highwayman-ADFv2"
    
              
    
          
    
    
    
  
    

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          AzTableStorage-FastApi  AzTableStorage-FastApi          Public
        
    
      
    


      
    
        
      
    

      
    
          
  
  Python


      
    
    
    
  
    

    7.