Data Explorer and Data Catalog

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@Eric Starker Hi Eric, my name is Jody Claggett. I'm a Data Engineer working for a healthcare company out of Colorado. We're just in the beginning stages of implementing an Azure Data Lake solution. My team is responsible for data analytics and reporting.

 

What I'd like to understand regarding Azure Data Explorer is just the primary differences between Data Explorer and Data Catalog and what types of use cases I should think about using for each? My understand is that Data Catalog would be exposed to my end users? Is that accurate or is Data Explorer that tool for end users to leverage?

2 Replies

Hi @JodyClaggett985 !

Great question!

Azure Data Explorer is a low latency, high-performance, big data analytics service that provides a fast general purpose interactive analytics data platform.  

Featuring an intuitive query language and powerful ingestion and storage capabilities, ADX is the ideal tool to analyze high volumes of fresh and historical data in the cloud.   

By analyzing structured, semi-structured and unstructured data across time series and leveraging Machine Learning, Azure Data Explorer makes it simple to extract key insights, spotting patterns and trends, and creating forecasting models.  

 

Main use cases for Azure Data Explorer  

  • Log analytics 
  • IoT analytics  
  • Time series analytics   
  • Clickstream and any other form of live source analytics  
  • Text search 
  • Geospatial analytics 
  • Advanced analytics 
  • Exploratory environment for data scientists and business/data analysts 

  

What makes ADX unique? 

  • Data diversity - ability to work with any kind of data: structured, semi-structured (JSON and more) and unstructured (free text).  
  • Ingestion - high velocity (millions of events per second), low-latency (seconds) and linear scale ingestion of raw data. Terabytes of data can be ingested in minutes in a variety of formats and from a variety of data sources. 
  • Query Engine - industry-leading scalable query performance. Petabytes of data can be queried with results returned within milliseconds to seconds 
  • Query Language - Rich and powerful query capabilities, supporting the whole complexity spectrum: from a simple keyword search to the complex time series and behavioral analytics. Simple, yet powerful and productive query language and toolset.  
  • Full analytics toolkit – including advanced analytics, Python and R supportnotebooks integration, native visualizations and dashboards, as well as integration with external visualization and dashboarding services, integrations with the Azure ecosystem for automation, scheduling and orchestration.  

 

ADX includes native tools such as query editor, equipped the best InteliSense in the business and an advanced and powerful results grid, and dashboarding application that can absolutely be leveraged by end users.

 

 

@OlgaGold Thank you, that helps clear up my confusion.