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‎0_Azure/1_AzureData/README.md‎

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Last updated: 2024-11-19
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Last updated: 2025-02-13
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## Content
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- [Data Storage](./0_DataStorage/)
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- [Databases](./1_Databases/)
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- [Azure Databricks](./2_Databricks)
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Azure Data Storage provides scalable, secure, and accessible cloud storage, ideal for big data and analytics, with various storage tiers. It supports a wide range of services and tools. Azure also offers relational and non-relational databases, with built-in management for high availability and performance, catering to different application needs.
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| Area | Category | Service | Overview |
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| ---- | ---- | ---- | ---- |
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| Big Data Analytics | Service | [Azure Databricks](https://azure.microsoft.com/en-us/products/databricks/) | Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure. It provides an interactive workspace for data engineers, data scientists, and business analysts. <br/> <br/> For more information: <br/> [Azure Databricks Overview](https://azure.microsoft.com/en-us/products/databricks/) <br/> [What is Azure Databricks?](https://learn.microsoft.com/en-us/azure/databricks/scenarios/what-is-azure-databricks) <br/> [Azure Databricks Learning documents](https://learn.microsoft.com/en-us/azure/databricks/). |
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| Data Integration | Service | [Azure Data Factory](https://azure.microsoft.com/en-us/products/data-factory/) | Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale. <br/> <br/> For more information: <br/> [Azure Data Factory Overview](https://azure.microsoft.com/en-us/products/data-factory/) <br/> [What is Azure Data Factory?](https://learn.microsoft.com/en-us/azure/data-factory/introduction) <br/> [Azure Data Factory Learning documents](https://learn.microsoft.com/en-us/azure/data-factory/). |
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## Differences between Azure Data Storage and Databases
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Azure Data Storage and Databases both persist data but are optimized for different purposes. Storage provides durable capacity while databases structure data for efficient access. Storage suits long-term file retention while databases enable interactive applications.
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| Durable long-term retention | Temporary persistence tier |
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## DataFrames types:
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Comparative analysis of various types of DataFrames. Each type of DataFrame has its unique features and is suited for different use cases. The table below summarizes the key characteristics and common applications of each type:
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<h3 style="color: #4CAF50;">Total Visitors</h3>
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0_Azure/1_AzureData/2_Databricks/README.md renamed to 0_Azure/2_AzureAnalytics/3_Databricks/README.md

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‎0_Azure/2_AzureAnalytics/README.md‎

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- [Microsoft Fabric](./0_Fabric/README.md)
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- [Azure Synapse Analytics](./1_SynapseAnalytics/README.md)
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- [Azure Event Hubs](./2_EventHubs)
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- [Azure Databricks](./3_Databricks)
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## Wiki
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| Real-time Data Processing | Service | [Azure Stream Analytics](https://azure.microsoft.com/en-us/products/stream-analytics/) | Azure Stream Analytics is a real-time analytics and complex event-processing engine that is designed to analyze and process high volumes of fast streaming data from multiple sources simultaneously. <br/> <br/> For more information: <br/> [Azure Stream Analytics Overview](https://azure.microsoft.com/en-us/products/stream-analytics/) <br/> [What is Azure Stream Analytics?](https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-introduction) <br/> [Azure Stream Analytics Learning documents](https://learn.microsoft.com/en-us/azure/stream-analytics/). |
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| Unified Analytics Platform | Service | [Microsoft Fabric](https://azure.microsoft.com/en-us/blog/introducing-microsoft-fabric-data-analytics-for-the-era-of-ai/) | Microsoft Fabric is an end-to-end, unified analytics platform that integrates technologies like Azure Data Factory, Azure Synapse Analytics, and Power BI into a single product. It covers data movement, processing, ingestion, transformation, real-time event routing, and report building, simplifying analytics requirements for enterprises. <br/> <br/> For more information: <br/> [Microsoft Fabric Overview](https://azure.microsoft.com/en-us/blog/introducing-microsoft-fabric-data-analytics-for-the-era-of-ai/) <br/> [What is Microsoft Fabric?](https://learn.microsoft.com/en-us/fabric/get-started/microsoft-fabric-overview) <br/> [Microsoft Fabric Learning documents](https://learn.microsoft.com/en-us/fabric/). |
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| Real-time Data Streaming | Service | [Azure Event Hubs](./2_EventHubs/) | Azure Event Hubs is a fully managed, real-time data streaming platform that can ingest and process millions of events per second with low latency. It supports multiple protocols, including Apache Kafka, and integrates with various Azure services for building comprehensive data streaming solutions. <br/> <br/> For more information: <br/> [Azure Event Hubs Overview](https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-about) <br/> [What is Azure Event Hubs?](https://learn.microsoft.com/en-us/azure/event-hubs/event-hubs-about) <br/> Azure Event Hubs Learning documents. |
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| Big Data Analytics | Service | [Azure Databricks](https://azure.microsoft.com/en-us/products/databricks/) | Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure. It provides an interactive workspace for data engineers, data scientists, and business analysts. <br/> <br/> For more information: <br/> [Azure Databricks Overview](https://azure.microsoft.com/en-us/products/databricks/) <br/> [What is Azure Databricks?](https://learn.microsoft.com/en-us/azure/databricks/scenarios/what-is-azure-databricks) <br/> [Azure Databricks Learning documents](https://learn.microsoft.com/en-us/azure/databricks/). |
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| Data Integration | Service | [Azure Data Factory](https://azure.microsoft.com/en-us/products/data-factory/) | Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale. <br/> <br/> For more information: <br/> [Azure Data Factory Overview](https://azure.microsoft.com/en-us/products/data-factory/) <br/> [What is Azure Data Factory?](https://learn.microsoft.com/en-us/azure/data-factory/introduction) <br/> [Azure Data Factory Learning documents](https://learn.microsoft.com/en-us/azure/data-factory/). |
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<div align="center">
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<h3 style="color: #4CAF50;">Total Visitors</h3>
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‎0_Azure/3_AzureAI/9_AzureOpenAI/README.md‎

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- **Models Available**: The models available through Azure OpenAI Service include GPT-4, GPT-3.5-Turbo, and Embeddings.
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- **Security and Compliance**: Azure OpenAI Service offers the security and enterprise promise of Azure.
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## Content
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- [Azure OpenAI](#azure-openai)
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- [Content](#content)
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- [Example of Use Cases](#example-of-use-cases)
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- [Text Generation - Azure OpenAI:](#text-generation---azure-openai)
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- [Sentiment Analysis - Azure OpenAI:](#sentiment-analysis---azure-openai)
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- [Language Translation - Azure OpenAI:](#language-translation---azure-openai)
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- [Content Moderation - Azure OpenAI:](#content-moderation---azure-openai)
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- [Speech Recognition - Azure OpenAI:](#speech-recognition---azure-openai)
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- [Demos & Tech Talks](./demos/)
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- [Optimizing Chatbot Efficiency](./demos/1_OptimizingChatbotEfficiency.md)
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<!-- /TOC -->
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<details>
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<summary><b>List of References </b> (Click to expand)</summary>
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- [Azure Open AI resource - Change log](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/openai/Azure.AI.OpenAI/CHANGELOG.md)
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</details>
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<details>
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<summary><b>Table of Content </b> (Click to expand)</summary>
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- [Example of Use Cases](#example-of-use-cases)
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- [Text Generation - Azure OpenAI:](#text-generation---azure-openai)
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- [Sentiment Analysis - Azure OpenAI:](#sentiment-analysis---azure-openai)
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- [Language Translation - Azure OpenAI:](#language-translation---azure-openai)
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- [Content Moderation - Azure OpenAI:](#content-moderation---azure-openai)
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- [Speech Recognition - Azure OpenAI:](#speech-recognition---azure-openai)
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- [Demos & Tech Talks](./demos/)
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- [Optimizing Chatbot Efficiency](./demos/1_OptimizingChatbotEfficiency.md)
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</details>
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## Example of Use Cases
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