The document discusses how businesses need to build a data strategy and modernize their data platforms to harness the power of data from diverse and growing sources. It provides examples of how organizations like healthcare and energy companies are using technologies like machine learning, real-time analytics, and predictive modeling on data from various sources to improve outcomes, predict trends, and drive business decisions. The Microsoft data platform is positioned as helping businesses manage both traditional and new forms of data, gain insights faster, and transform into data-driven organizations through offerings like SQL Server, Azure, Power BI, and the Internet of Things.
Azure SQL Database is a relational database-as-a-service hosted in the Azure cloud that reduces costs by eliminating the need to manage virtual machines, operating systems, or database software. It provides automatic backups, high availability through geo-replication, and the ability to scale performance by changing service tiers. Azure Cosmos DB is a globally distributed, multi-model database that supports automatic indexing, multiple data models via different APIs, and configurable consistency levels with strong performance guarantees. Azure Redis Cache uses the open-source Redis data structure store with managed caching instances in Azure for improved application performance.
This document summarizes key components of Microsoft Azure's data platform, including SQL Database, NoSQL options like Azure Tables, Blob Storage, and Azure Files. It provides an overview of each service, how they work, common use cases, and demos of creating resources and accessing data. The document is aimed at helping readers understand Azure's database and data storage options for building cloud applications.
Introduction to Windows Azure Data ServicesRobert Greiner
This document provides an overview of using Azure for data management. It discusses using PartitionKey and RowKey to organize data into partitions in Azure table storage. It also recommends using the Azure Storage Client library for .NET applications and describes retry policies for handling errors. Links are provided for additional documentation on Azure table storage and messaging between Azure services.
The cloud is all the rage. Does it live up to its hype? What are the benefits of the cloud? Join me as I discuss the reasons so many companies are moving to the cloud and demo how to get up and running with a VM (IaaS) and a database (PaaS) in Azure. See why the ability to scale easily, the quickness that you can create a VM, and the built-in redundancy are just some of the reasons that moving to the cloud a “no brainer”. And if you have an on-prem datacenter, learn how to get out of the air-conditioning business!
This document discusses the benefits of cloud computing using Microsoft Azure. It highlights how Azure allows businesses to rapidly setup environments, scale to meet demands, and increase efficiency at a reduced cost compared to on-premises infrastructure. It provides an overview of Azure services including compute, storage, databases, analytics, web apps, and developer tools. Finally, it outlines how users can get started with Azure through the management portal, scripting, or development tools.
This document discusses Microsoft Azure, a cloud computing platform. It provides an overview of Azure's capabilities including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). It highlights key Azure services such as virtual machines, SQL database, web apps, machine learning, and more. The document also discusses how Azure enables businesses to rapidly setup environments, scale infrastructure, and increase efficiency at a lower cost compared to on-premises solutions.
Azure SQL Database & Azure SQL Data WarehouseMohamed Tawfik
This document provides an overview of Microsoft Azure Data Services and Azure SQL Database. It discusses Infrastructure as a Service (IaaS) versus Platform as a Service (PaaS), and highlights the opportunities in the Linux database market. It also discusses Microsoft's commitment to customer choice and partnerships with companies like Red Hat. The remainder of the document focuses on features of Azure SQL Database, including an overview of the DTU and vCore purchasing models, managed instances, backup and recovery, high availability options, elastic scalability, and data sync capabilities.
Azure SQL DB Managed Instances Built to easily modernize application data layerMicrosoft Tech Community
The document discusses Azure SQL Database Managed Instance, a new fully managed database service that provides SQL Server compatibility. It offers seamless migration of SQL Server workloads to the cloud with full compatibility, isolation, security and manageability. Customers can realize up to a 406% ROI over on-premises solutions through lower TCO, automatic management and scaling capabilities.
Microsoft certified azure developer associateGaurav Singh
The Mastering Microsoft Azure Developer Training makes you proficient in developing, planning, and scaling your web applications on Microsoft Azure. It includes training on Azure App Services, Azure Storage, Azure Virtual Machines, Azure SQL Database , Microservices, Azure AD, Azure Automation and DevOps using real-life case studies. The curriculum has been designed by Microsoft MVPs & Industry expert to earn Microsoft Azure Developer Associate Certification (AZ-204).
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
The Webinar takes participants through the entire cloud migration life-cycle – from initial analysis to final migration. We evaluate the leading cloud DBMS offerings from Amazon, Microsoft and Oracle. We also compare IaaS and DBaaS to better understand the two architectures and identify the most appropriate use case for each platform.
We finish by providing RDX’s recommended database migration procedures and the vendor utilities you can leverage to ensure trouble-free cloud transitions. Learn from experts who have migrated dozens of on-premises systems to the cloud!
Microsoft Azure Cosmos DB is a multi-model database that supports document, key-value, wide-column and graph data models. It provides high throughput, low latency and global distribution across multiple regions. Cosmos DB supports multiple APIs including SQL, MongoDB, Cassandra and Gremlin to allow developers to use their preferred API based on their application needs and skills. It also provides automatic scaling of throughput and storage across all data partitions.
The Evolution of SQL Server as a Service - SQL Azure Managed InstanceJavier Villegas
Managed Instance provides a fully managed SQL Server database hosted on Azure PaaS that allows existing SQL Server applications to be migrated to the cloud with minimal changes. It provides near 100% compatibility with on-premises SQL Server along with the management and scalability benefits of PaaS. Key capabilities include built-in high availability, automated backups, isolation within a VNet, and the ability to migrate databases with minimal downtime.
Microsoft Azure Offerings and New Services Mohamed Tawfik
Microsoft Azure offers a wide range of computing services including networking, compute, storage, databases, developer tools, and analytics services. It provides benefits such as pay-as-you-go pricing, quick setup, scalability, redundancy, and high availability. Microsoft has seen incredible growth in Azure due to its ability to convert its large enterprise customer base into Azure customers and build hybrid cloud solutions. The presentation highlights several new Azure services and features in networking, compute, storage, databases, and security.
Introduction to Azure SQL Database Managed Instance SQLKonferenz 2018. Showing architecture and overview of the features that are available in public preview.
This document provides an overview of Azure SQL Managed Instance and how it compares to other Azure SQL options. It discusses how Managed Instance takes care of database management tasks like backups, high availability, and updates. It also summarizes the service tiers of General Purpose and Business Critical and their key features like storage performance and read replicas. Finally, it outlines approaches for migrating databases to Managed Instance using tools like DMA and restoring backups.
Azure SQL Database now has a Managed Instance, for near 100% compatibility for lifting-and-shifting applications running on Microsoft SQL Server to Azure. Contact me for more information.
Data saturday Oslo Azure Purview Erwin de KreukErwin de Kreuk
Azure Purview provides unified data governance capabilities including automated data discovery, classification, and lineage visualization. It helps organizations overcome data governance silos, comply with regulations, and increase data agility. The key components of Azure Purview include the Data Map for automated metadata extraction and lineage, the Data Catalog for data discovery and governance, and Insights for monitoring data usage. It supports governance of data across cloud and on-premises environments in a serverless and fully managed platform.
--session donnée lors du SQL Saturday Lisbon 2015--
Data Management Gateway (and also AS Connector) is what make modern Microsoft BI stack hybrid. Power BI and Azure Data Factory use that component to interact with On-Prem Data assets.
That session is a Deep dive into the DMG and the hybrid architecture involved by Power BI and ADF. How does it work ? Security, Firewall, Certificates, Multiple gateways, Admin delegation, Scale out, Disaster Recovery…. All that topics will be covered during that technical session.
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp
ML.NET is an open source, machine learning framework built in .NET and runs on Windows, Linux and macOS. It allows developers to integrate custom machine learning into their applications without any prior expertise in developing or tuning machine learning models. Enhance your .NET apps with sentiment analysis, price prediction, fraud detection and more using custom models built with ML.NET
In this Session, Andy will show not only the core of ML.NET but best practices around Azure Data Lake and data in general when using .NET
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
Microsoft Azure platform provides a database as a service offering that allows developers to use SQL in the same way as they would in an on-premises location.
We identify the key challenges associated with switching to cloud DBMS environments and provide proven best practices for making your transition to the cloud successful. RDX currently supports dozens of cloud systems.
The webinar provides our experiences with the cloud and its hidden impact on IT support. A video recording of the webinar is included.
The new Microsoft Azure SQL Data Warehouse (SQL DW) is an elastic data warehouse-as-a-service and is a Massively Parallel Processing (MPP) solution for "big data" with true enterprise class features. The SQL DW service is built for data warehouse workloads from a few hundred gigabytes to petabytes of data with truly unique features like disaggregated compute and storage allowing for customers to be able to utilize the service to match their needs. In this presentation, we take an in-depth look at implementing a SQL DW, elastic scale (grow, shrink, and pause), and hybrid data clouds with Hadoop integration via Polybase allowing for a true SQL experience across structured and unstructured data.
The document provides an overview of Microsoft Azure's data platform and various database options, including SQL Database, SQL Server VMs, DocumentDB, HDInsight, and Azure Search. It discusses the architecture and features of these services, how to provision and manage databases, and includes demos of interacting with the databases. The key services covered allow for relational, non-relational, and search databases hosted on Azure infrastructure at varying levels of management and control.
Azure SQL DB Managed Instances Built to easily modernize application data layerMicrosoft Tech Community
The document discusses Azure SQL Database Managed Instance, a new fully managed database service that provides SQL Server compatibility. It offers seamless migration of SQL Server workloads to the cloud with full compatibility, isolation, security and manageability. Customers can realize up to a 406% ROI over on-premises solutions through lower TCO, automatic management and scaling capabilities.
Microsoft certified azure developer associateGaurav Singh
The Mastering Microsoft Azure Developer Training makes you proficient in developing, planning, and scaling your web applications on Microsoft Azure. It includes training on Azure App Services, Azure Storage, Azure Virtual Machines, Azure SQL Database , Microservices, Azure AD, Azure Automation and DevOps using real-life case studies. The curriculum has been designed by Microsoft MVPs & Industry expert to earn Microsoft Azure Developer Associate Certification (AZ-204).
This document provides an overview of Azure SQL DB environments. It discusses the different types of cloud platforms including IaaS, PaaS and DBaaS. It summarizes the key features and benefits of Azure SQL DB including automatic backups, geo-replication for disaster recovery, and elastic pools for reducing costs. The document also covers pricing models, performance monitoring, automatic tuning capabilities, and security features of Azure SQL DB.
The Webinar takes participants through the entire cloud migration life-cycle – from initial analysis to final migration. We evaluate the leading cloud DBMS offerings from Amazon, Microsoft and Oracle. We also compare IaaS and DBaaS to better understand the two architectures and identify the most appropriate use case for each platform.
We finish by providing RDX’s recommended database migration procedures and the vendor utilities you can leverage to ensure trouble-free cloud transitions. Learn from experts who have migrated dozens of on-premises systems to the cloud!
Microsoft Azure Cosmos DB is a multi-model database that supports document, key-value, wide-column and graph data models. It provides high throughput, low latency and global distribution across multiple regions. Cosmos DB supports multiple APIs including SQL, MongoDB, Cassandra and Gremlin to allow developers to use their preferred API based on their application needs and skills. It also provides automatic scaling of throughput and storage across all data partitions.
The Evolution of SQL Server as a Service - SQL Azure Managed InstanceJavier Villegas
Managed Instance provides a fully managed SQL Server database hosted on Azure PaaS that allows existing SQL Server applications to be migrated to the cloud with minimal changes. It provides near 100% compatibility with on-premises SQL Server along with the management and scalability benefits of PaaS. Key capabilities include built-in high availability, automated backups, isolation within a VNet, and the ability to migrate databases with minimal downtime.
Microsoft Azure Offerings and New Services Mohamed Tawfik
Microsoft Azure offers a wide range of computing services including networking, compute, storage, databases, developer tools, and analytics services. It provides benefits such as pay-as-you-go pricing, quick setup, scalability, redundancy, and high availability. Microsoft has seen incredible growth in Azure due to its ability to convert its large enterprise customer base into Azure customers and build hybrid cloud solutions. The presentation highlights several new Azure services and features in networking, compute, storage, databases, and security.
Introduction to Azure SQL Database Managed Instance SQLKonferenz 2018. Showing architecture and overview of the features that are available in public preview.
This document provides an overview of Azure SQL Managed Instance and how it compares to other Azure SQL options. It discusses how Managed Instance takes care of database management tasks like backups, high availability, and updates. It also summarizes the service tiers of General Purpose and Business Critical and their key features like storage performance and read replicas. Finally, it outlines approaches for migrating databases to Managed Instance using tools like DMA and restoring backups.
Azure SQL Database now has a Managed Instance, for near 100% compatibility for lifting-and-shifting applications running on Microsoft SQL Server to Azure. Contact me for more information.
Data saturday Oslo Azure Purview Erwin de KreukErwin de Kreuk
Azure Purview provides unified data governance capabilities including automated data discovery, classification, and lineage visualization. It helps organizations overcome data governance silos, comply with regulations, and increase data agility. The key components of Azure Purview include the Data Map for automated metadata extraction and lineage, the Data Catalog for data discovery and governance, and Insights for monitoring data usage. It supports governance of data across cloud and on-premises environments in a serverless and fully managed platform.
--session donnée lors du SQL Saturday Lisbon 2015--
Data Management Gateway (and also AS Connector) is what make modern Microsoft BI stack hybrid. Power BI and Azure Data Factory use that component to interact with On-Prem Data assets.
That session is a Deep dive into the DMG and the hybrid architecture involved by Power BI and ADF. How does it work ? Security, Firewall, Certificates, Multiple gateways, Admin delegation, Scale out, Disaster Recovery…. All that topics will be covered during that technical session.
Technical session on Databases as Service in Azure
Technical session - Azure SQL DB on Dec 20, 2020
https://youtu.be/Cl4IDpc_0yc
Technical session - 2 on Azure SQL DB - Dec 27, 2020
https://youtu.be/_4lZ54eI3F0
Technical session on Azure Cosmos DB -Dec 27, 2020
https://youtu.be/rtDwX1K_64k
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp
ML.NET is an open source, machine learning framework built in .NET and runs on Windows, Linux and macOS. It allows developers to integrate custom machine learning into their applications without any prior expertise in developing or tuning machine learning models. Enhance your .NET apps with sentiment analysis, price prediction, fraud detection and more using custom models built with ML.NET
In this Session, Andy will show not only the core of ML.NET but best practices around Azure Data Lake and data in general when using .NET
Migrating on premises workload to azure sql databasePARIKSHIT SAVJANI
This document provides an overview of migrating databases from on-premises SQL Server to Azure SQL Database Managed Instance. It discusses why companies are moving to the cloud, challenges with migration, and the tools and services available to help with assessment and migration including Data Migration Service. Key steps in the migration workflow include assessing the database and application, addressing compatibility issues, and deploying the converted schema to Managed Instance which provides high compatibility with on-premises SQL Server in a fully managed platform as a service model.
Microsoft Azure platform provides a database as a service offering that allows developers to use SQL in the same way as they would in an on-premises location.
We identify the key challenges associated with switching to cloud DBMS environments and provide proven best practices for making your transition to the cloud successful. RDX currently supports dozens of cloud systems.
The webinar provides our experiences with the cloud and its hidden impact on IT support. A video recording of the webinar is included.
The new Microsoft Azure SQL Data Warehouse (SQL DW) is an elastic data warehouse-as-a-service and is a Massively Parallel Processing (MPP) solution for "big data" with true enterprise class features. The SQL DW service is built for data warehouse workloads from a few hundred gigabytes to petabytes of data with truly unique features like disaggregated compute and storage allowing for customers to be able to utilize the service to match their needs. In this presentation, we take an in-depth look at implementing a SQL DW, elastic scale (grow, shrink, and pause), and hybrid data clouds with Hadoop integration via Polybase allowing for a true SQL experience across structured and unstructured data.
The document provides an overview of Microsoft Azure's data platform and various database options, including SQL Database, SQL Server VMs, DocumentDB, HDInsight, and Azure Search. It discusses the architecture and features of these services, how to provision and manage databases, and includes demos of interacting with the databases. The key services covered allow for relational, non-relational, and search databases hosted on Azure infrastructure at varying levels of management and control.
This document provides an introduction to Azure SQL Database. It describes Azure SQL Database as a fully managed relational database service. It notes that Azure SQL Database differs from SQL Server in some ways, such as not supporting certain T-SQL constructs and commands. The document also discusses server provisioning, database deployment, monitoring, and new service tiers for Azure SQL Database that offer different levels of scalability, performance, and business continuity features.
Azure SQL Database Managed Instance is a new flavor of Azure SQL Database that is a game changer. It offers near-complete SQL Server compatibility and network isolation to easily lift and shift databases to Azure (you can literally backup an on-premise database and restore it into a Azure SQL Database Managed Instance). Think of it as an enhancement to Azure SQL Database that is built on the same PaaS infrastructure and maintains all it's features (i.e. active geo-replication, high availability, automatic backups, database advisor, threat detection, intelligent insights, vulnerability assessment, etc) but adds support for databases up to 35TB, VNET, SQL Agent, cross-database querying, replication, etc. So, you can migrate your databases from on-prem to Azure with very little migration effort which is a big improvement from the current Singleton or Elastic Pool flavors which can require substantial changes.
This document discusses Microsoft SQL Server options in Azure. It begins by explaining the differences between Azure SQL and on-premises SQL Server, noting that Azure SQL is based on the latest SQL Server Enterprise version in a PaaS model and is not fully compatible with on-premises SQL Server. It then outlines the various options for SQL in Azure, including SQL Server on VMs, containers, and Azure SQL with DTU or vCore pricing/scaling models. The document provides details on features, pricing tiers, scaling, security, and other considerations for using SQL in Azure. It concludes that while migration may require adjustments, Azure SQL provides many advantages over on-premises SQL Server.
The document summarizes key topics from a lecture on database design for enterprise systems, including:
1) Logical and physical database design steps such as conceptual modeling and converting models to schemas.
2) Database security topics like authentication, authorization, and data encryption.
3) Characteristics of enterprise database environments including high availability, load balancing, clustering, replication, and integrating databases with continuous integration systems.
Data is as critical as ever. Storage costs are lower but we have more and more data to store. This is where Microsoft Azure Data Storage solutions come in. This slide deck provides an overview of the most important data storage options available in Azure.
Note: I did not create this deck. I instead combined slides from the Microsoft Azure-Readiness/DevCamp repo on GitHub (https://github.com/Azure-Readiness/DevCamp) while adding additional material from a slide deck of David Chappell's.
This talk was given at Cloud Camp Kitchener 2015.
This document discusses data options in the cloud, including database choices like SQL Server, SQL Azure Database, and hosted SQL Server. It covers features of SQL Azure like scalability, high availability, and self-provisioning. Storage options like Windows Azure Storage blobs, tables, and queues are described. SQL Server 2008 R2 improvements in performance, manageability, business intelligence, and master data management are highlighted. Pricing models for SQL Azure and Windows Azure Storage are provided at the end.
SQL Azure provides a relational database as a service on the Windows Azure platform. It aims to be familiar to SQL Server developers by using the same programming model and tools. SQL Azure databases are automatically replicated and scaled to ensure high availability and performance. The initial release will focus on supporting common web and departmental application scenarios. Over time, additional SQL Server capabilities will be added as services on SQL Azure.
SQL Azure is Microsoft's relational database service that allows users to provision databases in the cloud. It provides automatic high availability, scalability, and management. SQL Azure databases are massively scaled out across commodity hardware and support common SQL features and application patterns. Key benefits include self-provisioning, capacity on demand, high availability, automated management, and pay per use pricing. Security measures include standard SQL authentication and authorization, network access control via firewall rules, and encryption of data in transit.
Survey of SQL Azure, SQL Azure Data Sync, SQL Azure OData Feeds, SQL Azure Data Migration Wizard, Roadmap, and PowerPivot Integration. Given on Day of Azure 2, Dec 4th, 2010. Presented by Ike Ellis & Lynn Langit
Dans cette session nous vous présenterons les différentes manières d'utiliser SQL Server dans une infrastructure Cloud (Microsoft Azure). Seront présentés des scénarios hybrides, de migration, de backup, et d'hébergement de bases de données SQL Server en mode IaaS ou PaaS.
Experience sql server on l inux and dockerBob Ward
Microsoft SQL Server provides a full-featured database for Linux that offers high performance, security and flexibility across languages and platforms at a lower cost compared to other commercial databases. It has the most consistent data platform with industry-leading performance on Linux and Windows and supports machine learning and artificial intelligence capabilities. SQL Server on Linux allows customers to deploy the database on their choice of Linux distribution for both traditional and container-based workloads.
This document discusses the future of data and the Azure data ecosystem. It highlights that by 2025 there will be 175 zettabytes of data in the world and the average person will have over 5,000 digital interactions per day. It promotes Azure services like Power BI, Azure Synapse Analytics, Azure Data Factory and Azure Machine Learning for extracting value from data through analytics, visualization and machine learning. The document provides overviews of key Azure data and analytics services and how they fit together in an end-to-end data platform for business intelligence, artificial intelligence and continuous intelligence applications.
Azure Days 2019: Business Intelligence auf Azure (Marco Amhof & Yves Mauron)Trivadis
In dieser Session stellen wir ein Projekt vor, in welchem wir ein umfassendes BI-System mit Hilfe von Azure Blob Storage, Azure SQL, Azure Logic Apps und Azure Analysis Services für und in der Azure Cloud aufgebaut haben. Wir berichten über die Herausforderungen, wie wir diese gelöst haben und welche Learnings und Best Practices wir mitgenommen haben.
The document provides an overview of new features and enhancements in SQL Server 2008 including:
- .NET Framework integration and new data types
- Database engine improvements like partitioning and failover clustering
- Management tools like SQL Server Management Studio and SQLCMD
- Performance tuning tools like the Database Tuning Advisor
- Analytics capabilities including Analysis Services and Reporting Services
- Replication, reporting, and integration with other Microsoft technologies
It also discusses best practices for upgrading from previous versions of SQL Server to version 2008.
This document provides an overview of 6 modules related to SQL Server workshops:
- Module 1 covers database design and architecture sessions
- Module 2 focuses on intelligent query processing, data classification/auditing, database recovery, data virtualization, and replication capabilities
- Module 3 discusses the big data landscape, including data growth drivers, common use cases, and scale-out processing approaches like Hadoop and Spark
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
The role of intelligent sensors in the cloud publicMostafa
The document discusses the role of intelligent sensors in the cloud and edge computing. It outlines the advantages of compute at the edge such as minimizing latency, reducing bandwidth costs, and improving reliability. The 3Cs of the intelligent edge are described as connect, compute, and control insights. Instructions are provided on setting up an IoT edge device and links are included for further information on how IoT edge works and Microsoft Build.
Skill up in machine learning using Azure MLMostafa
Data drives decisions and actions. Machine learning uses data to build models that can predict unknown data. The machine learning process involves getting data, preparing it by extracting features, training a model on known data and labels, and evaluating the model's performance on predicting labels of unknown data. These trained models can then be deployed as web services to power applications.
Azure Data Platform Services
HDInsight Clusters in Azure
Data Storage: Apache Hive, Apache Hbase, Azure Data Catalog
Data Transformations: Apache Storm, Apache Spark, Azure Data Factory
Healthcare / Life Sciences Use Cases
Building predictive models in Azure Machine LearningMostafa
This presentation covers how to build and drive insights from data by building machine learning models. The session covers how to develop and train models in Python/R using Azure Machine Learning. The session covers how to explore key concepts in data acquisition, preparation, exploration, and visualization, and take a look at how to build a predictive solution using Azure Machine Learning, R, and Python. The session covers tips and tricks on selecting the right algorithm for your data science problem and how to utilize Machine Learning to solve it.
Architecting big data solutions in the cloudMostafa
The session covers how to architect big data solutions in Azure. Azure provides different Hadoop clusters types. The session covers the basic understanding of Lambda Architecture and how to build end to end big data solution using Apache Hadoop HDFS, HBase, Hive, Storm and Spark. The session covers how to integrate by building apps using any programming language such as Java, Python, or Scala with HDInsight clusters using various Hadoop integration frameworks and libraries. The session is a jump start for Architects, engineers and DBAs with RDBMS experience who are looking for starting building big data solutions based on Hadoop. The session is a demo driven and will cover the basics of Hadoop open source products.
This session covers how to work with PySpark interface to develop Spark applications. From loading, ingesting, and applying transformation on the data. The session covers how to work with different data sources of data, apply transformation, python best practices in developing Spark Apps. The demo covers integrating Apache Spark apps, In memory processing capabilities, working with notebooks, and integrating analytics tools into Spark Applications.
Use Machine learning to solve classification problems through building binary and multi-class classifiers.
Does your company face business-critical decisions that rely on dynamic transactional data? If you answered “yes,” you need to attend this free event featuring Microsoft analytics tools. We’ll focus on Azure Machine Learning capabilities and explore the following topics: - Introduction of two class classification problems.
- Classification Algorithms (Two Class Classification)
- Available algorithms in Azure ML.
- Real business problems that is solved using two class classification.
A presentation covers how data science is connected to build effective machine learning solutions. How to build end to end solutions in Azure ML. How to build, model, and evaluate algorithms in Azure ML.
The talk will cover how to build interactive analytics, dashboards and reports in PowerBI. Using multiple data sources, synchronization schedule and sharing capabilities in PowerBI. The PowerBI web and client tool provides sophisticated tools for non-technical users to build interactive dashboards.
The session will be demo driven and will cover different use cases that use multiple data formats and sources.
-- PowerBI client tool & web capabilities
-- Interactive Dashboards and Reporting.
-- Platform capabilities such as sharing, scheduling and more.
The document discusses microservices architecture and Azure services for building and hosting microservices. It describes how Azure supports microservices using PaaS options like App Service and Service Fabric. It also provides examples of implementing microservices using Cloud Services with Web and Worker roles along with features of App Service like deployments, backups and integrations.
The session covers how to get started to build big data solutions in Azure. Azure provides different Hadoop clusters for Hadoop ecosystem. The session covers the basic understanding of HDInsight clusters including: Apache Hadoop, HBase, Storm and Spark. The session covers how to integrate with HDInsight in .NET using different Hadoop integration frameworks and libraries. The session is a jump start for engineers and DBAs with RDBMS experience who are looking for a jump start working and developing Hadoop solutions. The session is a demo driven and will cover the basics of Hadoop open source products.
The presentation covers how to get started to build big data solutions in Azure. Azure provides different Hadoop clusters for Hadoop ecosystem. The session covers the basic understanding of HDInsight clusters including: Apache Hadoop, HBase, Storm and Spark. The session covers how to integrate with HDInsight in .NET using different Hadoop integration frameworks and libraries. The session is a jump start for engineers and DBAs with RDBMS experience who are looking for a jump start working and developing Hadoop solutions. The session is a demo driven and will cover the basics of Hadoop open source products.
Patterns and Practices in Building Office Add-insMostafa
This document discusses Office Add-ins, which allow users to extend Office applications like Word, Excel, PowerPoint and Outlook using web technologies. Office Add-ins can be embedded inline within documents or as a task pane. They are defined using an XML manifest and include HTML, CSS and JavaScript. The document outlines how to design, develop and deploy effective Office Add-ins.
In this session i am covering data science principals such as: Regression, Clustering, Classification, Recommendation and how to build programmable components in Azure Machine Learning experiments using data science programming languages. The session shows and illustrate how to implement these concepts using Azure ML studio.
This document discusses building interactive analytics using Power BI. It provides an overview of Power BI capabilities including connecting to various data sources, scheduling data refreshes, and sharing dashboards. It also covers Power BI Embedded which allows embedding Power BI reports in web and mobile apps without requiring user logins. The document includes demonstrations of the Power BI web service, creating a dashboard from Google Analytics data, and using Power BI Embedded in an ASP.NET MVC application.
This presentation covers the basics of TypeScript and will show you how to enable TypeScript features in existing projects. We'll take a guided tour of TypeScript, showing how the language and toolset makes it easier to write cross-platform, large-scale JavaScript applications.
The session covers how to get started to build big data solutions in Azure. Azure provides different Hadoop clusters for Hadoop ecosystem. The session covers the basic understanding of HDInsight clusters including: Apache Hadoop, HBase, Storm and Spark. The session covers how to integrate with HDInsight in .NET using different Hadoop integration frameworks and libraries. The session is a jump start for engineers and DBAs with RDBMS experience who are looking for a jump start working and developing Hadoop solutions. The session is a demo driven and will cover the basics of Hadoop open source products.
The session covers how to build web, mobile, Api solutions using Microsoft Azure platform. The session covers in detail how to build intelligent solutions using Azure App Service. Azure App Service includes web apps, logic apps and mobile apps services as PaaS solutions for engineers. The session is a demo driven and demonstrate how to design and provision complete end-to-end solutions using Microsoft intelligent cloud.
Why Orangescrum Is a Game Changer for Construction Companies in 2025Orangescrum
Orangescrum revolutionizes construction project management in 2025 with real-time collaboration, resource planning, task tracking, and workflow automation, boosting efficiency, transparency, and on-time project delivery.
Download YouTube By Click 2025 Free Full Activatedsaniamalik72555
Copy & Past Link 👉👉
https://dr-up-community.info/
"YouTube by Click" likely refers to the ByClick Downloader software, a video downloading and conversion tool, specifically designed to download content from YouTube and other video platforms. It allows users to download YouTube videos for offline viewing and to convert them to different formats.
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov
Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search.
Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.
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Wondershare Filmora is a video editing software and app designed for both beginners and experienced users. It's known for its user-friendly interface, drag-and-drop functionality, and a wide range of tools and features for creating and editing videos. Filmora is available on Windows, macOS, iOS (iPhone/iPad), and Android platforms.
Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup
In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals.
This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft.
What You’ll Learn in Part 2:
Explore real-world nonprofit use cases and success stories.
Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!
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Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
Here's a more detailed breakdown:
Motion Graphics:
.
After Effects is powerful for creating animated titles, transitions, and other visual elements to enhance the look of videos and presentations.
Visual Effects:
.
It's used extensively in film and television for creating special effects like green screen compositing, object manipulation, and other visual enhancements.
Video Compositing:
.
After Effects allows users to combine multiple video clips, images, and graphics to create a final, cohesive visual.
Animation:
.
It uses keyframes to create smooth, animated sequences, allowing for precise control over the movement and appearance of objects.
Integration with Adobe Creative Cloud:
.
After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
Post-Production Tool:
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After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell
It's time you stopped letting your telemetry data pressure your budgets and get in the way of solving issues with agility! No more I say! Take back control of your telemetry data as we guide you through the open source project Fluent Bit. Learn how to manage your telemetry data from source to destination using the pipeline phases covering collection, parsing, aggregation, transformation, and forwarding from any source to any destination. Buckle up for a fun ride as you learn by exploring how telemetry pipelines work, how to set up your first pipeline, and exploring several common use cases that Fluent Bit helps solve. All this backed by a self-paced, hands-on workshop that attendees can pursue at home after this session (https://o11y-workshops.gitlab.io/workshop-fluentbit).
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Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
Key improvements and features of Cinema 4D 2025 include:
Procedural Modeling: New tools and workflows for creating models procedurally, including fabric weave and constellation generators.
Procedural Animation: Field Driver tag for procedural animation.
Simulation Enhancements: Improved particle, Pyro, and rigid body simulations.
Spline Tools: Enhanced spline tools for motion graphics and animation, including spline modifiers from Rocket Lasso now included for all subscribers.
Unified Simulation & Particles: Refined physics-based effects and improved particle systems.
Boolean System: Modernized boolean system for precise 3D modeling.
Particle Node Modifier: New particle node modifier for creating particle scenes.
Learning Panel: Intuitive learning panel for new users.
Redshift Integration: Maxon now includes access to the full power of Redshift rendering for all new subscriptions.
In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
Discover why Wi-Fi 7 is set to transform wireless networking and how Router Architects is leading the way with next-gen router designs built for speed, reliability, and innovation.
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
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Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
Users who prefer a traditional workflow:
Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
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5. SQL Database Server
The Service head contains databases
Connect via automatically generated
FQDN: {name}.database.windows.net
Initially contains only a master
database
7. Limit Exposure of Sensitive Data
Protect Sensitive Data
Limits sensitive data exposure
Prevents unauthorized access to data
Policy-based security – no changes to
data or application
Meet regulatory compliance
Dev/Test production data without
compromising data
Dynamic Data Masking
8. Encrypt and Protect Database
Encrypted database, backups, and
transaction log at rest
2-click provisioning
Reduced attack surface area
No code changes to existing applications
Database encryption key - AES-256
Meet regulatory compliance
Accelerated hardware encryption
Transparent Data Encryption (TDE)
9. Fine-grained Access Over Rows
Fine-grained access over rows
Access restrictions logic contained in
database
Simplified design and coding of security
Meet regulatory compliance
Reduced surface area of your security
system
Available on SQL Server 2016.
Row-Level Security (RLS)
10. Fine-grained Access Over Rows
Contained Database Users
Parallel Queries
Common Language Runtime (CLR)
assemblies
Other notable features
15. Service
Tier
Performance
Level
Common App
Pattern
Performance Business Continuity
Max DB
Size
Transaction
Perf. Objective
DTU PITR DR / GEO-Rep
Basic Basic Small DB, SQL opp 2 GB Reliability / Hr. 5 7 Days DB Copy +
Manual Export
Standard S0
S1
S2
Wrkgp/cloud app,
multiple concurrent
operations
250 GB Reliability / Min. 10
20
50
14
Days
DB Copy +
Manual Export
Premium P1
P2
P3
Mission Critical, High
volume, Many
concurrent Users
500 GB Reliability / sec. 100
200
800
35
Days
Active Geo-
replication
Selecting the right SQL Database edition
This information is subject to change over time.
16. Auto backups, transactional logs every 5 min
Backups in Azure Storage and geo-replicated
Creates a side-by-side copy, non-disruptive
Backups retention policy: 7, 14 or 35 days
Automated export of logical backups for long-term
backup protection
Point-in-time restore - “oops recovery”
17. Available in all tiers: Basic, Standard and Premium
Built on geo-redundant Azure Storage
Recover to any Azure region
Geo-restore – Emergency data recovery when you need it most
18. Opt-in for Standard & Premium databases
Creates a stand-by secondary
Replicate to pre-paired Azure region
Automatic data replication, asynchronous
Opt-in via REST API, PowerShell or Azure Portal
Microsoft-managed, RTO<24h, RPO<1 hr
Standard geo-replication
19. Self-service activation in Premium
Create up to 4 readable secondaries
Replicate to any Azure region
Automatic data replication, asynchronous
REST API, PowerShell or Azure Portal
RTO<1h, RPO<5m, you choose when to failover
Active geo-replication
20. Configurable to track & log database activity
Dashboard views in the portal for at-a-glance insights
Pre-defined Power View reports for deep visual
analysis on Audit log data
Audit logs reside in your Azure Storage account
Available in Basic, Standard, and Premium
Auditing
21. Fast and flexible indexing of textual data
Data types: char, varchar, nchar, nvarchar, text, ntext,
image, xml, varbinary(max), or FILESTREAM
Handles high query volume
Common use cases:
Searching websites, product catalogs, news items and more
Document management systems
Any applications that need to provide search capabilities over data stored in a SQL
Database
Full-Text Search
22. XML Indexes - improves XQuery-based query
performance
Primary XML Index - speed up access to elements and
attributes
CREATE PRIMARY XML INDEX XML_Order_Items
ON Sales.Order (Items);
Secondary XML Index – help resolve specific XQuery
expressions rapidly
XML Indexes
27. Use Familiar Technologies - Tools
SQL Server Management Studio (>=2008 R2)
SQL Server command-line utilities (SQLCMD, BCP)
Visual Studio IDE for database development
28. Unsupported
SQL Server
Features
Use command, distributed
transactions, distributed views
Service Broker
SQL Agent
SQL Profiler
Native Encryption
29. Web designers for tables, views, stored procs
Interactive query editing and execution
Azure SQL Database Management Portal
33. Elastic Database Model PREVIEW
Elastic databases, Elastic database pools
Pooled resources leveraged by many databases
Standard elastic pool provides 200-1200* eDTUs for up to 100* databases
Elastic Standard databases can burst up to 100 eDTUs (S3 level)
Create/configure pool via portal, PowerShell, REST APIs
Move databases in/out using portal, PowerShell, REST APIs, T-SQL
Databases remain online throughout
Monitoring and alerting is available on both pool and databases
*Additional pricing tiers may be introduced, and the ranges and limits may be increased during the preview
Max per-database burst level
34. Scalability options in Azure SQL DB
Vertical: Scale-up or scale-down
Horizontal: Scale-out or scale-in
Basic
Standard
Premium
Basic Basic Basic Basic Basic Basic
Premium
Standard
Scale out/in
Scaleup/down
36. Run SQL on VM
Run any SQL product on cloud VM
Support for SQL Server, Oracle, MySql
Ready to go VM images available in Gallery
Persistent storage using attached disk in blob storage
Has all the benefits and powers of VMs combined with
the full features of a SQL Engine
39. Other features SQL IaaS supports that SQL Database
doesn’t (yet)
Full SQL Server functionality (e.g. Reporting Services)
Windows authentication available (requires VM to be
joined to on-premises domain)
Larger database sizes possible (16TB)
43. Microsoft Azure Data Services
fully managed, scalable, queryable, schemafree JSON
document database service for modern applications
transactional processing
rich query
managed as a service
elastic scale
internet accessible http/rest
schema-free data model
arbitrary data formats
47. Azure Search
Embed a sophisticated search experience into web
and mobile applications without having to worry
about the complexities of full-text search and
without having to deploy, maintain or manage any
infrastructure.
48. Azure Search
Perfect for enterprise cloud developers,
cloud software vendors, cloud architects
who need a fully-managed search
solution.
49. Search
Functionality
Simple HTTP/JSON API for creating
indexes, pushing documents, searching
Keyword search with user-friendly
operators (+, -, *, “”, etc.)
Hit highlighting
Faceting (histograms over ranges,
typically used in catalog browsing)
50. Search
Functionality
Suggestions (auto-complete)
Rich structured queries (filter, select,
sort) that combines with search
Scoring profiles to model search result
relevance
Geo-spatial support integrated in
filtering, sorting and ranking
56. App Service Azure SQL Database
Azure Machine Learning
Intelligent App
Hadoop
Azure SQL Data
Warehouse
Power BI
A relational data warehouse-as-a-service
57. Scales to petabytes of data
Massively Parallel Processing
Instant-on compute scales in
seconds
Query Relational / Non-
Relational
Get started in minutes
Integrated with Azure ML,
PowerBI & ADF
Enterprise Ready
Simple billing compute &
storage
Pay for what you need, when
you need it with dynamic
pause
Bring DW to the Cloud
without rewriting
59. Azure Data Lake service
Store and manage infinite data
Keep data in its original form
High through put, low latency analytic
jobs
Enterprise-grade security + access
control
Data Lake
62. Additional Database options in Azure
Azure Table Service is a “Big Table” entity store.
MongoDB is a document (JSON) store.
Cassandra is a columnar store with excellent
replication.
HBase is a Big Data (Hadoop) store available in
HDInsight.
Oracle VMs are supported in Azure.
MySQL is offered from the partner ClearDB.
63. SQL Database SQL on IaaS DocumentDB
Search HDInsight
MongoDB, MySQL,
Oracle, Cassandra,
Neo4j and more
Microsoft Azure Data Platform
64. Post your questions to:
Stack Overflow Forums
MSDN Forums
Twitter: @MostafaElzoghbi
#3: The Azure data Platform is HUGE and growing. This session will have to be brief about some of this content and make a few deep dives here and there.
#4: Now let’s focus on Microsoft Azure SQL Database the PaaS service!
#5: Slide Objectives:
Understand that while there are physical SQL Server boxes behind the scenes, when connecting to SQL Database, you are not connecting to a physical server, but to a TDS endpoint.
Transition:
The key to understanding SQL Database is understanding while SQL Database is SQL Server, we do not interact with them in the same physical manner.
Speaking Points:
In an on-premises environment, we typically have physical access to the actual SQL Server server.
In Microsoft Azure, we do not have physical access to the actual server.
Notes:
It is important that the attendee understands that it IS INDEED SQL Server at the platform layer. There are physical boxes running SQL Server 2012 Enterprise Edition. However, due to the nature of the Azure environment to provide the high-availability and scalability necessary, access to the physical boxes is currently not supported.
#6: Slide Objectives:
Show the different methods of provisioning a SQL Database server along with how easy it is. Plus, help the attendees understand what a SQL Database “server” really is.
Transition:
Provisioning an on-premises SQL Server box can be time consuming, costly, and at times, a challenge. With SQL Database, provisioning a “server” is painless, quick, and provisioned in a matter of seconds.
Speaking Points:
Provision servers interactively using the Management Portal
Automate server provisioning using the Microsoft Azure Management API or PowerShell.
Notes:
While the “server” is technically a TDS endpoint, much of the SQL Server process is similar. Administration login credentials are still needed for security, and more importantly defining service access is essential, and required, for maintaining the integrity of your server through firewall rules.
#7: Slide Objectives:
Explain SQL Server Database Connectivity.
Speaking Points:
Explain how data is protected using server-level firewall and database-level firewall rules.
Explain the difference when services connecting to SQL Databases from the internet versus services connecting from the Azure Datacenters.
#8: Mostafa’s notes:
Available on SQL Server 2016.
Ref.: https://msdn.microsoft.com/en-us/library/mt130841.aspx
Speaker notes:
Limit sensitive data(e.g. customer or PII) exposure by masking data to non-privileged users in real time
Limit the exposure of sensitive data to meet industry compliance policies
Policy-based security feature hides the sensitive data in the result set of a query over designated database fields, while the data in the database is not changed and as a result require no changes to the Application layer.
A developer can query production environments for troubleshooting purposes without violating compliance regulations
#9: Speaker notes:
Protect your data by encrypting your database, associated backups, and transaction log files at rest in real-time without requiring changes to your application
Help you meet regulatory compliance
An entire database is encrypted by using an industry standard AES-256 symmetric key by the service
Easy as a 2 clicks to provision the service and all key management for database copying, Geo-Replication, and database restores anywhere in SQL Database is handled by the service
Support for Intel AES-NI hardware acceleration of encryption. This will reduce the CPU/DTU overhead of turning on Transparent Data Encryption
#10: -- Mostafa’s Notes:
This features is available from SQL Server 2016.
https://msdn.microsoft.com/en-us/library/dn765131(v=sql.130).aspx
Speaker notes:
Allow for data protection when multiple users or applications need to access different records in the same database tables. For example, implement restrictions on data rows to users pertinent to their department or restricting a customer's data access to only the data relevant to their company.
The access restriction logic is located in the database tier rather than away from the data in another application tier. Simplifies the design and coding of security in your application
Makes your security system more reliable and robust by reducing the surface area of your security system
#11: Speaker Notes:
SQL Database authenticate at the database level by using contained database users making databases more portable
Parallel Queries support heavier workloads
Author stored procedures, triggers, user-defined functions, user-defined types, and user-defined aggregates in managed code
#12: Important: In the Preview Management Portal you are able to create a custom server FQDN! In the Management Portal that name is randomized.
Slide Objectives:
Show the different methods of provisioning a SQL Database server along with how easy it is. Plus, help the attendees understand what a SQL Database “server” really is.
In the Preview Portal you can select the name of the server you create!
Transition:
Provisioning an on-premises SQL Server box can be time consuming, costly, and at times, a challenge. With SQL Database, provisioning a “server” is painless, quick, and provisioned in a matter of seconds.
Speaking Points:
Provision servers interactively using the Management Portal
Automate server provisioning using the Microsoft Azure Management API or PowerShell.
Notes:
While the “server” is technically a TDS endpoint, much of the SQL Server process is similar. Administration login credentials are still needed for security, and more importantly defining service access is essential, and required, for maintaining the integrity of your server through firewall rules.
#13: Slide Objectives:
Show the different methods of provisioning a SQL Database server along with how easy it is. Plus, help the attendees understand what a SQL Database “server” really is.
Transition:
Provisioning an on-premises SQL Server box can be time consuming, costly, and at times, a challenge. With SQL Database, provisioning a “server” is painless, quick, and provisioned in a matter of seconds.
Speaking Points:
Provision servers interactively using the Management Portal
Automate server provisioning using the Microsoft Azure Management API or PowerShell.
Notes:
While the “server” is technically a TDS endpoint, much of the SQL Server process is similar. Administration login credentials are still needed for security, and more importantly defining service access is essential, and required, for maintaining the integrity of your server through firewall rules.
#14: Slide Objectives:
Show the different methods of provisioning a SQL Database server along with how easy it is. Plus, help the attendees understand what a SQL Database “server” really is.
Transition:
Provisioning an on-premises SQL Server box can be time consuming, costly, and at times, a challenge. With SQL Database, provisioning a “server” is painless, quick, and provisioned in a matter of seconds.
Speaking Points:
Automate server provisioning using the Microsoft Azure Management API or PowerShell or xplat-cli.
#15: Demo 1)
-- Create SQL DB on Azure Portal – Setup Firewall – Connect using SSMS
-- Use VS 2015 // Server Explorer // SQL Server Object Explorer
-- Shows Dynamic Data Masking Feature in SQL Azure ( View Data in VS )
--
#16: Slide Objectives:
Highlight what’s new in the latest SQL Database service update.
Transition:
In late September a service update was deployed to Microsoft Azure SQL Database that included new functionality.
Speaking Points:
Linked Server – This is a new component for database hybrid solutions spanning on-premises corporate networks and the Microsoft Azure cloud.
Recursive Trigger – Just like SQL Server 2012, the option can be configured via ALTER DATABASE dbname SET RECURSIVE_TRIGGERS ON|OFF
DBCC – The query optimizer uses statistics to estimate the cardinality or number of rows in the query result, which enables the query optimizer to create a high quality query plan.
Firewall Rules – different rules for different databases hosted on the same logical SQL Database server
Notes:
#18: Emergency data recovery when you need it most
#19: RTO Recovery time objective http://en.wikipedia.org/wiki/Recovery_time_objective
RPO Recovery point objective http://en.wikipedia.org/wiki/Recovery_point_objective
#20: RTO Recovery time objective http://en.wikipedia.org/wiki/Recovery_time_objective
RPO Recovery point objective http://en.wikipedia.org/wiki/Recovery_point_objective
#21: Gain insight into database events & streamline compliance-related tasks
#22: Speaker notes:
Full-Text Search allows fast and flexible indexing for keyword-based query of text data stored in tables with columns of following data types: char, varchar, nchar, nvarchar, text, ntext, image, xml, or varbinary(max)
Full-text queries can include simple words and phrases or multiple forms of a word or phrase.
A full-text query returns any documents that contain at least one match (also known as a hit). A match occurs when a target document contains all the terms specified in the full-text query, and meets any other search conditions, such as the distance between the matching terms.
Full-text queries perform linguistic searches against text data in full-text indexes by operating on words and phrases based on rules of a particular language such as English or Japanese
A full-text query returns any documents that contain at least one match (also known as a hit). A match occurs when a target document contains all the terms specified in the full-text query, and meets any other search conditions, such as the distance between the matching terms.
Full-text search is applicable to a wide range of business scenarios such as e-businesses—searching for items on a web site; law firms—searching for case histories in a legal-data repository; or human resources departments—matching job descriptions with stored resumes.
#23: Slide objective:
XML indexes speedup XQuery-based query response
Speaker notes:
An XML index is like a copy of an XML object tree that is saved into the database for rapid reuse rather than an object created in memory and traversed during query time which is a relatively slow process.
Before you can create a primary XML index on a table, the table must have a clustered primary key.
Secondary indexes are designed to speed up a particular type of query such as PATH, VALUE, and PROPERTY indexes:
A PATH index helps to decide whether a particular path to an element or attribute is valid. It is typically used with the exist() XQuery method.
A VALUE index helps to obtain the value of an element or attribute.
A PROPERTY index is used when retrieving multiple values through PATH expressions.
#24: Slide objective:
Emphasize Azure SQL Database service has extremely rich environment for monitoring the status of your databases using DMVs.
Speaker notes:
Microsoft Azure SQL Database partially supports three categories of dynamic management views:
Database-related dynamic management views (indexes, partitions and waits)
Execution-related dynamic management views (connections, sessions, requests)Transaction-related dynamic management views (transactions and locks)
Identify expensive queries and gain an understanding of long running queries
View the status of your query within the execution plan
Detect the queries that run for long may be getting throttled by Azure SQL Database service
Monitor the size of transactions and transaction log usage
Helps with capacity planning - If these percentages remain near 100% utilization, you should consider improving performance by scaling out, scaling up, or optimizing your database design.
#26: Slide Objectives:
Point out that 1) The same great technologies that developers use today on-premises works with SQL Database 2) high-level differences between on-premises and SQL Database 3) SQL Database features currently unsupported
Transition:
Creating, managing, and deploying a database in Microsoft Azure SQL Database isn’t difficult. The key is understanding the features that are supported and how SQL Database compares to on-premises SQL Server and the technologies that can be used with SQL Database.
Speaking Points:
The same great technologies that developers use today on-premises works with SQL Database, including developer languages, Frameworks, and Tools. Nothing new to learn!
SQL Server Comparison -> highlight the physical vs. logical administration. Developers and DBAs can now focus on things they love to do and not worry about the physical aspect.
Features unsupported by SQL Database -> Many of the unsupported features are hardware based and thus don’t need to be in SQL Database. Other features, such as encryption, are server-based and become a challenge in solving in a shared-environment.
Notes:
CLR data types ARE supported, SQLCLR is not yet supported.
Backup/Restore: PIT Coming; Import/Export can be used for backup to BLOB storage. Third-party backup products available via RedGate and Enzo.
Data can be stored encrypted but the encryption must be done at the application level.
Native encryption is being looked at.
**Linked Servers and Distributed Queries are now supported, linking a SQL Database instance from an on-premises server. Linking two SQL Database instances is NOT supported.
#27: Slide Objectives:
Point out that 1) The same great technologies that developers use today on-premises works with SQL Database 2) high-level differences between on-premises and SQL Database 3) SQL Database features currently unsupported
Transition:
Creating, managing, and deploying a database in Microsoft Azure SQL Database isn’t difficult. The key is understanding the features that are supported and how SQL Database compares to on-premises SQL Server and the technologies that can be used with SQL Database.
Speaking Points:
The same great technologies that developers use today on-premises works with SQL Database, including developer languages, Frameworks, and Tools. Nothing new to learn!
SQL Server Comparison -> highlight the physical vs. logical administration. Developers and DBAs can now focus on things they love to do and not worry about the physical aspect.
Features unsupported by SQL Database -> Many of the unsupported features are hardware based and thus don’t need to be in SQL Database. Other features, such as encryption, are server-based and become a challenge in solving in a shared-environment.
Notes:
CLR data types ARE supported, SQLCLR is not yet supported.
Backup/Restore: PIT Coming; Import/Export can be used for backup to BLOB storage. Third-party backup products available via RedGate and Enzo.
Data can be stored encrypted but the encryption must be done at the application level.
Native encryption is being looked at.
**Linked Servers and Distributed Queries are now supported, linking a SQL Database instance from an on-premises server. Linking two SQL Database instances is NOT supported.
#28: Slide Objectives:
Point out that 1) The same great technologies that developers use today on-premises works with SQL Database 2) high-level differences between on-premises and SQL Database 3) SQL Database features currently unsupported
Transition:
Creating, managing, and deploying a database in Microsoft Azure SQL Database isn’t difficult. The key is understanding the features that are supported and how SQL Database compares to on-premises SQL Server and the technologies that can be used with SQL Database.
Speaking Points:
The same great technologies that developers use today on-premises works with SQL Database, including developer languages, Frameworks, and Tools. Nothing new to learn!
SQL Server Comparison -> highlight the physical vs. logical administration. Developers and DBAs can now focus on things they love to do and not worry about the physical aspect.
Features unsupported by SQL Database -> Many of the unsupported features are hardware based and thus don’t need to be in SQL Database. Other features, such as encryption, are server-based and become a challenge in solving in a shared-environment.
Notes:
CLR data types ARE supported, SQLCLR is not yet supported.
Backup/Restore: PIT Coming; Import/Export can be used for backup to BLOB storage. Third-party backup products available via RedGate and Enzo.
Data can be stored encrypted but the encryption must be done at the application level.
Native encryption is being looked at.
**Linked Servers and Distributed Queries are now supported, linking a SQL Database instance from an on-premises server. Linking two SQL Database instances is NOT supported.
#29: Slide Objectives:
Point out that 1) The same great technologies that developers use today on-premises works with SQL Database 2) high-level differences between on-premises and SQL Database 3) SQL Database features currently unsupported
Transition:
Creating, managing, and deploying a database in Microsoft Azure SQL Database isn’t difficult. The key is understanding the features that are supported and how SQL Database compares to on-premises SQL Server and the technologies that can be used with SQL Database.
Speaking Points:
The same great technologies that developers use today on-premises works with SQL Database, including developer languages, Frameworks, and Tools. Nothing new to learn!
SQL Server Comparison -> highlight the physical vs. logical administration. Developers and DBAs can now focus on things they love to do and not worry about the physical aspect.
Features unsupported by SQL Database -> Many of the unsupported features are hardware based and thus don’t need to be in SQL Database. Other features, such as encryption, are server-based and become a challenge in solving in a shared-environment.
Notes:
CLR data types ARE supported, SQLCLR is not yet supported.
Backup/Restore: PIT Coming; Import/Export can be used for backup to BLOB storage. Third-party backup products available via RedGate and Enzo.
Data can be stored encrypted but the encryption must be done at the application level.
Native encryption is being looked at.
**Linked Servers and Distributed Queries are now supported, linking a SQL Database instance from an on-premises server. Linking two SQL Database instances is NOT supported.
#30: Slide Objectives:
Point out that 1) The same great technologies that developers use today on-premises works with SQL Database 2) high-level differences between on-premises and SQL Database 3) SQL Database features currently unsupported
Transition:
Creating, managing, and deploying a database in Microsoft Azure SQL Database isn’t difficult. The key is understanding the features that are supported and how SQL Database compares to on-premises SQL Server and the technologies that can be used with SQL Database.
Speaking Points:
The same great technologies that developers use today on-premises works with SQL Database, including developer languages, Frameworks, and Tools. Nothing new to learn!
SQL Server Comparison -> highlight the physical vs. logical administration. Developers and DBAs can now focus on things they love to do and not worry about the physical aspect.
Features unsupported by SQL Database -> Many of the unsupported features are hardware based and thus don’t need to be in SQL Database. Other features, such as encryption, are server-based and become a challenge in solving in a shared-environment.
Notes:
CLR is now supported: http://azure.microsoft.com/blog/2014/12/11/preview-available-for-next-generation-of-azure-sql-database/
Backup/Restore: PIT Coming; Import/Export can be used for backup to BLOB storage. Third-party backup products available via RedGate and Enzo.
Data can be stored encrypted but the encryption must be done at the application level.
Native encryption is being looked at.
**Linked Servers and Distributed Queries are now supported, linking a SQL Database instance from an on-premises server. Linking two SQL Database instances is NOT supported.
#31: Slide Objectives:
Highlight the set of tools for developers when interacting with Microsoft Azure SQL Database.
Transition:
Transition statement(s) to setup the slide
Speaking Points:
SQL Database Management Portal -> Cross Browser, Unified Management Experience
SQL Server Data Tools -> Integrated Database Design Environment, Table Designer, Debugging, T-SQL Editor
Notes:
IntelliSense in T-SQL Editor
SQL Server Data Tools
Strive to make it consistent as possible
Intersection with the cloud
Bridging you to the new cloud world
Consistency to the new developer experience
Consistency with the new cloud model
#32: Demo 3)
-- Generate Scripts
-- Deploy to SQL Azure ( There is a bug in UI Wizard for SQL Wizard)
#34: Speaker notes:
Elastic pools simplify the process of creating, maintaining, and managing both performance and cost for large numbers of Azure SQL databases.
Manage large numbers of databases that have unpredictable resource demands.
Ability to run centralized queries and reporting tools across database pool.
#36: Speaker notes:
Execute administrative tasks across each database
Don’t have to connect to each database independently in order to run T-SQL statements or perform other administrative tasks
For example, you can easily update the schema in every database to include a new table
Elastic database jobs handles the task of logging in, and reliably running the script for you, while logging the status of execution for each database
#38: Vertical: Change service-tiers for a given database as capacity needs fluctuate
Horizontal: Add or remove databases as more or less capacity is needed
Animation:
We start off with 3 basic databases
[click]: We can vertically scale one of these to a standard instance
[click]: We can also add more instances by scaling horizontally
[click]: If an instance need more headroom, we can always still vertically scale
#39: Now let’s focus on SQL Server in a Microsoft Azure Virtual Machine!
#43: Note: Full-Text Search now supported https://msdn.microsoft.com/library/ms142571.aspx
#45: Now let’s focus on the new Microsoft Azure DocumentDB Service!
#49: Demo 5)
What is Azure DocumentDB?
https://azure.microsoft.com/en-us/documentation/videos/what-is-azure-documentdb/
Create DocumentDB on Azure?
https://azure.microsoft.com/en-us/documentation/videos/create-documentdb-on-azure/
#50: Time for the Microsoft Azure Search as a Service offering!
#51: Azure Search is a fully managed search solution that allows developers to enable search experiences in applications.
#55: Now let’s focus on Hadoop in Azure known as Microsoft Azure HDInsight!
#61: Speaker notes:
Fully managed relational data warehouse-as-a-service.
Industry’s first elastic cloud data warehouse with enterprise-grade capabilities
Support your smallest to largest data sets
#64: Speaker notes:
It’s as an enterprise wide repository of every type of data collected in a single place prior to any formal definition of requirements or schema.
Data is be kept without discrimination regardless of its size, structure, or how fast it is ingested.
Organizations can then use Hadoop or advanced analytics to find patterns of the data.
Azure Data Lake can be part of your existing data platform by leveraging Azure Active Directory as well as providing data replication to ensure high durability and availability.
#65: Speaker notes:
HDFS for the Cloud: The Azure Data Lake is a Hadoop File System compatible with HDFS enabling Microsoft offerings such as Azure HDInsight, Revolution-R Enterprise, industry Hadoop distributions like Hortonworks and Cloudera all to connect to it.
Petabyte files, massive throughput: The goal of the data lake is to run Hadoop and advanced analytics on all your data to discover conclusions from the data itself.
Curated data: Azure Data Lake can also serve as a repository for lower cost data preparation prior to moving curated data into a data warehouse such as Azure Data Warehouse.
#66: There are other SQL Solutions you can choose to run in Azure. Official support exists for MySQL and Oracle.
(Good place to show the portal and that you can provision Oracle and MySQL databases in Azure just as easily as you can provision the Microsoft SQL options.
#68: As you can see there are a lot of options in the Microsoft Azure DataPlatform offerings. It may be a challenge to identify the most suitable options in every case but we can rest assured that there will be a good option for almost any scenario!