Be a part of the largest SQL Server professional gathering in Europe at SQL Bits 2019. At SQL Bits, you have the unique opportunity to meet with community leaders sharing their real world experience and Microsoft product teams providing deep insights into Microsoft data solutions.

For those attending this year, we’ve put together a quick guide below on some of the Data and AI sessions you can look forward to. Can’t wait until SQL Bits? Check out the conference sessions to get a taste of what you won’t want to miss at SQL Bits 2019.

SQL Bits is also running a promotion right now to share their love for data. Save 50% when you add an extra day using the code: welovedata

Keynote

Friday, March 1

Data Never Rests

Speaker: Buck Woody and Bob Ward

In today’s world, the growth of data is ushering in an era of rapid innovation. Microsoft’s goal is to bring the best hybrid data platform to help data professionals in building a data infrastructure that supports their organization now and into the future.  Join Buck Woody, Bob Ward, Anna Thomas, Alain Dormehl, and Adam Saxton as they demonstrate the latest advances from Microsoft across SQL Server, Azure Data Services, Business Analytics, and AI.

Pre-conference activities (training days)

Wednesday, February 27

Modernize your database with SQL Server 2019

Speaker: Bob Ward

Earlier in September, we announced SQL Server 2019 preview, the first release of SQL Server to create a unified data platform by packaging Apache Spark^TM and Hadoop Distributed File System (HDFS) together with SQL Server as a single, integrated solution. In this session, come join us for a deep dive into SQL Server 2019.

Building a modern database architecture with Azure

Speaker: Jes Borland

This session will review the key foundations of Azure and introduce various Azure database options like SQL Server MI, Azure SQL DB, Cosmos DB, etc.

Thursday, February 28

Microsoft SQL Server Big Data Clusters architecture

Speaker: Buck Woody

This session is a  deep dive into the concepts of big data analytics and data virtualization in SQL Server 2019. You will also learn about the architecture to enable machine learning to train your models within SQL Server 2019.

Data science from scratch with Azure Machine Learning

Speaker: Mithun Prasad

This will be a crash course to create data science solutions and apply machine learning algorithms to real world scenarios.

SELECT * FROM Azure Cosmos DB

Speaker: Theo van Kraay

This pre-conference session will provide in-depth training on Azure Cosmos DB. At the end of the training, you will be equipped to build your applications on Cosmos DB.

Deep dive into Azure Data Factory with SSIS

Speaker: Sandy Winarko

This session will focus on modernizing your extract, transform, and load (ETL) workloads with a deeper integration of SQL Server Integration Services (SSIS) in Azure Data Factory (ADF).

Highlighted sessions during the conference March 1st and 2nd

Inside SQL Server 2019

Speakers: Bob Ward, Buck Woody, Anna Thomas

Come learn all the new capabilities of SQL Server 2019 directly from the Microsoft engineering team.

What’s New – Query Performance Insights

Speaker: Pedro Lopes

Come and be a rockstar at troubleshooting query performance with all the latest innovations in intelligent query processing.

Hyperscale for Azure SQL DB   

Speaker: Kevin Farlee

In this session you’ll learn how the Hyperscale service tier in Azure SQL DB removes many of the practical limits traditionally seen in cloud.

A dive into the architecture that is Azure SQL DW Gen2. How does it work?

Speaker: Philip Beaumont, Neil Millington

Come learn how you can turbocharge your query performance and concurrency with a fully managed cloud data warehouse.

Getting intimate with the Power BI desktop

Speaker: Patrick LeBlanc, Adam Saxton

Join us in this session, where we will dive deep into the Power BI desktop.

Enterprise BI with Power BI Premium and SSAS

Speaker: Christian Wade

Join the two-part series to learn about the new features landing in SQL Server Analysis services and also learn how to use Power BI premium to create semantic models.

There are over 44 sessions from Microsoft data platform speakers, and we invite you to come hear from Microsoft and community experts at SQL Bits 2019.

The post Join us at SQL Bits 2019 February 27-March 2 in Manchester, UK! appeared first on Microsoft SQL Server Blog.

Hybrid connects all your data

Now more than ever, we are architecting for hybrid, because we are hearing from customers that they will be running data workloads on-premises and in the cloud – rarely just one or the other. We believe that the value Microsoft can add is to provide a great and consistent experience wherever they deploy.  One example of this commitment is Azure SQL Database Managed Instance, which was recently made generally available.  Managed Instance enables organizations to migrate their SQL Server workloads to Azure with zero code changes and offers an easy path to the cloud at an incredible value – and with security, intelligent performance and management tools that are unique to our cloud database services.  The end of extended support for SQL Server 2008 and 2008 R2 next year is a great opportunity for customers to rehost to Azure SQL Database Managed Instance, a fully-managed solution that eliminates the need for future upgrades. It’s easy to get there using comprehensive, yet easy-to use migration tools like Azure Database Migration Service.

Microsoft is excited to announce the general availability of Azure SQL Database Managed Instance Business Critical tier on December 1. Designed for mission-critical business apps with high I/O requirements, the business critical tier supports high availability with the highest level of storage and compute redundancy.  This new tier provides support for in-memory processing, a range of sizes up to 80 cores on Gen5, and zone-redundant HA using several isolated replicas to provide the highest resilience to failure.  We offer all this performance at an incredibly compelling price point—up to 85% less expensive than AWS.  Programs such as the Azure Hybrid Benefit, which allows customers to re-use their on-premises SQL Server licenses for discounts in Azure, and upcoming Reserved capacity pricing for Managed Instance Business Critical which allows you to prepay for a 1 or 3-year term commitment, further help you manage costs in the cloud.

In addition, we’re announcing a limited preview of Machine Learning services in Azure SQL Database. You can now use the Azure SQL Database support for Microsoft Machine Learning Services with R language to complete data processing, model training, and scoring all inside your SQL Database. This means you no longer need to move data out of the database to train and operationalize machine learning models. The R code can be deployed in production by embedding it in T-SQL stored procedures.

Azure is also a great destination for open source database migration. We recently announced an expansion to our relational OSS database managed service offerings with a preview of Azure Database for MariaDB. With MariaDB joining MySQL and PostgreSQL, Azure now offers the community versions of all the most popular OSS relational databases as managed services in the cloud, with advantages like built-in high availability, dynamic scaling and world-class security features.  When looking to migrate NoSQL databases like MongoDB and Cassandra to the cloud, Cosmos DB provides an excellent destination.  Customers gain access to managed NoSQL at a lower total cost of ownership (TCO) vs. on-premises and cloud competitors not to mention the industry leading SLA, global distribution, and features that take all the work out of DevOps. You can get started today by using the Azure Cosmos DB API of your choice to migrate NoSQL data and apps from MongoDB, Cassandra, Hbase, and more, using a free trial of Azure Cosmos DB.

With SQL Server 2019, organizations can now seamlessly manage their structured and unstructured data in a single, integrated solution. It comes with big data capabilities built-in, including support for Apache Spark^TM and Hadoop Distributed File System (HDFS)—everything you need to build a data lake with your SQL Server skills. Today we announce SQL Server 2019 community technology preview (CTP) 2.1 which has a number of new features for the database engine and big data clusters:

• Ability to deploy R and Python apps inside a SQL Server big data cluster
• Scalar UDF inlining feature in Intelligent query processing, optimizing a common performance problem scenario for User Defined Functions
• Derived table or view aliases in graph match queries
• Improved diagnostic data for long-running queries, helping to pinpoint when a query is blocked by stats background processing
• Ability to put buffer pool in persistent memory, dramatically speeding up I/O operations

And we have more planned for upcoming previews of SQL Server 2019, including Accelerated Data Recovery to speed up recovery processing, transaction rollback, readable secondaries, and adding availability groups for system databases which enables users to replicate linked server definitions, logins, and SQL Agent jobs to the secondary replicas.

Hybrid enables comprehensive AI and analytics

Having the most consistent data platform across on-premises and cloud enables us to offer AI and analytics over all your data. Azure SQL Data Warehouse is a cloud data warehouse that combines lightning fast query performance with advanced security features to turn all your data into actionable insights. Azure SQL Data Warehouse has been recognized as the fastest cloud data warehouse by third party benchmarks. Building upon its industry leading performance, today we announced significant security and usability updates. Customers can now take advantage of a new workload importance feature to influence query execution by priority, making sure high business value work gets first access to system resources. In addition, SQL Data Warehouse now offers native row level security, enabling customers to implement the most stringent security policies for fine-grained access control. Other new capabilities include support for SQL Server Data Tool, enhanced performance monitoring, advanced tuning and accelerated database recovery to significantly improve service usability. Learn more about this and other new features in today’s Azure SQL Data Warehouse blog. Experience the performance of Azure SQL Data Warehouse by creating your first data warehouse.

Azure SQL Data Warehouse also offers efficient and scalable structured streaming write support through native Azure Databricks connector. Azure Databricks is an Apache^® Spark™-based analytics platform that enables you to accelerate and simplify the process of building big data and AI solutions to drive the business forward, all backed by industry leading SLAs. We recently announced the preview of Azure Databricks Delta, a powerful transactional storage layer built on Apache Spark to provide better consistency of data and faster read access. Organizations also benefit from Azure Databricks’ native integration with other services like Azure Blob Storage, Azure Data Factory, and Azure Cosmos DB. This enables new analytics solutions that support modern data warehousing, advanced analytics, and real-time analytics scenarios.

Announced at Ignite, the Azure Data Explorer preview is a fast, highly scalable data exploration service for log and telemetry data. It helps you handle many data streams, so you can collect, store, and analyze data. Azure Data Explorer is ideal for analyzing large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. Azure Data Explorer makes it simple to ingest this data and enables you to perform complex ad-hoc queries on the data in seconds.  Today at PASS, we’re excited to host one of our customers, Taboola, to demonstrate how their organization is using Azure Data Explorer to analyze web data in near real time, crunching large amounts of web data in order to provide the best content recommendations to webpage readers – all in real time.

Customers who want to stream data or analyze in real-time to get valuable insights faster need a massively scalable, distributed, event-driven messaging platform with multiple producers and consumers. Apache Kafka and Azure Event Hubs provide such distributed platforms.  Azure Event Hubs for Apache Kafka, now generally available, provides a Kafka endpoint that can be used by your existing Kafka-based applications as an alternative to running your own Kafka cluster. With Event Hubs for Kafka, you get the best of both worlds—the ecosystem and tools of Kafka, along with Azure’s security and global scale—in a fully managed solution.

Experience your data

Microsoft’s Business Intelligence (BI) tools are evolving as well. Power BI already includes robust self-service data preparation capabilities in Power BI Desktop through the familiar Power Query based experiences that are used by millions of users worldwide. With the new public preview of dataflows in Power BI, we’re taking self-service data preparation to the next level, enabling business analysts to create data preparation logic that can be reused across multiple Power BI reports and dashboards and linked together to create sophisticated data transformation pipelines. Dataflows can be configured to store the data in the customer’s Azure Data Lake Storage Gen2 instance, and dataflows support the Microsoft Common Data Model, giving organizations the ability to leverage a standardized and extensible collection of data schemas (entities, attributes, and relationships).

For our long-time BI customers with investments in SQL Server Reporting Services, with the public preview today, you can include pixel-perfect paginated reports alongside to Power BI’s existing interactive reports. This provides a unified, secure, enterprise-wide reporting platform accessible to any user across devices. You can read more about these innovations in a blog from Arun Ulagaratchagan, General Manager, Power BI Engineering.

Getting started

In conclusion, I’m excited to share with you that hybrid is here:  Microsoft’s consistent data platform across on-premises and cloud connects all your data and makes intelligence over all your data possible. We are proud to provide customers with the widest range of options to run SQL on Azure at the best price.  And our best-of-breed data analytics options bring AI to all your data.

•  If you’d like to watch my talk at PASS, you can sign in on the PASS website.  Registration is free and sessions the keynote content starts at 8:15 AM Pacific.
•  If you’re ready to get started, here are a few great places to get going:
  • Learn more about SQL Server 2019
  • Get started on your migration with a free trial of Azure Services, including Azure SQL Database

The post Harness the future with the ultimate hybrid platform for data and AI appeared first on Microsoft SQL Server Blog.

SQL Server

Build modern applications using the language of your choice, on-premises and in the cloud, now on Windows, Linux, and Docker containers.

• Prepare for Windows Server 2008 and SQL Server 2008 End of Support
  Support for SQL Server 2008/ 2008 R2 and Windows Server 2008 will end in July 2019 and January 2020, respectively, which means you’ll no longer receive security patches for these versions. When you join this session, you’ll learn how to migrate your applications and data, avoid business disruptions, and adopt the most current security technologies. You will also receive guidance for your migration and find resources to help you move quickly.

Azure Database services for PostgreSQL and MySQL

Azure Database Services for PostgreSQL and MySQL provide fully managed, enterprise-ready community PostgreSQL/MySQL database as a service. These community editions help you easily lift and shift to the cloud, using languages and frameworks of your choice. On top of that, you get built-in high availability and capability to scale in seconds, helping you easily adjust to changes in customer demands.

• How Open Source Database engines help you migrate to Azure
  Learn how to take advantage of fully managed, enterprise-ready PostgreSQL and MySQL community database engines. Join us as we cover how to use Azure Database Migration Service and what incentives are in place to help you in your migration journey.

Azure Cosmos DB

Azure Cosmos DB offers the first globally distributed, multi-model database service for building planet-scale apps.

• Controlling your application experience with Azure Cosmos DB’s consistency models
  The ability to control your application experience by changing your consistency model has been lacking—until now. Azure Cosmos DB offers five well-defined and preconfigured consistency models, helping you navigate the tradeoffs between data consistency and app availability. In this session, learn the key differences between the five consistency models, which applications are best suited for each model and how to configure the models to ensure high performance.

Big Data and analytics

Deliver better experiences and make better decisions by analyzing massive amounts of data in real time. Get the insight you need to deliver intelligent actions that improve customer engagement, increase revenue, and lower costs.

• Making R-based analytics easier and more scalable
  R is an increasingly popular programming language for running predictive analytics workloads. If you are looking to scale out R-based advanced analytics to big data, Azure Databricks starts in seconds, integrates with RStudio, and automatically executes R workloads at unprecedented scale across single or multiple nodes. Join us to see how to get the ideal dataset for your needs and a detailed demonstration of the entire solution.

The post Cloud data and AI services training roundup August 2018 appeared first on Microsoft SQL Server Blog.

SQL Server 2017

Whether on Windows, Linux, or Docker containers, you have the flexibility of leveraging SQL Server 2017’s industry-leading performance and security wherever you like. Here’s a rundown of recent and upcoming training sessions to help you learn more.

• Complying with GDPR on Microsoft SQL-based technologies

Extended support for SQL Server 2008 and 2008 R2 is coming to an end on July 9, 2019, which means it’s time to choose your path to modernization. Without support, security updates will no longer be available, and you may run the risk of non-compliance with industry regulations such as GDPR (General Data Protection Regulation). Join this detailed training session on demand to understand how to begin your migration journey today.

• Move your transactional workloads to the cloud with Azure SQL Database

Moving your on-premises database to the cloud has never been easier. Join this demo-filled training to learn how Azure SQL Database helps you unlock the potential of your database (and your people) without changing your application architecture. Specifically, we cover how to use built-in intelligence for enabling high performance and security, building reports into your apps to drive customer value, and management of emerging application requirements.

Artificial Intelligence (AI)

Infuse your apps, websites, and bots with intelligent algorithms to see, hear, speak, understand, and interpret your user needs through natural methods of communication. The Microsoft AI platform offers a comprehensive set of flexible AI services for any scenario and enterprise-grade AI infrastructure that runs AI workloads anywhere at scale.

• Introduction to Custom Vision Service

If you are looking to easily customize your own state-of-the-art computer vision models that fit perfectly with your unique use cases, this session is for you. Join us for the 60-minute demo-rich training to learn more about Microsoft’s Custom Vision Service, a tool for building custom image classifiers. In addition to an overview of the tool, you’ll learn to use labeled images to teach Custom Vision Service the concepts you want it to learn and to use simple REST API calls to quickly tag images with your new custom computer vision model.

Azure Cosmos DB

Azure Cosmos DB offers the first globally distributed, multi-model database service for building planet-scale apps.

• Azure Cosmos DB Technical Training Series

Engineering experts are leading a seven-part technical training series on Azure Cosmos DB, complete with interactive Q&As. In addition to technical deep dives, this series covers a wide array of topics. Join the series to learn to build serverless applications and conduct real-time analytics using Azure Cosmos DB, Azure Functions, and Spark. Attend the entire series (past sessions are available on demand) to become an Azure Cosmos DB guru, or simply register for the sessions that interest you.

The post Cloud data and AI services training roundup appeared first on Microsoft SQL Server Blog.

Join us for one or all of these training sessions for a deep dive into a variety of topics, including products like SQL Server 2017, Azure SQL Database, and Azure Cosmos DB, along with Microsoft innovations in artificial intelligence, advanced analytics, and big data.

SQL Server 2017

It’s all about choice. Now, you have the flexibility of leveraging SQL Server 2017’s industry-leading performance and security wherever you like—whether that’s on Windows, Linux, or Docker containers. We’re hosting two training sessions this month to help you learn more about the many exciting features of SQL Server 2017.

Industry-leading performance and security with SQL Server 2017
In this webinar, learn more about innovative SQL Server 2017 features that enhance your applications, analytics, and business intelligence (BI) workloads, including:

• Automated tuning features such as Adaptive Query Processing and Automatic Plan Correction for faster, more consistent performance.
• Advanced security features such as encryption at rest and in use, dynamic data masking, and row-level security.
• The ability to store and query graph data along with your existing SQL Server tables.
• In-database advanced analytics using R and Python machine-learning services.

Running SQL Server on Linux in Azure, AWS, and Google Cloud Platform
In addition to a comprehensive set of features and flexibility of their preferred platform or programming languages, customers want flexibility when it comes to their choice of underlying infrastructure. This includes both the underlying OS as well as the platform. In this in-depth training, we’ll cover:

• The different ways you can run your SQL Server 2017 on Linux workloads in the cloud. We’ll discuss what our Azure infrastructure enables, but also what other public or private cloud providers are offering.
• How you can leverage the Azure Infrastructure to enable new SQL Server 2017 on Linux scenarios.
• Demos of SQL Server 2017 on Linux in Azure, AWS, and the Google Cloud Platform.

Azure Cosmos DB

Engineering experts are leading a seven-part training series on Azure Cosmos DB, complete with interactive Q&As. In addition to a high-level technical deep dive, this series covers a wide array of topics, including:

• Graph API
• Table API
• Building Mongo DB apps

By the end of this series, you’ll be able to build serverless applications and conduct real-time analytics using Azure Cosmos DB, Azure Functions, and Spark. Attend the whole series to become an Azure Cosmos DB guru, or just register for the sessions that interest you. Learn more.

Artificial Intelligence (AI)

Learn to create the next generation of applications—spanning an intelligent cloud as well as an intelligent edge powered by AI. Microsoft offers a comprehensive set of flexible AI services for any scenario and enterprise-grade AI infrastructure that runs AI workloads anywhere at scale. Modern AI tools designed for developers and data scientists help you create AI solutions easily, with maximum productivity.

Unlock deeper learning with the new Microsoft Cognitive Toolkit
Data is powerful, but navigating it can be slow, unreliable, and overly complex. Join us to learn about the Microsoft Cognitive Toolkit—offering deep-learning capabilities that allow you to enable intelligence within massive datasets. In this session, you’ll learn:

• What’s new with the Microsoft Cognitive Toolkit.
• How to maximize the programming languages and algorithms you already use.
• Cognitive Toolkit features, including support for ONNX, C#/.NET API, and model simplification/compression.

Filter content at scale with Cognitive Services’ Content Moderator
Learn how Azure Cognitive Services’ Content Moderator filters out offensive and unwanted content from text, images, and videos at scale. By combining intelligent machine-assisted technology with an intuitive human review system, Content Moderator enables quick and reliable content scanning. In this training, you’ll learn:

• Content Moderator platform basics.
• How to use the machine learning-based APIs
• How to easily integrate human review tools with just a few lines of code.

Advanced Analytics and Big Data

Data volumes are exploding. Deliver better experiences and make better decisions by analyzing massive amounts of data in real time. By including diverse datasets from the start, you’ll make more informed decisions that are predictive and holistic rather than reactive and disconnected.

Accelerate innovation with Microsoft Azure Databricks
Learn how your organization can accelerate data-driven innovation with Azure Databricks, a fast, easy-to-use, and collaborative Apache Spark-based analytics platform. Designed in collaboration with the creators of Apache Spark, it combines the best of Databricks and Azure to help you accelerate innovation, with one-click set up, streamlined workflows, and an interactive workspace that enables collaboration among data scientists, data engineers, and business analysts. In this session, you’ll learn how to:

• Use Databricks Notebooks to unify your processes and instantly deploy to production.
• Launch your new Spark environment with a single click.
• Integrate effortlessly with a wide variety of data stores.
• Improve and scale your analytics with a high-performance processing engine optimized for the comprehensive, trusted Azure platform.

The post Cloud data and AI services training roundup appeared first on Microsoft SQL Server Blog.

In this session Rohan Kumar, General Manager, Data Systems Group, discusses all the latest news — from upcoming SQL Server 2017 general availability, to the new Azure Hybrid Benefit for SQL Server, to serverless computing with Azure Cosmos DB and Azure Functions. Hear how to take your SQL Server Integration Services to the cloud with Azure Data Factory’s new hybrid functionality, plus learn about the latest performance and scale enhancements for Azure Data Services. This 75-minute session is packed with demonstrations and customer testimonials from the likes of ASOS, Caradigm, and dv01.

Join us now:

• Watch the Data Platform general session on SQL Server 2017 and Azure Data Services
• See other Microsoft Ignite 2017 sessions on-demand
• Learn more about SQL Server 2017

The post View on-demand: Microsoft Data Platform – SQL Server 2017 and Azure Data Services appeared first on Microsoft SQL Server Blog.

Welcome to Microsoft Ignite 2017! I hope you are able to join us in person, or virtually through the Ignite Live Stream, to hear our exciting product announcements for your Data Estate.

• As Scott Guthrie wrote, today we announced general availability of SQL Server 2017, coming October 2! This is an incredible milestone representing the first version of SQL Server to run on Windows Server, Linux and Docker—and it already has been pulled on Docker X 2 million times since November.
• We also announced the upcoming public preview of SQL Database Managed Instance and Azure Database Migration Service previews, along with the addition of SQL Server to Azure Hybrid Benefit. The new Azure Hybrid Benefit for SQL Server enables customers to use on-premises SQL Server licenses for the easiest lift and shift of SQL Server workloads to fully-managed cloud.
• For developers looking to drive highly customized experiences based on events in a serverless architecture, we also announced support for Azure Functions with Azure Cosmos DB.
• To simplify analytics in the cloud, we’re releasing a public preview of new hybrid data integration capabilities in Azure Data Factory including the ability to run SSIS packages within the service.
• Finally, dramatic scale investments are coming to Azure SQL Data Warehouse for double the performance and 5x the scale.

This afternoon, I’ll be speaking in the Data General Session about the investments Microsoft has made across our Data and Analytics portfolio. From key announcements about the availability of SQL Server 2017 on Linux and Docker, to innovative programs that let you use on-premises SQL Server licenses to easily lift and shift to the cloud, to great price and performance for analytics workloads in Azure, we have lots of ways to help you unleash the power of your data, across the entire Data Estate. You’ll also get to hear from customers who have come with us on this journey, and whose investments in data and analytics have led to out-innovating and out-performing their competition.

Let’s take a look at some of the products and features you’ll hear more about.

SQL Server 2017 on Linux and Docker

With SQL Server 2017, we’ve made huge strides of choice for the data platform, and one of the heroes of our new choice paradigm is SQL Server 2017. Starting next Monday, October 2, customers will be able to bring the industry-leading performance and security of SQL Server to Linux and Docker Enterprise Edition containers for production workloads. SQL Server 2017 delivers a mission-critical database with everything built-in, on the platform of your choice. And, it can unlock seamless DevOps with Docker Enterprise Edition containers, bringing efficiency and simplicity to your innovation. As one customer reported:

“The Linux switchover was very easy. We didn’t have to do anything custom for Azure. It was literally plug and play,” said Dean Chen, VP of Engineering for dv01.

Today we are also announcing a SQL Server on Red Hat Enterprise Linux offer to help with upgrades and migrations. This offer provides up to 30% off SQL Server 2017 through an annual subscription. When customers purchase new Red Hat Enterprise Linux (RHEL) to support their SQL Server, they will be eligible for another 30% off their operating system. In addition to discounts on SQL Server and Red Hat Enterprise Linux, all of this is backed by integrated support from Microsoft and Red Hat.

Upgrading now to SQL Server 2017 will get you access to these cool features:

• AI built-in, with R and Python analytics plus native scoring in T-SQL – SQL Server was the first commercial database to have AI built-in. SQL Server 2017 enables you to build intelligent apps using scalable, parallelized and highly performant analytics using both R and now Python. New native scoring in T-SQL lets you score in near real-time.
• SQL Server 2017 will enable customers to use graph data management and analysis in order to discover new kinds of relationships. You can track and analyze highly interconnected data, for uses like detecting financial fraud or understanding pharmaceutical drug interactions.
• Adaptive Query Processing is a new family of features in SQL Server that bring intelligence to database performance. Adaptive Memory Grants in SQL Server track and learn from how much memory is used by a given query over time to avoid over- or under-provisioning memory and spilling to disk, a situation that can negatively affect performance. The more you run your application, the smarter this feature gets. Automatic Plan Correction ensures continuous performance by finding and fixing performance regressions.
• The newly renamed Machine Learning Server for Hadoop, formerly R Server, brings R and Python based scalable analytics to Hadoop and Spark environments, and it is now available to all SQL Server Enterprise Edition customers as a Software Assurance benefit.
• SQL Server Enterprise edition software assurance benefits also enable you to run Power BI Report Server. Power BI Report Server enables a truly hybrid reporting and dashboard experience by allowing you to manage your SQL Server Reporting Services (SSRS) reports alongside your Power BI reports

Easy lift and shift to the cloud with Azure SQL Database Managed Instance and Azure Hybrid Benefit

With Microsoft’s cloud-first development principle, you’ll find many of these same advances in our database-as-a-service: Azure SQL Database brings your workloads industry-leading performance and security, all on the same core engine as SQL Server.

With intelligent features like Threat Detection and auto-tuning built-in, Azure SQL Database offers the most productive database service, ideal for managing and modernizing data estate with thousands of databases — delivering a 406% ROI¹ to organizations. Today, we are announcing the upcoming public preview for SQL Database Managed Instance, an expansion to the service which offers close to full compatibility with SQL Server — ideal for migrating database estate to Azure for hassle-free operations. We are also announcing an upcoming public preview for Azure Database Migration Service which will streamline the movement of databases to Azure including SQL Server to Azure SQL Database. But we aren’t stopping there. We will make Azure the most economical and logical choice for existing SQL Server customers with the addition of Azure Hybrid Benefit for SQL Server, a way to re-use on-premises SQL Server licenses to run database-as-a-service in Azure. Azure Hybrid Benefit offers customers big savings compared to moving to other public clouds.

“We wanted the best of what we do in our data center, which is reliable SQL Servers on flash storage. With the best of what Azure could bring to it…For us we found Azure SQL Database was the best way to do it. We deploy our SQL Server’s schema element into a Managed Instance and we point the application via connection string change directly over the managed instance. We basically picked up our existing infrastructure and were able to deploy to Azure within a few seconds. It allows us to scale the business very quickly, with very minimal effort. The holy grail in a move like this is being able to lift your existing platform, move it into Azure without significant amounts of work, without having to re-engineer things,” said Eric Fleischman, Vice President & Chief Architect of DocuSign.

In addition to making it easier than ever to move to Azure SQL Database, we’re building in new capabilities that make it more compelling than ever to move. SQL Database has new Machine Learning Services for R language advanced analytics, a service that provides a platform for building and deploying intelligent applications in the cloud. And we’re adding other capabilities that leverage SQL Database’s cloud architecture: Intelligent Insights provide automated monitoring at scale and detection of any database performance degradations, faster than possible with traditional means. Not only that the issue is detected, but a root cause analysis is provided to the user, to easily decide on the best way to mitigate problems. With the new Vulnerability Assessment, customers can proactively improve the security state of their database. They get visibility into their security settings and vulnerabilities, and concrete steps to resolve issues and lock down security settings – an important issue if you’re subject to EU General Data Protection Regulation (GDPR) regulations.

Data Analytics at scale in the cloud with Azure Data Factory and Azure SQL Data Warehouse

We are helping customers transform with analytics and AI through faster performance, reduced time to value, and intelligence that can redefine customer interactions. With cloud-first innovation, you get a superset of business intelligence and analytics features that work across your entire Data Estate – on-premises and in the cloud.

Azure Data Factory is a data integration service that now lets you create, schedule, and orchestrate data integration pipelines at scale wherever your data lives, in the cloud or on premises. You can meet security and compliance needs for your data while taking advantage of Azure Data Factory’s extensive orchestration and data movement capabilities while paying only for what you use.

Now in public preview, SQL Server Integration Services (SSIS) customers can easily lift SSIS packages into the cloud using new managed SSIS hosting capabilities in Data Factory. Coming soon, customers who have active SQL Server license on SQL Server will be able to take advantage of the Azure Hybrid Benefit for SQL Server to receive discounted rates on SSIS execution in Data Factory.

Customers are already using these new features to speed data integration. Said David B. McAuley, CTO for Lumedx, “Azure Data Factory has simplified the integration of data from multiple hybrid sources at scale and enabled us to leverage big data and analytics offerings in Azure to drive better health outcomes for our customers.”

Azure SQL Data Warehouse is a fully-managed, petabyte-scale cloud data warehouse based on SQL Server. Soon we’ll preview a new performance tier that offers 2x the performance and 5x the scale of the current performance tier. This new compute-optimized performance tier leverages the latest Azure hardware with data caching through low-latency Non-Volatile Memory Express (NVMe)-based solid-state disks for the most demanding data warehouse workloads. You are also able to store an unlimited amount of columnar data with each data warehouse. These benefits of increased performance and scale are offered while retaining the ability to pause, resume and dynamically scale your data warehouse to achieve the lowest possible cost.

Finally, you’re probably familiar with how Power BI has been revolutionizing self-service business intelligence, revealing the information stored within your analytics using powerful visualizations. Power BI works across locations and devices to put BI in the hands of all your users. With Power BI Report Server, announced this past May, you can now run Power BI reports on-premises! This unlocks the deployment and distribution of interactive Power BI reports – and traditional paginated reports – completely within the boundaries of the organization’s firewall. Power BI Report Server extends the hybrid BI experience by allowing you to build on your on-premises reporting infrastructure while maintaining compatibility with Power BI to ensure a natural transition when you are ready to move to the cloud. And because Power BI Report Server is built on the proven SQL Server Reporting Services technology, it is fully compatible with SSRS. So, you can take advantage of SSRS capabilities when you deploy Power BI Report Server. Power BI Report Server is included with the purchase of Power BI Premium and available as a Software Assurance benefit for SQL Server Enterprise customers.

Build serverless apps with near infinite global-scale with new support for Azure Functions in Azure Cosmos DB

Finally, only Microsoft offers a complete development, application, and data platform that enables developers to build the next-generation of applications that will enrich the world around us. At Ignite, we continue this journey with new support for Azure Functions in Azure Cosmos DB which will dramatically streamline a developer’s ability to build globally distributed apps in a serverless architecture. These capabilities enable developers to build rich, real-time customer experiences based on data and events, with minimal infrastructure overhead. Azure Cosmos DB offers turnkey global distribution across Azure regions and guarantees performance, with single-digit-millisecond latencies at the 99th percentile anywhere in the world. Its multiple consistency models help fine-tune performance for your application, and guaranteed high availability is backed by industry-leading, comprehensive service level agreements (SLAs). And now, you can try it for free!

Join us

Ready to hear more? Please join me at this afternoon’s Data General Session and for the other exciting sessions in the Ignite Data track. We’ll have lots of advice and ideas help you unleash the power of your data.

• Watch Microsoft Ignite keynotes online at the Live Stream
• Search Microsoft Ignite Data sessions
• Learn more about data in Microsoft Azure
• Get started with SQL Server 2017 on Windows, Linux and Docker

¹ “The Business Value of Microsoft Azure SQL Database Services” IDC, March 2015.

The post Microsoft for the Modern Data Estate appeared first on Microsoft SQL Server Blog.

This week at the annual Microsoft Build conference, we are discussing how, more than ever, organizations are relying on developers to create breakthrough experiences. With big data, cloud and AI converging, innovation & disruption is accelerating to a pace never seen before. Data is the key strategic asset at the heart of this convergence. When combined with the limitless computing power of the cloud and new capabilities like Machine Learning and AI, it enables developers to build the next generation of intelligent applications. As a developer, you are looking for faster, easier ways to embrace these converging technologies and transform your app experiences.

Today at Build, we made several product announcements, adding to the recent momentum announced last month at Microsoft Data Amp, that will help empower every organization on the planet with data-driven intelligence. Across these innovations, we are pursuing three key themes:

1. Infusing AI within our data platform
2. Turnkey global distribution to push intelligence wherever your users are
3. Choice of database platforms and tools for developers

Infusing AI within our data platform

A thread of innovation you will see in our products is the deep integration of AI with data. In the past, a common application pattern was to create machine learning models outside the database in the application layer or in specialty statistical tools, and deploy these models in custom built production systems. This results in a lot of developer heavy lifting, and the development and deployment lifecycle can take months. Our approach dramatically simplifies the deployment of AI by bringing intelligence into existing well-engineered data platforms through a new extensibility model for databases.

SQL Server 2017

We started this journey by introducing R support within the SQL Server 2016 release and we are deepening this commitment with the upcoming release of SQL Server 2017. In this release, we have introduced support for a rich library of machine learning functions and introduced Python support to give you more choices across popular languages. SQL Server can also leverage GPU accelerated computing through the Python/R interface to power even the most intensive deep learning jobs on images, text and other unstructured data. Developers can implement GPU accelerated analytics and very sophisticated AI directly in the database server as stored procedures and gain orders of magnitude higher throughput.

Additionally, as data becomes more complex and the relationships across data are many-to-many, developers are looking for easier ways to ingest and manage this data. With SQL Server 2017, we have introduced Graph support to deliver the best of both relational and graph databases in a single product, including the ability to query across all data using a single platform.

We have made it easy for you to try SQL Server with R, Python, and Graph support today whether you are working with C#, Java, Node, PHP, or Ruby.

Azure SQL Database

We’re continuing to simultaneously ship SQL Server 2017 enhancements to Azure SQL Database, so you get consistent programming surface area across on-premises and cloud. Today, I am excited to announce the support for Graph is also coming to Azure SQL Database so you can also get the best of both relational and graph in a single proven service on Azure.

SQL Database is built for developer productivity with most database management tasks built-in. We have also built AI directly into the service itself, making it an intelligent database service. The service runs millions of customer databases, learns, and then adapts to offer customized experiences for each database. With Database Advisor, you can choose to let the service learn your unique patterns and make performance and tuning recommendations or automatically take action on your behalf. Today, I am also excited to announce general availability of Threat Detection, which uses machine learning around the clock to learn, profile and detect anomalous activity over your unique database and sends alerts in minutes so you can take immediate action versus what historically can take an organization days, months, or years to discover.

Also, we are making it even easier for you to move more of your existing SQL Server apps as-is to Azure SQL Database. Today we announced the private preview for a new deployment option within the service, Managed Instance—you get all the managed benefits of SQL Database and now at the instance level which offers support for SQL Agent, three-part names, DBMail, CDC and other instance-level capabilities.

To streamline this migration effort, we also introduced a preview for Azure Database Migration Service that will dramatically accelerate the migration of on-premises third-party and SQL Server databases into Azure SQL Database.

Eric Fleischman, Vice President & Chief Architect from DocuSign notes, “Our transaction volume doubles every year. We wanted the best of what we do in our datacenter…with the best of what Azure could bring to it. For us, we found that Azure SQL Database was the best way to do it. We deploy our SQL Server schema elements into a Managed Instance, and we point the application via connection string change directly over to the Managed Instance. We basically picked up our existing build infrastructure and we’re able to deploy to Azure within a few seconds. It allows us to scale the business very quickly with minimal effort.”

Learn more about our investments in Azure SQL Database in this deeper blog.

Turnkey global distribution to push intelligence wherever your users are

With the intersection of mobile apps, internet of things, cloud and AI, users and data can come from anywhere around the globe. To deliver transformative intelligent apps that support the global nature of modern applications, and the volume, velocity, variety of data, you need more than a relational database, and more than a simple NoSQL database. You need a flexible database that can ingest massive volumes of data and data types, and navigate the challenges of space and time to ensure millisecond performance to any user anywhere on earth. And you want this with simplicity and support for the languages and technologies you know.

I’m also excited to share that today, Microsoft announced Azure Cosmos DB, the industry’s first globally-distributed, multi-model database service. Azure Cosmos DB was built from the ground up with global distribution and horizontal scale at its core – it offers turn-key global distribution across any number of Azure regions by transparently scaling and distributing your data wherever your users are, worldwide. Azure Cosmos DB leverages the work of Turing award winner Dr. Leslie Lamport, PAXOS algorithm for distributed systems and TLA+ a high-level modeling language. Check out a new interview with Dr. Lamport on Azure Cosmos DB.

Azure Cosmos DB started as “Project Florence” in 2010 to address developer the pain-points faced by large scale applications inside Microsoft. Observing that the challenges of building globally distributed apps are not a problem unique to Microsoft, in 2015 we made the first generation of this technology available to Azure developers in the form of Azure DocumentDB. Since that time, we’ve added new features and introduced significant new capabilities.  Azure Cosmos DB is the result.  It is the next big leap in globally distributed, at scale, cloud databases.

Now, with more innovation and value, Azure Cosmos DB delivers a schema-agnostic database service with turnkey global distribution, support for multiple models across popular NoSQL technologies, elastic scale of throughput and storage, five well-defined consistency models, and financially-backed SLAs across uptime, throughput, consistency, and millisecond latency.

“Domino’s Pizza chose Azure to rebuild their ordering system and a key component in this design is Azure Cosmos DB—delivering the capability to regionally distribute data, to scale easily, and support peak periods which are critical to the business. Their online solution is deployed across multiple regions around the world—even with the global scaling they can also rely on Azure Cosmos DB millisecond load latency and fail over to a completely different country if required.”

Learn more about Azure Cosmos DB in this deeper blog.

Choice of database platforms and tools for developers

We understand that SQL Server isn’t the only database technology developers want to build with. Therefore, I’m excited to share that today we also announced two new relational database services; Azure Database for MySQL and Azure Database for PostgreSQL to join our database services offerings.

These new services are built on the proven database services platform, which has been powering Azure SQL Database, and offers high availability, data protection and recovery, and scale with minimal downtime—all built-in at no extra cost or configurations. Starting today, you can now develop on MySQL and PostgreSQL database services on Azure. Microsoft is managing the MySQL and PostgreSQL technology you know, love and expect but backed by an enterprise-grade, highly available and fault tolerant cloud services platform that allows you to focus on developing great apps versus management and maintenance.

“Each month, up to 2 million people turn to the GeekWire website for the latest news on tech innovation. Now, GeekWire is making news itself by migrating its popular WordPress site to the Microsoft Azure platform. Kevin Lisota, Web Developer at GeekWire notes, “The biggest benefit of Azure Database for MySQL will be to have Microsoft manage and back up that resource for us so that we can focus on other aspects of the site. Plus, we will be able to scale up temporarily as traffic surges and then bring it back down when it is not needed. That’s a big deal for us.”

Learn more about these new services and try them today.

Azure Data Lake Tools for Visual Studio Code (VSCode)

Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. Additionally, Azure Data Lake includes a set of cognitive capabilities built-in, making it seamless to execute AI over petabytes of data. On our journey to make it easier for every developer to become an AI and data science developer, we are investing in bringing more great tooling for data into the tools you know and love.

Today, I’m excited to announce General Availability of Azure Data Lake Tools for Visual Studio Code (VSCode) which gives developers a light but powerful code editor for big data analytics. The new Azure Data Lake Tools for VSCode supports U-SQL language authoring, scripting, and extensibility with C# to process different types of data and efficiently scale any size of data. The new tooling integrates with Azure Data Lake Analytics for U-SQL job submissions with job output to Azure Data Lake Analytics or Azure Blob Storage. In addition, U-SQL local run service has been added to allow developers to locally validate scripts and test data. Learn more and download these tools today.

Getting started

It has never been easier to get started with the latest advances in the intelligent data platform. We invite you to watch our Microsoft Build 2017 online event for streaming and recorded coverage of these innovations, including SQL Server 2017 on Windows, Linux and Docker; scalable data transformation and intelligence from Azure Cosmos DB, Azure Data Lake Store and Azure Data Lake Analytics; the Azure SQL Database approach to proactive Threat Detection and intelligent database tuning; new Azure Database for MySQL and Azure Database for PostgreSQL. I look forward to a great week at Build and your participation in this exciting journey of infusing AI into every software application.

The post Serving AI with data: A summary of Build 2017 data innovations appeared first on Microsoft SQL Server Blog.