Tags
Search
Conference
One of the last technical challenges of cloud adoption is right security configuration. This session focuses on Azure Sql PaaS, covers governance, risk management and compliance and provides 8-step process for securing public cloud.
A technical overview of Azure SQL Data Warehouse Gen 2. SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.
Within Azure we have a rich ecosystem of AI services that can be leveraged to gain new insights into your data. This session will give you an easy to digest breakdown of the key services that matter and how to approach each one. Cognitive Services, Bot Framework, Azure Machine Learning Studio, Databricks, Notebooks, the Azure ML SDK for Python and the Azure ML Service
Tabular Editor, an open source tool for authoring Tabular Models, makes it easier for teams of developers to work on the same model simultaneously. It also provides functionality for automated build and deployment. In short, DevOps for SSAS Tabular.
Azure offers a comprehensive set of big-data solutions that help you gather, store, process, analyse and visualise data of any variety, volume or velocity, so you can discover new opportunities and take quick action. In this overview session, we’ll look at the various components within Azure that make up the Modern Data Warehouse, enable Real-Time Analytics, and support Advanced Analytics scenarios. You should leave with a high level understanding of the capabilities and limitations of each of the products within the Azure Analytics portfolio.
Find out how a major UK hotel chain unified their wildly different sources of data to build a supercharged analytics and pricing engine to power their business. Find out how Cosmos and Databricks helped them get to know their customers, how best to retain them, and how best to keep them happy, all while ensuring GDPR compliance and the right to be forgotten.
Do you want to know why customers chose Cosmos DB? Come learn about the business goals and technical challenges faced by real world customers, and learn about key Cosmos DB features so you can help your customers deliver their high-performance business-critical applications on Cosmos DB.
We will review this new feature of ADFv2, do deep dive to understand the mentioned techniques, compare them to SSIS and/or T-SQL and learn how modelled data flow runs Scala behind the scenes.
See how to analyze images in your Data Lake with Azure Data Lake Analytics, U-SQL and custom models
Azure Databricks support both Classic and Deep Learning ML Algorithms to analyse Large DataSets at scale. The Integrated Notebook experience gives the Data Scientists and Data Engineers to do exploratory Data Analysis, also feels like native to Jupyter notebook users. In this session we will extract intelligence from Higgs Dataset (Particle Physics) by running Classic and Deep Learning models using Azure Databricks. We will also peek into AMl service's integration with Azure Databricks for managing the end-to-end machine learning lifecycle.
Azure Machine Learning is a platform for developing and deploying your machine learning models on Azure. We will look at the life cycle of ML projects: from data, to model, to consumption. This will include Automated Machine Learning capabilities.
Managed Instances can make your cloud migrations simpler, but have their own nuances. Learn about what you need to know to manage this new platform.
Learn in 75 Minutes what Batch Execution Mode is, when & how it will affect your workloads (in upcoming SQL Server 2019 & Azure SQLDB) on the traditional Rowstore Indexes.
Join me in this session and learn how to capture a production workload, replay it to your cloud database and compare the performance. I will introduce you to the methodology and the tools to bring your database to the cloud without breaking a sweat.
This session presents how to migrate, replicate, and synchronize data between SQL Server, SQL VM, Azure SQL Database, and Azure SQL Database Managed Instance, across on-premises, Microsoft Azure, and other cloud platforms to build a real hybrid data platform. We introduce our current technology choices, deep dive in customer scenarios, and use cases, and share product roadmap.
Azure offers a wide range of services that can be combined into a BI solution in the cloud.
In this session, we’ll look at the different options within the Cognitive Services suite, show you how to connect to the APIs using Python code, walk through a live bot demo, and build an Azure Cognitive Search index. You should leave this session feeling like you’ve had a jump start to further your AI developer skill set.
If you have already mastered the basics of Azure Data Factory (ADF) and are now looking to advance your knowledge of the tool this is the session for you.
Paginated reports (SSRS), are available in both on-premises and cloud-based solutions. Join this session to experience the journey of SSRS and how to create and deploy reports across all the different products available in the Microsoft Ecosystem.
Azure offers a vast comprehensive data estate! While this is great for enabling users to pick the right tools for the right job - this has also increased the surface area for understanding how to integrate a vast number of components. In this session, we will show off the plug and play nature of Azure products by showcasing you can write to Azure Cosmos DB with a data pipeline moving data from multiple sources powered by Azure Data Factory and Databricks.
Data lakes have been around for several years and there is still much hype and hyperbole surrounding their use. This session covers the basic design patterns and architectural principles.
This session focuses on the deeper integration of SQL Server Integration Services (SSIS) in Azure Data Factory (ADF) and the broad extensibility of Azure-SSIS Integration Runtime (IR).
In this session I will show you how to apply DevOps practices to speed up your development cycle and ensure that you have robust deployable models. We will focus on the Azure cloud platform in particular, however this is applicable to other platforms
Using Azure DevOps and Azure RM templates to created isolated environments for testing PaaS solutions.
Hybrid data landscapes are common and the on-premises data gateway enables connecting to your on-premises data sources from online services (like Power BI, PowerApps, Microsoft Flow and Logic Apps) without the need to move your data to the cloud. Come to this session to see the latest gateway features and best practices related to setup and configuration along with troubleshooting tips and tricks, investigate bottlenecks and resolve your common gateway errors.
We’ll take a look at how to approach making an Azure Databricks based ETL solution from start to finish. Along the way it will become clear how Azure Databricks works and we will use our SSIS knowledge to see if it can handle common use-cases
An end-to-end solution covering many Azure features
Real-time decisions enabled by massively scalable distributed event driven systems with embedded analytics are re-shaping our digital landscapes. But how do you know which technology to choose? We'll cover the fundamentals of streaming systems, how and why they can deliver value to your business, and a look at options for streaming analytics in Azure
In this session you'll learn how Hyperscale removes limits for cloud based VLDBs.  We'll demonstrate how to create, migrate, and do point in time restore of very large databases in Azure.
Implementaing a CI/CD pipeline for Anomaly Detection and Predictive Maintenance on Azure
With SQL 2017 we entered a brave new world with cross-platform SQL Server, and with the new Azure Data Studio, we now have the tools to go with it. In this demo-packed session, learn about the newest tool for SQL Server for Windows, MacOS, and Linux, and how you can use it and extend it for your own needs. Be one of the first to see the new Notebooks feature for SQL Server, which brings the power of Jupyter notebooks to your SQL Server workflow.
The new SQL Server tool designed to help manage your estate
Learn how dataflows can be used to load data in Power BI.
In this session we will learn which processes are required to build a real-time analytical model along with batch-based workloads, which are the foundation of a Lambda architecture.
Moving to the cloud means that we need to take a different approach when it comes to how we design and tune databases. Managed Instance included, get the storage configuration wrong and it will not perform. We'll look at the storage options and architecture for Managed Instance before demonstrating how to get tune the storage layer to get the performance we need
In this session, you will learn about the architectural details of Managed Instance, the available features, and the best ways to configure it and migrate your databases to Managed Instance.
In this session, we will discuss the strategies and thought process one should adopt for modeling and partition data effectively in Azure Cosmos DB. We will also briefly cover related topics such implementing optimistic concurrency control, transactions with stored procedures, batch operations, and tuning queries + indexing
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data. Azure Databricks is a fast, easy and collaborative Apache Spark-based analytics service that can be used for big data analytics and artificial intelligence (AI) solutions. This session will cover the architecture patterns for using the two in synergy.
SQL Server 2008/R2 is soon reaching end of support. We'll take a look at the migration life cycle and show you how easy it is to migrate SQL Server instances to Azure with near-zero downtime by using the Azure Database Migration Service and related tools. We'll also give you a deep dive how to perform scale migrations using our CLI components
Modernizing is often a loaded term in a software application setting. In this session, we will break down what are the options of modernizing an existing application, what are the benefit of moving applications to managed Azure Open Source Database platform and what are the best practices and gotcha(s) that you need to look out during data migration.
Join this session to learn how managing performance is even more critical with Azure SQL DB. Learn what key performance indicators are most applicable, what auto-tuning really means and get some tools to help you identify and fix issues.
In this session, you will learn about the latest additions to the portfolio of network security features for Azure SQL Database. This session will be heavy on the “how-to” for securing the network connectivity for Managed Instance.  ?
Manish Kumar from Microsoft will take you through various performance tuning measures you should take before increasing service tier of your database. The session will be packed with tons of information, steps and demos.
Automatic Plan Correction is a feature you can use whether you're a pro at performance tuning or just starting with SQL Server. Come to this session to learn how to spend less time fighting fires with this new feature.
Come to this session to learn how to enable collaboration and solution design for business users and IT specialists to build solutions that enable an origanization to harness the power of their big data.  This session will enable you to collaborate across business and IT, and how we can extend intelligence beyond Power BI into Azure Data Services. Once Power BI has landed in an organization, attaching and extending into Azure can be achieved using common use cases and modernization plays.
PowerShell loves Power BI. In this session we will take a look at how to manage your datasets, security, monitor licensing and more, all through the ultimate administration interface: PowerShell!
Azure DataBricks is a PaaS offering of Apache Spark, which allows for blazing fast data processing! How can data engineers harness the in-memory processing power? Azure DataBricks can be your data ingestion, transformation and curation tool of choice
IoT is difficult. You need to know C and C++. It takes months to get it working. You need devices to start. And none of that is true. Join me to see how easy, in few minutes, you can have your IoT project up and running.
Azure Stream Analytics is a fully managed serverless offering that enables customers to perform real-time data transforms and hot-path analytics using a simple SQL language. In this session, we will show how to combine SQL reference data to augment data coming from devices and create real-time alerts, leverage partitioning to write data to SQL at high speed, and create real-time dashboards.
Are you curious about Azure Cosmos DB? This is the session for you! Join us to find out what it is, how it compares to other database platforms, and what all the hype is about!
<<12>>