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.
This talk will address how to add the unit testing framework tSQLt to the database deployment pipeline. The purpose is to reduce the cost of validate every change in the database with a fully automated pipeline.
We introduce the concept of aggregation, we show several examples of their usage understanding the advantages and the limitations of aggregations, with the goal of building a solid understanding on how and when to use the feature in data models.
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
This session will take a look at better Unicode support, query processing improvements for row store tables, secure enclaves, and other neat things you'll find useful as a modern database administrator or developer.
A walk-through on what is possible analyzing your data with the "R" language.
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.
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.
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.
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.
Biml is not just for generating SSIS packages! Come and see how you can use Biml to save time and speed up other Data Warehouse development tasks like T-SQL development, test data creation, and dimension population.
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.
This session looks at creating a SQL test lab on your workstation. We start by selecting a hypervisor, look at building a virtual machine and then creating a domain controller, a Windows failover cluster and a couple of SQL Servers.
Based on real life scenarios, an audience interactive session.
Learning DAX can be tricky, especially if you have a background in SQL.
In this session we'll look at ETL metadata, use it to drive process execution, and see benefits quickly emerge. I'll show how a metadata-first approach reduces complexity, enhances resilience and allows ETL processing to become self-organising.
In this hour long session we will attempt to include lots of advice and guidance on how to develop code that will easily get approved by your DBA prior to release to production.
Using Azure DevOps and Azure RM templates to created isolated environments for testing PaaS solutions.
Power BI Premium and Analysis Services enable you to build comprehensive, enterprise-scale analytic solutions. This session will deep dive into exciting new and upcoming features.
Various topics will be covered such as management of large, complex models, connectivity, programmability, performance, scalability, management of artifacts, source-control integration, and monitoring. Learn how to use Power BI Premium to create semantic models that are reused throughout large, enterprise organizations.
Step back through the ages and explore how database teams have approached creating environments for dev and test. Learn how, in the new age of provisioning, databases are delivered safer, faster, and more efficiently
SQL Server provides a wealth of tools in the box to help you spot troublesome queries. We'll explore those and examine how they can best be used.
SQL Server 2019 includes new query processing features such as batch mode on rowstore, memory grant feedback, approximate query processing, and more. How do these work? Are they as good as Microsoft wants us to believe?
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
Start your database off right so you can scale when you need to
Graph databases – Origins, how they work, strengths and weaknesses
Let’s dive deep into the Kubernetes Architecture and learn how it works under the hood!
SQL Server 2019 expands on the Polybase feature from SQL Server 2019 by providing a robust data virtualization solution to reduce the need for ETL and data movement. Come learn how new data connectors work with sources like Oracle, MongoDB, CosmosDB, Terradata, and HDFS.
Containers are the new virtual machines. They present a new way to deploy, manage, and run SQL Server never possible before. This session will present an internal view of how Docker containers work, how SQL Server runs in them, and how they work in environments such as Kubernetes
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, attendees learn about how to create PowerApps solutions, how to use PowerApps as data entry application for Power BI. How to integrate PowerApps in Power BI and Power BI in PowerApps.
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.
Everyone that has been involved in Software Development can notice how huge the impact of a bug can be, and Databases are not the exception. In this session, you will learn how to test your SQL Server projects using Visual Studio and SQLUnitTesting.
In this session, you'll learn about the various prebuilt AI/ML models that are available for your consumption through Microsoft's Cognitive Services. Additionally, you'll see examples of how these prebuilt services can be leveraged with SQL Server 2019.
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
Learn in this session how you can package any database- or server-level permission in a stored procedure with help of certificate signing or EXECUTE AS and why one method is to prefer over the other.
Getting better performance from your ETL
This session will cover how to work around hardware issues when it isn’t in the budget for newer, faster, stronger, better hardware. Learn tips and tricks on how to reduce IO,relieve memory pressure, and reduce blocking.
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!
What data profiling is & why you should do it.
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!
Slack, Bots, ChatOps? Is any of this useful to a DBA? Yes, come and let me show you how!
Machine Learning is a popular buzzword, but what does it actually look like, and how can we use it? This session will show a number of high level examples of using ML to do some useful and fun stuff, including training a model to play a game
Running SQL Server in containers has huge benefits for Data Platform professionals but there are challenges to running SQL Server in stand alone containers. This session will cover what those challenges are and how Kubernetes overcomes them.
With GDPR and the number of data breaches we see in the news, encrypting sensitive data is incredibly important. In this talk we start with the basics of encryption, moving on to look at the ways we can encrypt data in SQL Server and Azure SQL DB.
Learn how Machine Learning Services in SQL Server is a powerful end-to-end ML platform for customers, on both Windows and Linux. Come learn about the unique value proposition of doing your entire machine learning pipeline in-database – right from data pre-processing, feature engineering, and model training to deploying ML models and scripts to production in secure and compliant environment without moving data out. 
I'll share what I've learned so you can successfully manage SQL Server on Linux!
Learn about the metadata features in SQL Server that describe your database and how they can make documentation, tuning, and maintenance much easier.
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