| Start Time (24h) | Speaker | Track | Title |
|---|---|---|---|
| 10:00:00 | Tomaž Kaštrun | BI Analytics | Usage of R in SQL Server for better data understanding |
| 10:00:00 | Luca Ferrari | Azure Data Platform | Azure Sql DataWarehouse - The First cloud enterprise solution for MPP |
| 10:00:00 | Alberto Ferrari | Power BI | Power BI Architecture |
| 10:00:00 | Gianluca Sartori | SQL Server 2016 | New Security Features in SQL Server 2016 |
| 11:30:00 | Alessandro Rezzani | SQL Server 2016 | Polybase In SQL Server 2016 |
| 11:30:00 | Alberto Ferrari | Power BI | Power BI Desktop |
| 11:30:00 | Davide Mauri | BI Analytics | AzureML - A full journey |
| 11:30:00 | Francesco Diaz | Azure Data Platform | A lap around Azure Data Factory |
| 13:30:00 | Dejan Sarka | BI Analytics | Analyzing Text with SQL Server, R, and Azure ML |
| 13:30:00 | Jean-Pierre Riehl | Power BI | Data Management Gateway Deep Dive |
| 13:30:00 | Alessandro Alpi | SQL Server 2016 | SQL Server 2016 native JSON support |
| 13:30:00 | Emanuele Zanchettin | Azure Data Platform | Implementing and Maintaining an Azure SQL Database project |
| 14:45:00 | Cédric Charlier | BI Analytics | Automating the testing of your BI solutions with NBi |
| 14:45:00 | Kenneth Nielsen | SQL Server 2016 | SQL Server 2016 - Temporal Data Tables (System-Versioned) |
| 14:45:00 | Marco Parenzan | Azure Data Platform | Azure Stream Analytics |
| 14:45:00 | Marco Russo | Power BI | Power Query |
| 16:15:00 | Mladen Prajdić | BI Analytics | Visualizing streaming data in real time |
| 16:15:00 | Marco De Nittis | Azure Data Platform | DocumentDB Jumpstart, NoSQL adventures in Azure |
| 16:15:00 | Sergio Govoni | SQL Server 2016 | SQL Server 2016 Query Store |
| 16:15:00 | andrea benedetti | Power BI | Using Power BI in Enterprise: Collaboration Features |
Event Date: 10-10-2015 - Session time: 10:00:00 - Track: BI Analytics
Event Date: 10-10-2015 - Session time: 10:00:00 - Track: Azure Data Platform
But how it works ? Why is it so fast ? Data warehouses require fixed combinations of storage and compute, often underutilizing expensive resources. With SQL Data Warehouse, data and compute scale independently. You can dynamically deploy, grow, shrink, and even pause compute, taking advantage of best-in-class price/performance. Additionally, SQL Data Warehouse utilizes the power and familiarity of T-SQL to easily integrate query results across relational data in your data warehouse and non-relational data in Azure blob storage.
Event Date: 10-10-2015 - Session time: 10:00:00 - Track: Power BI
Event Date: 10-10-2015 - Session time: 10:00:00 - Track: SQL Server 2016
Always Encrypted is a new technology that protects your data not only at rest, but also throughout the whole interaction between the application and the database. Dynamic Data Masking is another interesting feature that allows us to protect sensitive data by masking it to all users that don’t have enough privileges to see the actual contents. Row Level Security allows showing to end users only the data they’re entitled to access, without changing the applications’ code. We will demonstrate the use of these three features with example applications and we will explore the use cases where these technologies represent a big leap from previous custom implementations.
Event Date: 10-10-2015 - Session time: 11:30:00 - Track: SQL Server 2016
The session shows how to install, configure and take advantage of Polybase for querying the Hortonworks Data Platform on premises and an HDInsight cluster on Azure.
Event Date: 10-10-2015 - Session time: 11:30:00 - Track: Power BI
In this session we will provide a deep dive in the new tool, highlighting the most important feature and showing how to connect from Excel to Power BI Desktop to debug your calculation. Finally, we will show how to use DAX Studio to query the Power BI model and analyze measure performance.
Event Date: 10-10-2015 - Session time: 11:30:00 - Track: BI Analytics
Event Date: 10-10-2015 - Session time: 11:30:00 - Track: Azure Data Platform
Event Date: 10-10-2015 - Session time: 13:30:00 - Track: BI Analytics
Event Date: 10-10-2015 - Session time: 13:30:00 - Track: Power BI
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.
Event Date: 10-10-2015 - Session time: 13:30:00 - Track: SQL Server 2016
Event Date: 10-10-2015 - Session time: 13:30:00 - Track: Azure Data Platform
Event Date: 10-10-2015 - Session time: 14:45:00 - Track: BI Analytics
Event Date: 10-10-2015 - Session time: 14:45:00 - Track: SQL Server 2016
• Temporal Database Tables One of the many new features in SQL server 2016 is the built-in support for temporal data tables. This is a feature that many developers have been urging to have as a “out of the box feature” – and therefore many have developed their own ways of implementing the capability to store information about how data looked in a certain period of time. What is a Temporal Data Table? The concept of a temporal data table is that the table will hold information about a records value in any point in time – thus meaning that we easily can read from the table and get values that are not current, but merely a historical view of the record. There will be many demo's and script will be shown and shared.
Event Date: 10-10-2015 - Session time: 14:45:00 - Track: Azure Data Platform
Event Date: 10-10-2015 - Session time: 14:45:00 - Track: Power BI
and transform data from different data sources, populating tables in data models or in Excel. In this session, you will see the architecture and the connectors available, spending most of the time in demos and playing with the “M” language, expanding the capabilities of this tool beyond the capabilities of its user interface.
Event Date: 10-10-2015 - Session time: 16:15:00 - Track: BI Analytics
that has to be refreshed on an interval. And those are very important visualizations. But sometimes you just have to have a real time view of your data streams and snapshots aren't enough. What if you could monitor multiple servers with SQL Trace or Extended Events or had some other source of streaming data and be able to see it all happening live on a central monitoring website? This is a scenario we'll take a detailed look at and build a system for such monitoring. We'll do this by using Extended Events .Net provider to get the live data stream, SignalR to get the live stream from the server to the website and the D3 javaScript library for actual real time visualizations on any device. After seeing all this in action, you'll definitely get a few ideas on where you could use this in your company.
Event Date: 10-10-2015 - Session time: 16:15:00 - Track: Azure Data Platform
We’ll discover together how DocumentDB works, how we could use this new exciting product and which are its pros and cons compared to relational databases as SQL server. This session covers how configure a new DocumentDB instance in Azure, how to save and query data and the basic guidelines about organizing complex data as JSON documents.
Event Date: 10-10-2015 - Session time: 16:15:00 - Track: SQL Server 2016
Event Date: 10-10-2015 - Session time: 16:15:00 - Track: Power BI
Organizations can create and publish content packs to their employees, leveraging data across on-premises and cloud data sources. Groups and organizational content packs complement each other to create a powerful collaborative experience built on Office 365 groups. In this session, you will see how to use them effectively, making sure that the access security is always in place correctly.