|Start Time (24h)||Speaker||Track||Title|
|09:00:00||Janusz Rokicki||Database Administration||Anomaly Detection in Predictive Maintenance for Sql Server|
|09:00:00||Angela Henry||Database Development||Profiling Your Data|
|09:00:00||Karel Rejthar||Business Intelligence||Maps in Power BI|
|10:15:00||Alexander Klein||Business Intelligence||Build your next BI solution in Azure|
|10:15:00||Neil Hambly||Database Administration||Performance Troubleshooting Using DMVs|
|10:15:00||Tomas Tucek||Data DevOps||CI, CD, CDE and DevOps Explained|
|11:30:00||Dejan Sarka||Data Science Machine Learning||Comparing Predictive Models from R, Python, SSAS, and Azure ML|
|11:30:00||Marcos Freccia||Database Administration||My 10 favorite PowerShell commands|
|11:30:00||Jiří Neoral||Business Intelligence||Power BI Row Level Security Deep Dive|
|12:35:00||Oleg Ulyanov||Database Administration||Successfully Virtualizing SQL Server on VMware vSphere: Straight from the Source|
|12:35:00||Tasty Lunch||Data DevOps||.|
|13:30:00||Luis Beltran||Data Science Machine Learning||Clever data: Building a chatbot from your database|
|13:30:00||Michal Chmelár||Business Intelligence||Power BI as a universal analytic tool|
|13:30:00||Dmitry Pilugin||Database Development||Intelligent Query Processing in SQL Server 2019|
|14:45:00||Christina Leo||Business Intelligence||Analytics on Azure: What to Use When|
|14:45:00||Ivan Donev||Business Intelligence||Designing your tabular/PowerBI model for performance and scalability|
|14:45:00||Cédric Charlier||Data Science Machine Learning||Data scientists have left ... How will I deploy their work?|
|16:00:00||Dr. Subramani Paramasivam||Data Science Machine Learning||Azure Machine Learning with Power BI|
|16:00:00||Damian Widera||Database Administration||Transaction Isolation Levels - that could be funny|
|17:15:00||Pinal Dave||Database Administration||Practical Real-World Performance Tuning for Accidental DBAs|
|17:15:00||Nicky van Vroenhoven||Business Intelligence||Power BI (Premium) Implementation at a Financial Institute|
|17:15:00||Tomaž Kaštrun||Data Science Machine Learning||Common Data Science Mistakes|
Event Date: 21-09-2019 - Session time: 09:00:00 - Track: Database Administration
Event Date: 21-09-2019 - Session time: 09:00:00 - Track: Database Development
Event Date: 21-09-2019 - Session time: 09:00:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 10:15:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 10:15:00 - Track: Database Administration
We’ll be demonstrating using practical examples, including code that can be taken away and used on attendees’ own SQL Servers. We’ll also discuss how to identify common causes of performance issues, and learn how to quickly review and understand the wealth of performance data available.
Event Date: 21-09-2019 - Session time: 10:15:00 - Track: Data DevOps
"... am I really able to deploy our data solution more often than once in a 3-6 months? Is that real? ..." The answer always is "Yes it is and yes you are!!!" Let's meet and have a light talk about how is that possible, what actually the buzzwords like CI (continuous integration), CD (continuous delivery), CDE (continuous deployment) and DevOps in our data platform world means and why it is important. Also with some real examples showing how simple that actually is ...
Event Date: 21-09-2019 - Session time: 11:30:00 - Track: Data Science Machine Learning
In data mining, you typically create multiple predictive models for the same task, and then evaluate them to select the best one. So why wouldn’t you even use different tools for different models? You will learn how to evaluate the predictive models. Then you will see how to bring all of the mining models together and compare them no matter of the source they come from. You will see how you can use SQL Server Integration Services, Excel, and other tools for this task.
Event Date: 21-09-2019 - Session time: 11:30:00 - Track: Database Administration
I promise that at least one new thing you will learn it
Event Date: 21-09-2019 - Session time: 11:30:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 12:35:00 - Track: Database Administration
• vCPU allocation and deep dive in vNUMA • Memory allocation and configurations options • Storage configuration best practices including PMem/NFS/Snapshots • Network configuration myths and best practices
It all that you want to know about virtual platform configuration but hesitated to ask! Directly from the source with the ton of hands-on from VMware Professional Services.
Event Date: 21-09-2019 - Session time: 12:35:00 - Track: Data DevOps
Event Date: 21-09-2019 - Session time: 13:30:00 - Track: Data Science Machine Learning
One of the most engaging AI applications are chatbots, which interact with real-time users in order to assist them to perform a task -such as booking a hotel, answering a question or looking for specific information on the Internet- while simulating that a real human is behind the scene.
Data is knowledge, and the data that has been stored in your Azure SQL database can be used as an input for a bot which assists a company's customers in order to process the information for them and return expected results.
This session will be focused on explaining the actors involved when building a bot capable of obtaining data from your storage, including Azure SQL Database, Microsoft Bot Framework and LUIS (Language Understanding Intelligent Services). A mobile app built with Xamarin will be used as demo.
Event Date: 21-09-2019 - Session time: 13:30:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 13:30:00 - Track: Database Development
SQL Server 2017 introduced a new approach for solving performance problems called Adaptive Query Processing. SQL Server 2019 evolves those mechanisms and the entire feature family now is named – Intelligent Query Processing.
The Intelligent query processing in SQL Server 2019 includes the following:
In this session we will see how do these features work and in what cases they might be helpful.
Event Date: 21-09-2019 - Session time: 14:45:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 14:45:00 - Track: Business Intelligence
Event Date: 21-09-2019 - Session time: 14:45:00 - Track: Data Science Machine Learning
That's it, data scientists have left the house! Behind them, some scripts written in Python or R, thousands of CSV files, three sheets and two whiteboards of mathematical equations, many PowerPoint presentations and a clear instruction from the CEO: go to production ASAP! Unfortunately, no trace of a deployment procedure. Hopefully, this session, will explain how to industrialize data scientists' scripts. How to import and refactor code written in Jupyter Notebooks within VS Code, How to put in place the best practices of DevOps and apply them to Machine Learning with Azure Pipelines and some other tips and tricks for a successful go-live.
Event Date: 21-09-2019 - Session time: 16:00:00 - Track: Data Science Machine Learning
Event Date: 21-09-2019 - Session time: 16:00:00 - Track: Database Administration
Event Date: 21-09-2019 - Session time: 17:15:00 - Track: Database Administration
In this quick paced, demonstration-oriented learning session, we will see how we can immediately help our application with performance if we just know what exactly to do. We will cover the following topics during our session a) Learn and Implement best deployment and configurations practices b) Indexing (and statistics) best practices deployments c) Understanding cardinality and compatibility levels and their impact d) Enabling SQL Server 2019 (on-premises and cloud) new features e) Secret Performance Tuning Scripts
Event Date: 21-09-2019 - Session time: 17:15:00 - Track: Business Intelligence
Fast forward 6 months, there is more traction within the business, training is given and workshops are held. The adoption of Power BI is growing. Some departments already use Power BI very extensively and incorporate it in their day-to-day processes. Due to this quick success there is uncertainty regarding the right support team for incidents and problems. Because an app workspace creates an Office 365 group with a lot of artifacts behind the scenes, the creation workflow is controlled by IT. Unfortunately this inhibits the end users. We require more governance, not to further bother the users, but it is essential to stay in control. Responsibilities need to be better aligned between IT and the business. Throughout this session we take you along on our Power BI journey, with tips, tricks, do's and don'ts during the implementation of Power BI (Premium).
Event Date: 21-09-2019 - Session time: 17:15:00 - Track: Data Science Machine Learning