| Start Time (24h) | Speaker | Track | Title |
|---|---|---|---|
| 10:00:00 | Michal Sadowski | Enterprise Database Administration Deployment | How to start working in the multiserver environment? |
| 10:00:00 | Andrii Zrobok | Application Database Development | Важливість статистики в MS SQL Server, як вона використовується. |
| 10:00:00 | Yevhen Nedashkivskyi | Strategy and Architecture | SQL Server: Готуємося до гіршого |
| 11:10:00 | Eugene Polonichko | BI Platform Architecture, Development Administration | What’s new in SQL Server 2017 RC for Business Intelligence |
| 11:10:00 | Anton Boyko | Cloud Application Development Deployment | Создание data-driven serverless приложений используя Azure Functions |
| 11:10:00 | Marcin Szeliga | Advanced Analysis Techniques | State-of-the-Art Machine Learning Algorithms in R from Microsoft |
| 13:10:00 | Jan Mulkens | Advanced Analysis Techniques | Enabling Citizen Data Science with Microsoft |
| 13:10:00 | Catalin Gheorghiu | Application Database Development | IoT Circus – deathmatch oops, datematch :) Power Bi vs Time Series Insights |
| 13:10:00 | Mihail Mateev | Cloud Application Development Deployment | Dealing with CosmosDB |
| 14:20:00 | Andriy Pogorelov | Application Database Development | "The Time Machine". Change Tracking, Change Data Capture, Temporal Tables |
| 14:20:00 | Taras Bobrovytskyi | Application Database Development | Using non-relational data inside SQL Server |
| 14:20:00 | David Williams | Application Database Development | SQL Server 2017 New Features (Not Linux support!) |
| 16:05:00 | Mihail Mateev | Cloud Application Development Deployment | IoT Duel - Cloud vs. on Premises Solutions |
| 16:05:00 | Sergey Syrovatchenko | Application Database Development | SQL Server 2016: JSON vs XML |
| 16:05:00 | Denis Reznik | Enterprise Database Administration Deployment | SQL Server Performance Tuning Nowadays |
| 16:05:00 | Andrzej Kukula | Enterprise Database Administration Deployment | Introduction to SQL Server 2017 for Linux |
| 16:05:00 | Dmytro Stolpakov | Advanced Analysis Techniques | Як звучить Data Science у .mid |
Event Date: 19-08-2017 - Session time: 10:00:00 - Track: Enterprise Database Administration Deployment
Event Date: 19-08-2017 - Session time: 10:00:00 - Track: Application Database Development
Event Date: 19-08-2017 - Session time: 10:00:00 - Track: Strategy and Architecture
Event Date: 19-08-2017 - Session time: 11:10:00 - Track: BI Platform Architecture, Development Administration
If you want to know about it come to my session and I'll tell you about it.
Event Date: 19-08-2017 - Session time: 11:10:00 - Track: Cloud Application Development Deployment
Event Date: 19-08-2017 - Session time: 11:10:00 - Track: Advanced Analysis Techniques
We will start with linear regression, simple but powerful machine learning algorithm. With it you will learn about correlation coefficient, loss function, optimization algorithms and regularization. At the end of this section we will built a ML model using Fast linear model with Stochastic Dual Coordinate Ascent (SDCA) optimization. Next step is get to know artificial neural networks, their architecture, activation functions and backpropagation algorithm. This allows us to build a (better?) model using rxNeuralNet and N#. Evaluation metrics for regression models will conclude first part of the session. In the second part we will use almost the same ML algorithms for classification — the difference is that Logistic regression will replace Linear regression. Finally we will learn about Evaluation metrics for classification models, which allows us to pick the very best model for problems we are going to solve together.
Event Date: 19-08-2017 - Session time: 13:10:00 - Track: Advanced Analysis Techniques
Microsoft has been making sure that everyone can participate in the data revolution by giving people access to predictive API’s, in-database advanced analytics and drag-and-drop predictive experiments. All thanks to SQL Server 2016 and the Cortana Intelligence Suite in Azure.
These advances have given people with less knowledge of statistics and programming the ability to become what Gartner calls citizen data scientists. Should we be worried about creating fools-with-tools or should we embrace the democratization of data science as the golden age of data?
Using a combination of theory and demo’s, we explore Microsoft’s solutions to ensure democratization of data science and the possible dangers that lurk below the surface.
Event Date: 19-08-2017 - Session time: 13:10:00 - Track: Application Database Development
If you create an IoT solution today, you have a variety of components available to mix and match to make your solution, akin LEGO. You get your hardware and firmware right and you get data from the sensors, now what? Of course, you would like to have, some data visualization easy and fast, and of course you would like to learn something from that data easy and fast. And it would be nice to have the results available on mobile devices, yes, yes easy and fast. Now enter our two titan technologies in a match to the death oops data trying to achieve these goals, you guess it easy fast (and cheap). And we will see them clash, from real hardware, to the big Azure cloud, to mobile devices, trying to outmatch each other.
Event Date: 19-08-2017 - Session time: 13:10:00 - Track: Cloud Application Development Deployment
In this presentation, you will learn: • How to get started with DocumentDB you provision a new database account. • How to index documents • How to create applications using CosmosDb (using REST API or programming libraries for several popular language) • Best practices designing applications with CosmosDB • Best practices creating queries.
Event Date: 19-08-2017 - Session time: 14:20:00 - Track: Application Database Development
It will be few slides and many demos.
Event Date: 19-08-2017 - Session time: 14:20:00 - Track: Application Database Development
Event Date: 19-08-2017 - Session time: 14:20:00 - Track: Application Database Development
Using Query Store for automatic tuning of querys which have bad plans (multiple plans with regressions)
Additional information stored in actual execution plans
New DMVs e.g. log information, statistics histograms
Interleaved Execution for multi-statement T-SQL TVFs
Adapative joins for queries
Resumable online index rebuild
Faster non-cluster index builds on memory optimized tables.
Additional in-memory SQL Surface Area e.g. Computed columns, JSON, CROSS APPLY,sp_spaceused,sp_rename,CASE,TOP N with TIES
Parallel Redo for memory optimized tables, increases throughput for Always On Availability Groups
DTC support for Always On Availability Groups
Cluster-less Availability Groups
Minimum Replica Commit Availability Groups
New CLR strict security
Graph database queries
Running Python scripts in SQL Server
BULK INSERT directly from CSV files
Event Date: 19-08-2017 - Session time: 16:05:00 - Track: Cloud Application Development Deployment
Event Date: 19-08-2017 - Session time: 16:05:00 - Track: Application Database Development
Что можно сказать... JSON очень крут и на протяжении сессии я поделюсь опытом как с помощью новой функциональности смог ускорить OLTP/DW операции от 2 до 10 раз по сравнению с ранее использовавшимся парсингом XML. Кроме того, в конце мы поговорим об интересных багах и особенностях парсинга JSON и XML.
Event Date: 19-08-2017 - Session time: 16:05:00 - Track: Enterprise Database Administration Deployment
In this session, we will find answers to all these questions going from collecting data for analysis, through identifying bottlenecks to optimization of the particular queries. On this way, we will learn performance tuning practical techniques and solve a bunch of issues in real-time. And despite I'm a big fan of Profiler and old-fashioned tools and technics, new, more interesting and useful instruments are available nowadays, so will use them to find the bottleneck and tune performance. Minimum of theory and a lot of practice.
Event Date: 19-08-2017 - Session time: 16:05:00 - Track: Enterprise Database Administration Deployment
On my session I'll show details of solution that allowed this idea to come true. We'll see how to install, use and administer Linux version of SQL Server. We'll see it working as a service and in Docker containers. I'll give you details of why the second option is really interesting, or to say it more clearly - groundbreaking. In addition to slides you're going to see quite a bit of T-SQL and bash code, terminal windows, Visual Studio Code, tools that are familiar to you and new stuff as well.
Event Date: 19-08-2017 - Session time: 16:05:00 - Track: Advanced Analysis Techniques