In the second half of this session, we'll connect to Azure SQL DW, load some risk data, improve the data model, create some insightful reports and dashboards, ask some questions then analyse in Excel. We'll use an example of financial market risk data. This is stored in data warehouses since a bank can easily generate a few hundred million rows of each day and risk managers need to analyse this data over several days and months. Such large volumes make this data a prime candidate for moving to Azure SQL DW. In addition, the elastic capabilities of SQL DW are very useful for example at UAT phases when users need an additional large dataset available for a (hopefully) short period of time. In the demo, we will use the scenario of an equity trading division with a bank. I will spend a couple of minutes introducing a small fictional dataset of the profit and loss (P&L) and VaR over a few years. (VaR, stands for Value At Risk, and is a common measure of the riskiness of the portfolio of trades.) We will load the data into Power BI desktop. We will improve the data model; build a hierarchy, and hide columns of no interest to our users, and calculate a few useful quantities using DAX. We will build a typical market risk report known as a back test chart which compares our P&L and VaR. We'll do this firstly using the standard and custom visuals then using the R Script visual to give us a more precise visualisation that meet the demands of regulators. Once done, we are ready to publish data and reports to the Power BI service. There will we pin a few visuals to a dashboard and then interrogate the data using plain English with the Q&A feature. Finally we will analyse our data in Excel. This is a very exciting new(ish) feature of Power BI and very useful to the risk managers in our scenario who traditionally do analyse their risk data in Excel pivot tables. This allows them to have their cake and eat it – to be able to visualise, explore and share their data with Power BI but also to take advantage of all the analytical power of Excel.
Nowadays, you’re connected to a Wi-Fi network wherever you go – at homes, coffee shops, malls, hotels, even on air-planes! Have you ever wondered who else is connected to all these networks? With Windows 10’s DNS Service Discovery (DNS-SD) API, you can create apps that discover other devices over the same network. In this session, we’ll take a look at how the DNS-SD API can be used for creating multi-user applications without needing to setup a web server or any other complex systems; all you need is for all devices to be on the same network! Speaker: Jay Mahendru
How are natural & intuitive interactive emerging experiences designed into software? How do you design inspirational Emerging Experiences in new scenarios across the broadest range of devices, from big screens to small screens to no screens at all? How do you build software for a world that is more mobile, natural and grounded in intuitive? Join Tim Huckaby in a demo heavy, entertaining and technical discussion of the future of More Personal Computing and Emerging Experiences.Touch, Gesture, Voice Recognition, Demographic Profiling, Facial Recognition, Emotional Recognition, Holographic Experiences and more: All the bad; all the good; privacy law, all the real customer demos and stories, and the tools, tips and tricks learned along the way. This demo-heavy keynote will show you a number of real emerging experiences solutions (from propriety solutions to broadcast television solutions you see every day). Tim Huckaby will show you the use cases where these types of emerging experiences solutions are happening. And those coming in the immediate future and beyond.