Discover a complete hands-on immersive experience demonstrating the Microsoft Data Insights platform as a key component of the Microsoft Cloud OS strategy. In this structured set of labs, students will walk through various components of the Microsoft data platform, including hands-on experience with SQL Server relational databases, Windows Azure SQL Database, Azure HD Insight (Hadoop/Big Data), and Microsoft Power BI tools within Excel.
Instructors | Gregory Leake – Microsoft Director, Technical Product Management for SQL; Vanessa Bucher – Microsoft Senior Project Marketing Manager; Russell Bowden - Technical Architect/Intergen LLC; Zena Heywood - Microsoft Senior Project Marketing Manager
This session introduces you to the Data Insights Immersion, showing how the Microsoft Cloud OS vision and data insights content is used to introduce customers to the data platform. Learn how you can provide deep data insights, while identifying opportunities for your data center to evolve. With immersion, we bring the environment to you through four hands-on data immersion experiences: Unstructured data Structured data Combining data Gaining insights
Learn how to create resiliency in your data environment to minimize interruption to core business activities. Specifically, we will step through the setup of a SQL Server database mirror in the Azure cloud. By establishing a mirrored database on an Azure VM, you can configure the database to automatically fail over to the mirrored cloud database, should the primary on-premises database fail. Next, we will look at creating a Windows Azure SQL Database, using both the Windows Azure Management Portal and SQL Server Management Studio to migrate schema and data from an on-premises SQL Server Database to Windows Azure SQL Database.
In this session, we will introduce the concept of unstructured (aka Big Data) storage and analysis in the Azure cloud. Specifically, we will walk through the setup of Windows Azure storage and data loading of web log data being generated from a sales website into Azure storage. Next, we will discuss creating an Azure HDInsight (Hadoop) cluster to perform data analysis via Map/Reduce and ad-hoc queries on the unstructured data. We will also look at an actual HDInsight processing job against the data and establish a data feed from Excel to the results of the HDInsight processing job. From here, we will run a Hive query against the data to analyze the data and to gain business insight.
This module explores using BI tools, including Power Maps, within Microsoft Excel to perform data analysis and visualization across disparate data sources—both structured and unstructured. First, we will look at the process of importing data from a corporate SQL Server data warehouse into Excel. Then, we will enhance this data with unstructured data that has been processed via HDInsight, to create a richer data model for PowerPivot analysis within Excel. We will also use Excel to bring in publicly available data sets (specifically from Wikipedia, in this walk-through) to further enhance our data model and to perform data analysis across the combined data sets. Finally, we promote the data model from being a personal BI information source to an enterprise-grade information source using SQL Server Analysis Services (SSAS).
In this session, we will explore how to use BI tools within Excel to visualize complex information, patterns, and trends quickly from data at a glance. By increasing the level of interactivity in analysis and presentation of the data, businesses can now see multiple views of the data from a single interface, thereby allowing multiple questions to be answered without having to ask the analysts to change the underlying model or to generate a new report. Excel-based dashboards and PowerView provide an interactive, familiar interface in which a non-technical person can comfortably investigate the data. First, we will use Excel with Power View to create data visualization. Next, we will enhance the visualizations with time-based animations showing how the data changes over time, and we'll use Power Map to overlay data visualizations across a geographic interactive map. Finally, we will explore publishing the final visualizations via SharePoint, for collaboration across the organization.