In this workshop you’ll cover a series of modules that guide you from understanding an analytics workload using the Cortana Intelligence Suite Process, the foundations of data transfer and storage, data source documentation, storage and processing using various tools.
# About the Course In this workshop you’ll cover a series of modules that guide you from understanding an analytics workload, the Cortana Intelligence Suite Process, the foundations of data transfer and storage, data source documentation, storage and processing using various tools. Additionally, this workshop also covers a series of modules that guide you from understanding Massive Parallel Processing and loading a data warehouse using various tools. You’ll also learn how to work through a real-world scenario using the Cortana Intelligence Suite tools, including the Microsoft Azure Portal, PowerShell, and Visual Studio, among others. # Prerequisites There are a few things you will need in order to properly follow the course materials: - A subscription to Microsoft Azure (this may be provided through your company or as part of your invitation – you must have this enabled prior to class – you will be using Azure throughout the course, for all labs, work and exercises) You can use your MSDN subscription – https://azure.microsoft.com/en-us/pricing/member-offers/msdn-benefits/ - Your employer may provide Azure resources to you, but make sure you check to see if you can deploy assets and that they know you’ll be using their subscription in the class. - Optionally, you may receive instructions in your class invitation. Your workstation should have the following Software Installed: - Visual Studio installed – the Community Edition (free) is acceptable – Version 2015 preferable (https://www.visualstudio.com/en-us/products/visual-studio-community-vs.aspx) - SQL Server Data Tools for Visual Studio 2015 - Azure SDK and Command-line Tools installed (https://azure.microsoft.com/en-us/downloads/ ) - Azure Storage Explorer (http://go.microsoft.com/fwlink/?linkid=698844&clcid=0x409) - Power BI Desktop Installed (https://powerbi.microsoft.com/en-us/desktop/ )A background in data technologies, such as working with Relational and Non-Relational data processing systems Install the Microsoft R Client: http://aka.ms/rclient/download with the R tools for Visual Studio - SQL Server 2016 Management Studio - SQL Server 2015 Visual Studio - Azure PowerShell SDK - Azure PowerShell ISE - It’s also a good idea to have a general level of predictive and classification Statistics, and a basic understanding of Machine Learning # Agenda What will you learn - Process and Platform, Environment Configuration - Data Discovery and Ingestion - Data Preparation - Modeling for Machine Learning and Data Mining (Extended Class) - Business Validation and Model Evaluation (Extended Class) - Deploying and Accessing the Solution - CIS overview and how Azure SQL Data Warehouse fits into CIS - Introduction to Azure SQL Data Warehouse - Working with Tables, Indexes, and Statistics - Loading data into Azure SQL Data Warehouse - Managing Security and Administration. - Workshop recap (Extended Class) # Skills taught - Understand the CIS Process (General level), Understand CIS Components (General Level), Set up and configure the development environment - Understand how to source and vet proper data, Understand feature selection, Understand Azure Storage Options, Use various methods to ingest data into Azure Storage, Examine data stored in Azure Storage, Use various tools to explore data - Understand ADF and its constructs, Implement an ADF Pipeline referencing Data Sources and with various Activities including on-demand HDInsight Clusters, Understand the HIVE language and how it is used - Understand SQL Data Warehouse and its constructs, Implement loading activities into Azure SQL Data Warehouse. - Manage the security and administration of an Azure SQL Data Warehouse - Understand how to use Azure ML and how experiments are created, Understand how MRS can be used to perform Machine Learning experiments, Use ADF to schedule Azure ML Activities - Understand how to evaluate the efficacy and performance of an Azure ML experiment, Understand how to evaluate the efficacy and performance of an MSR ML experiment, Access and show data from Azure Storage, Access, and Query Azure SQL DB - Understand how to publish an Azure ML API, Understand the access methods of Azure Storage and Intelligent Processing, Understand the options to send a HIVE query to an HDI system, Use Power BI to query the results of a solution and create reports in Power BI Desktop, Power BI Service, and Power BI in Microsoft Excel - Understand when to use each component within CIS - Understand how to create an Azure SQL Data Warehouse using various tools. # Technologies Covered - Cortana Intelligence - SQL Data Warehouse - Cortana Intelligence Process, Cortana Intelligence Suite Platform - The Data Science Process, Azure Portal, ADC Interface, Visual Studio Interface (and RTVS), Power BI Interface - Azure Machine Learning Interface, Azure PowerShell, Azure Storage Explorer - Azure Data Catalog, Azure Storage, Techniques for discovery - Azure SQL Data Warehouse - Microsoft R Server overview, Azure Data Factory, HDInsight - Azure Data Storage, Azure Machine Learning API, Cognitive Services API, HIVE, Power BI - PowerShell Interface, SQL Server Management Studio