Microsoft Data Platform Hands-on Labs


(Version en français ici)

After the success of our first series of hands-on labs in Montreal in the first half of the year, we are expanding our efforts to increase room capacity, topic selection and depth. We firmly believe that placing our technology in your hands is the best way to make it shine. After all, teaching you how to use our solutions is much more fun than showing you slides!

The only way to make this possible is with the great help of our amazing Microsoft Partner community in Montreal. They work tirelessly to stay on top of the latest innovations and to make your initiatives successful. A big thank you to all firms that decided to help us provide these training sessions at no cost.

Topics

Not all labs are confirmed - this list is subject to change

Note that these are introductory 101 hands-on workshop. Partners may have more advanced training available on demand.

Category Workshop topic Partner
Analytics Azure ML Exia
Analytics Chatbot and Cognitive Services BinariesLid
Analytics Cognitive Services and CNTK Deep Learning TBD
Analytics R Server and Python Data Science Exia
BI Power BI Exia
BI SQL Server 2017 BI Exia
Big Data Azure Data Lake Analytics Exia
Big Data Hadoop Hortonworks
Big Data HDInsight AgileDSS
Database Azure SQL DB, MySQL, Postgress Emyode
Database Azure SQL DW Faction A
Database NoSQL Cosmos DB Pythian
Database SQL Server 2016/2017 OLTP Emyode
Database SQL Server 2017 on containers Emyode
IoT Internet of Things Matricis

Calendar

At this time only the labs scheduled in September are showed below.

All Montreal labs will be held at the Microsoft Montreal office: 2000 McGill College, Suite 550
All Quebec labs will be held at the Microsoft Quebec office: 2640 boul. Laurier, Suite 1500
All Ottawa labs will be held at the Microsoft Ottawa office: 100 Queen Street, Suite 500

 

Topic (click for details) Date Time City Language Capacity Partner Register!
Azure ML September 7 8am to 12pm Montreal French 50 Exia
IoT September 14 8am to 5pm Montreal English 30 Matricis
Big Data: Azure Data Lake Analytics September 22 9am to 4pm Montreal French 50 Exia
Power BI September 26 9am to 4pm Montreal French 50 Exia
Power BI September 28 9am to 4pm Quebec French 24 Syntell
SQL Server 2016 September 29 8:30am to 4pm Montreal French 30
Big Data: HDF October 13 8:30am to 3:30pm Montreal French 50 Hortonworks
Power BI Octber 17 9am to 4pm Ottawa English 40 Lixar
SQL Server 2016/2017 OLTP October 18 9am to 4pm Montreal French 50 Emyode
Big Data: HDInsight + Spark October 19 9am to 4pm Montreal French 50 AgileDSS
Power BI October 30 9am to 4pm Montreal French 50 Exia Register
Azure ML November 2 8:30am to 12pm Montreal French 50 Exia Register
Azure SQL DataWarehouse November 9 9am to 4pm Montreal French 50 Faction A Register
Master Data Management + Governance November 14 9am to 4pm Montreal French 50 Exia Register
SQL Server 2016/2017 BI November 16 9am to 4pm Montreal French 50
Azure SQL DB, MySQL, PostgresSQL November 21 9am to 12pm Montreal French 50 Emyode Register
NoSQL Cosmos DB December 7 9am to 4pm Montreal English 50 Pythian Register
Power BI December 12 9am to 5pm Montreal French 50 Exia Register
Power BI Hackathon February 3 2018 9am to 4pm Montreal French MSDEVMTL Register
IoT February 7 2018 8am to 5pm Montreal English 30 Matricis soon
Azure SQL DB, MySQL, Cosmos DB, Logic App, Migration February 8 2018 9am to 12pm Quebec French 24 Emyode soon
SQL Server 2017 on Containers February 13 2018 9am to 4pm Montreal French 50 Emyode soon

 

You can also register to our 8-part Data + AI webinar. More details here.

Content Details

Azure ML

Azure Machine Learning is a fully managed cloud service that enables you to easily build, deploy, and share predictive analytics solutions. In this one day event, Azure Machine Learning will teach users how to build their own experiments in Azure Machine Learning Studio.

Target audience: data practice lead, professional, developer practice lead and BI practice lead

Prerequisites:

  • Bring your own laptop

 

Internet of Things

Join the Microsoft IoT experts in a full day hands-on lab to build a basic IoT solution. In this hands on lab, you will gain practical experience to program a Raspberry Pi to send environmental data to the Azure IoT Suite. Learn to configure Azure to visualize the sensor data in Power BI and to route the sensor data to long term storage. Discuss using Microsoft IoT technologies to achieve your business goals and learn about the use cases that we see customers achieving using Azure IoT!

What You’ll Learn:

  • Microsoft Azure IoT Suite including IoT Hub
  • Data Analytics and Azure Stream Analytics
  • Serverless Architecture and Azure Functions
  • Data Visualization and PowerBI

Target audience: database, data warehouse, and Business Intelligence practice leads and architects

Prerequisites:

  • Bring your own laptop
  • A raspberry pi device will be needed: 
    You will need to acquire hardware prior to the event. For details on the required hardware and the lab, please see this link: IoT Hub Pi Hackathon .
    Please be prepared by completing the “Advanced Setup” section in the document. If you have any difficulties with your setup, please email vincent.hong@microsoft.com

 

Azure Data Lake Analytics Big Data

Learn about our Azure Data Lake Analytics technology for Big Data. This is the same technology that powers the Microsoft internal data lake (multiple Exabytes) at the core of many of our services such as Bing, Office 365, XBox Live, etc.

Target audience: database, data warehouse, and Business Intelligence practice leads and architects

Prerequisites:

  • Bring your own laptop

Agenda:

    • Introduction to Azure Data Lake
    • Understanding Azure Data Lake Analytics
    • Understanding Azure Data Lake Store
    • Break
    • Introduction to U-SQL
    • Introduction to U-SQL HOL
    • Lunch
    • Using Azure Data Lake Tools for Visual Studio
    • Advanced U-SQL topics
    • Break
    • Advanced U-SQL HOL
    • Break
    • Implementing security and Azure Data Lake
    • Azure Data Lake command-line tools
    • Using PowerShell to interact with Azure Data Lake HOL
    • [Optional] Building big data pipelines with Azure Data Factory
    • [Optional] Using Azure Data Factory to schedule jobs in Azure Data Lake HOL
    • wrap-up

 

Power BI

Learn how to collect and combine data from a variety of data sources inside and outside your organization with Power BI. Transform your data model into stunning visualizations extracting insights and business values from your data.

Target audience: Data practice lead, professional, business analyst, power user, developer practice lead and BI practice lead

Prerequisites:

Agenda:

  • Learn how to set up your own business analytics environment
  • Collect and combine data from a variety of data sources both inside and outside of your organization
  • Turn the data you prepared into stunning visualizations to extract insight and business value
  • Publish your report the Power BI environment to share with your peers and create a schedule to keep the data fresh without manual intervention

Schedule:

  • 9h00 – presentation
  • 9h45 – Begin lab
  • Noon – lunch break
  • 16h00 – end of lab

 

Master Data and Governance

Agenda:

  • Introduction to
    • Master Data Management
    • Master Data Services
    • Azure Data Catalog
  • Implement a data model
    • Create entities
    • Load data in an entity
    • Create business rules
    • Create subscription views
  • Add an entity subscription view to an Azure Data Catalog

Prerequisites:

  • Bring your own laptop
  • Make sure the port 3389 is open in order to do a remote desktop into a VM in Azure

 

SQL Server 2016/2017 OLTP

Agenda:

  • How to improve your application performance and security
    • In-Memory OLTP
    • Query Store
    • Temporal Tables
    • Always Encrypted
    • Row Level Security and Dynamic Data Masking
  • How to deploy application functionalities faster with the cloud
    • Stretch Database
    • Enhanced Backup to Azure
    • Migration to the SQL Azure
    • DevOps using SQL Azure & VSTS

Prerequisites:

  • Bring your own laptop
  • Make sure the port 3389 is open in order to do a remote desktop into a VM in Azure

 

 

For any questions, please contact Robert Luong at robert.luong@microsoft.com.

We hope to see you soon at our office!

Charles Verdon, Data Innovation Strategist

Robert Luong, Technology Specialist - Data Platform

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