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 | |
Azure ML | November 2 | 8:30am to 12pm | Montreal | French | 50 | Exia | |
Azure SQL DataWarehouse | November 9 | 9am to 4pm | Montreal | French | 50 | Faction A | |
Master Data Management + Governance | November 14 | 9am to 4pm | Montreal | French | 50 | Exia | |
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 | |
NoSQL Cosmos DB | December 7 | 9am to 4pm | Montreal | English | 50 | Pythian | |
Power BI | December 12 | 9am to 5pm | Montreal | French | 50 | Exia | |
IoT | January 17 2018 | 8am to 5pm | Ottawa | English | 30 | Lixar | 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 | Register |
Azure SQL DB, MySQL, Cosmos DB, Logic App, Migration | February 8 2018 | 9am to 12pm | Quebec | French | 24 | Emyode | Register |
SQL Server 2017 on Containers | February 13 2018 | 9am to 4pm | Montreal | French | 50 | Emyode | Register |
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 :
- Bring your own laptop
- Download and install the latest version of Power BI Desktop: https://powerbi.microsoft.com/en-us/documentation/powerbi-desktop-get-the-desktop/
- Make sure the port 1433 and 3389 are open in order to connect Power BI Desktop to a database in Azure
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