| Start Time (24h) | Speaker | Track | Title |
|---|---|---|---|
| 08:30:00 | Matt Cushing | Professional Development | Networking 102: Getting Ready for a SQL Event |
| 09:50:00 | Ginger Grant | Data Analysis / Cleaning Method and Tools / Data Demographics | Getting Started with Data Science and Databricks |
| 09:50:00 | Alberto Ferrari | Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension) | DAX Optimization Examples |
| 09:50:00 | William Assaf | Data Analysis / Cleaning Method and Tools / Data Demographics | Ethics in Data |
| 09:50:00 | Leslie Andrews | Other | Building a Strong Foundation for Data Analysis |
| 11:10:00 | Matthew Floyd | Data Presentation / Reports / Dashboards | Power BI Time Intelligence using a custom calendar |
| 11:10:00 | Matt Gordon | Other | Make Your Company Conversational using Azure Cognitive Services |
| 11:10:00 | Russel Loski | Data Importing Techniques and Tools (ex SSIS) | A metadata approach to fixed width files |
| 11:10:00 | Mike Byrd | Data Importing Techniques and Tools (ex SSIS) | Change Tracking: A Near Bullet-Proof ETL Synchronization Control |
| 11:10:00 | Jamey Johnston | Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension) | Code Like a Snake Charmer - Introduction to Python! |
| 13:30:00 | Michael McKinley | Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension) | Basics of Data Modeling for BI Reporting |
| 13:30:00 | Christine Assaf | Professional Development | Mastering your Resume Interview: Tips to Get Hired |
| 13:30:00 | Kevin Feasel | Data Analysis / Cleaning Method and Tools / Data Demographics | Getting Started with Apache Spark |
| 13:30:00 | Derek Wilson | Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension) | Data Vault on SQL Server Tabular Model and Power BI |
| 14:50:00 | Alicia Moniz | Other | AI For Good: Cognitive Services Vision |
| 14:50:00 | Alberto Ferrari | Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension) | Using calculation groups in DAX |
| 14:50:00 | Tracy Boggiano | Professional Development | More Common Than You Think: Mental Illness in Tech |
| 14:50:00 | Bob Phillips | Data Analysis / Cleaning Method and Tools / Data Demographics | Do I Need To M? |
| 16:10:00 | Wenbin Zhao | Data Analysis / Cleaning Method and Tools / Data Demographics | ETL Using Python, Pandas, and Jupyter Notebook |
| 16:10:00 | Brian Lee | Data Presentation / Reports / Dashboards | Power BI Ecosystem and Use Models Overview |
| 16:10:00 | Meagan Longoria | Data Presentation / Reports / Dashboards | Creating Accessible Power BI Reports |
| 16:10:00 | Ganesh Lohani | Professional Development | Building your Microsoft Business Intelligence (MSBI) Career |
Event Date: 08-02-2020 - Session time: 08:30:00 - Track: Professional Development
In this session, we'll go over steps you can take before, during and after the event to maximize the amount of great stuff you'll take away at the end (besides cool vendor swag). Not just keeping up on new technologies, but meeting new people, getting leads on solutions/opportunities, and an appreciation for the community you're in and what it has to offer.
Event Date: 08-02-2020 - Session time: 09:50:00 - Track: Data Analysis / Cleaning Method and Tools / Data Demographics
Today, more and more development is performed on very large datasets. Attendees will learn how to use Apache Spark, which is part of Databricks, to rapidly analyze lots of data. Learn how to use Databricks to reduces operational complexity to create solutions which can be scaled up or down depending on the amount of data needed to process without having to change the underlying code. Python, Jupyter Notebooks, and Apache Spark are the technologies used to create solutions within this session. No experience is required. Agenda
Event Date: 08-02-2020 - Session time: 09:50:00 - Track: Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension)
As you will see, most optimizations are the direct application of best practices, but the session has the additional takeaway of understanding what kind of performance you should expect from your formulas, and the improvement you might expect from learning how to optimize the model and the code.
Event Date: 08-02-2020 - Session time: 09:50:00 - Track: Data Analysis / Cleaning Method and Tools / Data Demographics
Event Date: 08-02-2020 - Session time: 09:50:00 - Track: Other
Event Date: 08-02-2020 - Session time: 11:10:00 - Track: Data Presentation / Reports / Dashboards
Event Date: 08-02-2020 - Session time: 11:10:00 - Track: Other
Event Date: 08-02-2020 - Session time: 11:10:00 - Track: Data Importing Techniques and Tools (ex SSIS)
To demonstrate such an approach, I build an Excel file describing US census data that has more than 300 columns of fixed width data. After demonstrating how this file communicates to business users, I will generate an SSIS package from that metadata using BIML Script. Then I will also look at how you can generate a SQL Server bulk insert format file from the same metadata. A small amount of C# code can generate quite a large extract.
Event Date: 08-02-2020 - Session time: 11:10:00 - Track: Data Importing Techniques and Tools (ex SSIS)
Event Date: 08-02-2020 - Session time: 11:10:00 - Track: Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension)
This session will be an introduction to the Python language including:
Attend this session to learn how Python can take your data analytics to the next level. We will use Python, SQL Server, and the Anaconda distribution of Python to learn the basics of Python and how it is integrated in the Microsoft stack! We will walk through a simple deployment of a machine learning model to see how it all works together and learn some basic data science fun
Event Date: 08-02-2020 - Session time: 13:30:00 - Track: Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension)
Event Date: 08-02-2020 - Session time: 13:30:00 - Track: Professional Development
Event Date: 08-02-2020 - Session time: 13:30:00 - Track: Data Analysis / Cleaning Method and Tools / Data Demographics
Event Date: 08-02-2020 - Session time: 13:30:00 - Track: Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension)
Event Date: 08-02-2020 - Session time: 14:50:00 - Track: Other
Join us for an introduction to the Cognitive Services Computer Vision and Custom Vision APIs on Azure.
In this session, we will look at the basics of Cognitive Services Vision. First learn how to create your Cognitive Services model. Then you can see how to train and improve accuracy. Finally, we will step through python code in Azure Notebooks to call the APIs.
After this session, you will get up and running in Cognitive Services Vision in under an hour!
Prerequisites: Attendees should have an Azure account, as well as an account on Azure Notebooks. Experience with coding in python is helpful, but not required.
Event Date: 08-02-2020 - Session time: 14:50:00 - Track: Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar, Fact vs Dimmension)
This session introduces the syntax of calculation groups, when they should be used and several examples of use cases. You will also learn how calculation groups work internally and what are the limits of this amazing tool.
Event Date: 08-02-2020 - Session time: 14:50:00 - Track: Professional Development
In this session, we will talk about what mental illness is and what it is not. How my mental illness has affected me. How it effects the tech industry. How mental illness can affect you and how you can tell if you are starting to have issues. What to say and what not to say to people you know that are affected by mental illness. Finally, how to get help and where reach out for help.
Event Date: 08-02-2020 - Session time: 14:50:00 - Track: Data Analysis / Cleaning Method and Tools / Data Demographics
But, and there is always a but, sometimes you need to do things that are just not available through the UI. This is where you need to get down and get dirty, and manage the M code directly (M being the language that drives Power Query).
This session is all about the value of developing skills in M. Starting with a brief intro to M and some references to resources to help develop those skills further, we will then demonstrate a number of things you can do by directly coding in M, things that are not as simple or just can't be done through the UI.
The session will be using Power Query in Excel as Excel is still the most used BI delivery tool, but all of the techniques and code also apply to Power BI.
Event Date: 08-02-2020 - Session time: 16:10:00 - Track: Data Analysis / Cleaning Method and Tools / Data Demographics
In this 60 minute session, I will show you how to set up and get it running on your laptop for a jupyter notebook environment and start improve your ETL workflow.
Event Date: 08-02-2020 - Session time: 16:10:00 - Track: Data Presentation / Reports / Dashboards
This session will provide an overview of the Power BI ecosystem, look at various tools and key capabilities, their stand-alone functionalities, and how they can be integrated with other tools and environments. The intention of the session is for the attendee to walk away with a greater understanding and appreciation of Power BI's capabilities, what you can do with "it", and gain new ideas on how to leverage the capabilities in Power BI ecosystem in your data reporting and analytics journey.
Event Date: 08-02-2020 - Session time: 16:10:00 - Track: Data Presentation / Reports / Dashboards
Event Date: 08-02-2020 - Session time: 16:10:00 - Track: Professional Development