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Sessions Found: 22
Face it, using SSIS to work with fixed width flat files is a pain.  The SSIS interface has you clicking around to mark each column. Then you use another interface to set each columns data types, etc.  And when you are done, you still need to document the file structure for your users.  What if you could simply document the file structure and then generate the ETL from the document?
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.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Data Importing Techniques and Tools (ex SSIS)

Level: Beginner

Session Code:

Date: February 08

Time: 11:10 AM - 12:10 PM

Room: 2

Are you curious about the role that AI will play in predictive modeling?  Are you wondering what the difference is between the Computer Vision API and the Custom Vision API?  Do you want a quick introduction to get you up to speed on both, so that you can quickly build and deploy a Cognitive Services model?

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.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Other

Level: Beginner

Session Code:

Date: February 08

Time: 2:50 PM - 3:50 PM

Room: 2

Come learn about the basics of data modeling for your business intelligence and reporting needs.  This course will cover several introductory modeling subjects, including:
  *  Transactional vs. Analytical models
  *  Kimball / Inman approaches
  *  The process for designing your data model
  *  Hierarchies / Parent-child relationships
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar,

Level: Beginner

Session Code:

Date: February 08

Time: 1:30 PM - 2:30 PM

Room: 2

We are living in a world full of data but what we need is information.  What is required to transform data into information?  What are the foundational activities your organization needs to do in order to produce analytics that you are confident in sharing?  In this session we will discuss what is needed for your organization to convert data into information, the basics of: Data Governance, Data Modeling and how to have an immediate impact using tools like Power BI to deliver value; and, Data Visualizations and telling stories with the data.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Other

Level: Beginner

Session Code:

Date: February 08

Time: 9:50 AM - 10:50 AM

Room: 1

Are you excited to know about the MSBI tools and work as a Business Intelligence Professional, a dynamic and rewarding career in Information Technology? If yes, this is the right time and place for you. In this session, I will give you the overview of the MSBI tools (SSIS, SSRS, SSAS, Power BI, Azure Machine Learning). I will also provide you some insights to build the MSBI career and to leverage the learning curve in Microsoft Data Platform, based on my knowledge and experience and the proven strategies and techniques.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Professional Development

Level: Beginner

Session Code:

Date: February 08

Time: 4:10 PM - 5:10 PM

Room: 3

Change Tracking came out with SQL Server 2008, but SS2012 almost eclipsed it with Change Data Capture. Change Tracking is now the red-headed stepchild, but in many cases may be the best solution for data ETL movement from an SQL Server OLTP database to a data warehouse or reporting database. This session will provide a review of change tracking syntax and implementation with detailed demos. It will then dive into an actual ETL subset implementation from the AdventureWorks database to a data warehouse solution (modified AdventureWorksDW) with detailed code discussion and demos using TSQL only (no SSIS).  A variation of this implementation has run every 5 minutes with never a failure in over 7 years.  Come learn how you can adapt the supplied code to have near real-time in your data warehouse (or reporting database).
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Importing Techniques and Tools (ex SSIS)

Level: Intermedia

Session Code:

Date: February 08

Time: 11:10 AM - 12:10 PM

Room: 3

Python is the one of the most popular programming languages used today and one of the most useful tools in the data scientist's tool belt, especially for machine learning. Python is integrated into the Microsoft stack in tools like Azure ML, Databricks, and SQL Server.

This session will be an introduction to the Python language including: 
1) Installing and Configuring Python
2) Accessing and Manipulating Data
3) Installing and Managing Packages
4) Creating and Using Objects/Variables
5) Controlling Flows and Functions
6) Controlling Flows and Functions 6) Python in MS Power BI, Azure ML, MSSQL, and Databricks. 

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
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar,

Level: Beginner

Session Code:

Date: February 08

Time: 11:10 AM - 12:10 PM

Room: 4

Accessibility is catering for your whole audience, including those with disabilities. According to the US Census Bureau, 19 percent of the of the population had a disability in 2010. Do you know if your reports are designed in an inclusive way? In this session, we'll discuss accessibility standards and regulations of which you may want to be aware, how users with disabilities can consume Power BI reports, and guidance and pitfalls when designing inclusive reports.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Presentation / Reports / Dashboards

Level: Intermedia

Session Code:

Date: February 08

Time: 4:10 PM - 5:10 PM

Room: 2

In this session, you will learn the basics of building a data vault to organize and store your companies disparate data on SQL Server.  Learn how Hubs, Links, and Satellite tables create options for storing a variety of data from multiple systems.  The data vault structures will then be used as the data source to create views designed for SQL Server Analysis Services Tabular models.  Finally, Power BI will be used to visual the data for your end users.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar,

Level: Beginner

Session Code:

Date: February 08

Time: 1:30 PM - 2:30 PM

Room: 1

How do you optimize a DAX expression? In this session we analyze some DAX expressions and Tabular models and, through the usage of DAX Studio and some understanding of the VertiPaq model, we will look at how to optimize them.
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.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Data Modeling Techniques, Tools (ex Star vs Snowflake, Tabluar,

Level: Advanced

Session Code:

Date: February 08

Time: 9:50 AM - 10:50 AM

Room: 3

Power Query is an powerful tool enabling the data analyst in creating usable data. It is one product that can truly claim to be user friendly, as so much of the functionality is available within the UI.

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.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Data Analysis / Cleaning Method and Tools / Data Demographics

Level: Intermedia

Session Code:

Date: February 08

Time: 2:50 PM - 3:50 PM

Room: 4

This session will explore a variety of considerations that modern data scientists and data practictioners must account for when gathering and presenting data, including topics on bias, construct analysis, and machine learning.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Analysis / Cleaning Method and Tools / Data Demographics

Level: Intermedia

Session Code:

Date: February 08

Time: 9:50 AM - 10:50 AM

Room: 2

ETL of large amount of data is always a daily task for data analysts and data scientists. While Excel and Text editors can handle a lot of the initial work, they have limitations. Python, in particular, Pandas library and Jupyter Notebook have becoming the primary choice of data analytics and data wrangling tools for data analysts world wide. 
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.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Analysis / Cleaning Method and Tools / Data Demographics

Level: Intermedia

Session Code:

Date: February 08

Time: 4:10 PM - 5:10 PM

Room: 1

As companies work to gain insight from ever-increasing amounts of data, data platform practitioners need tools which can scale along with the data. Early big data solutions in the Hadoop ecosystem assumed that data sizes overwhelmed available memory, emphasizing heavy disk usage to coordinate work between nodes. As the cost of memory decreases and the amount of memory available per server increases, we see a shift in the makeup of big data systems, emphasizing heavy memory usage instead of disk. Apache Spark, which focuses on memory-intensive operations, has taken advantage of this hardware shift to become the dominant solution for problems requiring distributed data. In this talk, we will take an introductory look at Apache Spark. We will review where it fits in the Hadoop ecosystem, cover how to get started and some of the basic functional programming concepts needed to understand Spark, and see examples of how we can use Spark to solve issues when analyzing large data sets.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Data Analysis / Cleaning Method and Tools / Data Demographics

Level: Beginner

Session Code:

Date: February 08

Time: 1:30 PM - 2:30 PM

Room: 3

Databricks is a very popular environment for developing data science solutions.  More and more companies are interested in Databricks as it is very simple to set up and contains a collaborative workspace for working with a team of people. In this session you will see how to create Machine Learning Solutions with multiple workflows starting with ETL, to data exploration, model experimentation, and lastly to a production release of a data science solution. 

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
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Data Analysis / Cleaning Method and Tools / Data Demographics

Level: Beginner

Session Code:

Date: February 08

Time: 9:50 AM - 10:50 AM

Room: 4

Customers and users increasingly demand more personal and prompt communication from companies and brands with which they interact. How can data professionals help fill that need? The incredible power and instant accessibility of the Azure Cognitive Services Language and Speech APIs, combined with other Azure services, put the power in our hands. From translating between languages to make communication more efficient to analyzing support communications to ensure customers are happy, Azure Cognitive Services allows data professionals to enhance a brand's interaction with and impression in the customer community. This demo-heavy sessions walks through practical applications of these APIs that you can apply at home or at work immediately after the session.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Other

Level: Beginner

Session Code:

Date: February 08

Time: 11:10 AM - 12:10 PM

Room: 1

Looking for a job? Learn trade secrets from an HR professional! Resume blunders and interview tips, this session will focus on the most important things you can do to get hired.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Professional Development

Level: Beginner

Session Code:

Date: February 08

Time: 1:30 PM - 2:30 PM

Room: 4

Mental illness is more common than you think.  One in four Americans suffers from a mental illness each year.  In the tech community, this is often not talked about.  Many times, people feel alone and isolated in the tech community with us mostly being introverted people.  It is time to start talking about mental illness out in the open and honestly about how it affects us and those around us.

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.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Professional Development

Level: Beginner

Session Code:

Date: February 08

Time: 2:50 PM - 3:50 PM

Room: 1

Looking to get the most out of your SQL Saturday, PASS Summit, or local user group meeting? Plan ahead!  Events aren't just about learning new things, they're about meeting new people, networking with peers, and learning different approaches to common issues.

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.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Professional Development

Level: Beginner

Session Code:

Date: February 08

Time: 8:30 AM - 9:30 AM

Room: 1

While Power BI is often known as a BI tool or visualization tool, it is more appropriately viewed as an ecosystem, as it includes various tools, capabilities and integration with other Microsoft and 3rd party tools. 
	
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.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Data Presentation / Reports / Dashboards

Level: Beginner

Session Code:

Date: February 08

Time: 4:10 PM - 5:10 PM

Room: 4

Sessions Found: 22
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