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Sessions Found: 35
Power BI is fast becoming a staple in many Business Intelligence solutions. And its feature set is expanding faster than the average user can assimilate. Take your knowledge of Power BI to the next level by incorporating some slick, 'no coding needed' features. Wow your boss by noon on Monday with advanced features you may not know existed, but leaned in this session. We'll let the attendees pick from a list of quick win and easy to implement topics such as Cortana Integration, Drill-through report pages, Power BI Mobile Dashboards, Bar Code readers, Query Folding (for performance), Excel Reports in Power BI and several others. We can't cover them all, so come vote on what is of the most interest to you!
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Information Delivery

Level: Beginner

Session Code:

Date: March 30

Time: 10:10 AM - 11:10 AM

Room: Canon

I’m sure you have heard about artificial intelligence because it’s next big thing and all major tech companies are involved in its development. Now you can implement it too directly in all your websites, mobile and desktop apps using Microsoft Cognitive Services. In this session you will get basic knowledge about artificial intelligence, machine learning and their applications, go over all 6 groups of Cognitive Services and see individual APIs available in Azure. We’ll see how to use pre-built and custom services. Also we will concentrate on some details and specifics of Cognitive Services implementation in Xamarin and Xamarin.Forms solutions. In the end, you will see a demo on how using exported model from Custom Vision service create image recognition app.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Professional Development

Level: Beginner

Session Code:

Date: March 30

Time: 11:20 AM - 12:20 PM

Room: Bretton Woods

Azure Data Factory - ADF - is a cloud data engineering solution. Like all data integration platforms (like SSIS), ADF is software development. 

Attend this session to learn: 
 - Pipeline data-load design patterns;
 - Pipeline execution design patterns.
 - Azure-SSIS execution design patterns.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Platform Architecture/Design

Level: Intermedia

Session Code:

Date: March 30

Time: 9:00 AM - 10:00 AM

Room: Jefferson

As more data services come online in Microsoft Azure, DBAs are being tasked with bringing these services into their organizations.  Azure Databricks is one such service that has the appeal of combining scalable compute resources with collaborative development and analytic tools in Notebooks and workspaces.  To the traditional DBA, however, many of the concepts and language support may be foreign. What the heck is Scala anyway?  This session is designed to introduce the DBA to the Azure Databricks workspace and show how to easily integrate it with upstream and downstream services like Azure Data Factory, Machine Learning and Power BI.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
BI Administration and Performance

Level: Beginner

Session Code:

Date: March 30

Time: 1:50 PM - 2:50 PM

Room: Adams

In this session we will explore the differences between Databricks and its foundation Spark, how easy it is to get started, what the Azure difference is, and common workloads in which we’re seeing it being used.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Advanced Analysis Techniques

Level: Beginner

Session Code:

Date: March 30

Time: 9:00 AM - 10:00 AM

Room: Monroe

With so many new technologies it can get confusing on the best approach to building a big data architecture.  The data lake is a great new concept, usually built in Hadoop, but what exactly is it and how does it fit in?  In this presentation I’ll discuss the four most common patterns in big data production implementations, the top-down vs bottoms-up approach to analytics, and how you can use a data lake and a RDBMS data warehouse together.  We will go into detail on the characteristics of a data lake and its benefits, and how you still need to perform the same data governance tasks in a data lake as you do in a data warehouse.  Come to this presentation to make sure your data lake does not turn into a data swamp!
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
BI Platform Architecture/Design

Level: Beginner

Session Code:

Date: March 30

Time: 11:20 AM - 12:20 PM

Room: Jefferson

Are you a DBA who does not have a background in SSAS or BI? Perhaps you're a BI analyst but never had to troubleshoot SSAS performance issues?
 
Join me for a mostly vendor-agnostic exploration of SSAS performance challenges. We'll break down SSAS workload and discuss factors that impact SSAS query performance. To close, will I show a brief demo of SentryOne's BI Sentry to bring everything together. 
 
When you leave, you will be armed with new insights into SSAS and how to tackle performance challenges.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Administration and Performance

Level: Beginner

Session Code:

Date: March 30

Time: 12:40 PM - 1:40 PM

Room: Adams

Are you a technologist who sometimes has a difficult time getting "the business" to sign off on the things you need?  Perhaps you have a great idea to improve something, but management just does not see the value that you see.  
 
Come to this session and you'll learn some new techniques on how to engage your busines counterparts, present an effective business case, and get them on your side!
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Administration and Performance

Level: Beginner

Session Code:

Date: March 30

Time: 9:00 AM - 10:00 AM

Room: Adams

Creating and Using Calendar Tables

There is a common need in analytics and reporting to aggregate data based on date attributes.  These may include weekdays, holidays, quarters, or specific times of the year.  Crunching these metrics on-the-fly can be slow and inefficient.

Calendar tables allow the complex conversions, definitions, and date-related metadata to be calculated ahead of time and stored in a static, reliable structure.  We can then use this table to avoid the need to perform any date math on the fly.  This not only saves time and computing resources, but also allows more complex analytics to be performed that would otherwise be very challenging.

This session delves into the design, implementation, and use of calendar tables, providing plenty of demos that illustrate their value and just how much fun they are!
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
BI Development

Level: Intermedia

Session Code:

Date: March 30

Time: 1:50 PM - 2:50 PM

Room: Washington

In order to effectively monitor SSIS performance, troubleshoot errors and understand the data linage in the production environment one needs to implement the package logging and Data auditing. SSIS already contains an Audit Transformation Component that captures information about the package metadata and the environment in which the package runs.

However, what if you encountered an error, or a package failure?  Suppose, a Data warehouse developer is performing an ETL to load a Dimension of a Data mart and would like to track the Data being processed. Audit Transformation Component cannot perform the job effectively.

So lets have an insight of how Auditing can be done by designing an SSIS  package that captures the Error information, DML operation on the table (Inserts/Updates/Deletes) along with the package metadata.

We'll create a package with an event handler that loads Data from a Staging to Dimension and creates an Audit table to track information on Data processing.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
BI Development

Level: Intermedia

Session Code:

Date: March 30

Time: 10:10 AM - 11:10 AM

Room: Washington

Geography often plays a big role in our data analysis. Power BI offers several standard map options to help us understand where our data happens. This session will explore the three standard maps, including ESRI. We will compare the type of data that best fits each map. We will also look at the ESRI Plus subscription and it's benefits. If you have data with a geographical component, this session will get you started mapping it.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Extended Session (90 minutes)

Track:
Advanced Analysis Techniques

Level: Beginner

Session Code:

Date: March 30

Time: 11:20 AM - 12:50 PM

Room: Monroe

Azure Data Warehouse is not Kimball's data warehouse. This session will discuss design and data modelling considerations when creating objects in Azure Data Warehouse to yield the best performance.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Platform Architecture/Design

Level: Advanced

Session Code:

Date: March 30

Time: 10:10 AM - 11:10 AM

Room: Jefferson

Grab your lunch, eat and discuss Diversity and Inclusion.  We will break into groups, network and discuss:

Making Diversity and Inclusion a priority at your organization: driving the use case and new policies
Improving Hiring, Retention and Promotion

Addressing Everyday Discrimination
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Platform Architecture/Design

Level: Beginner

Session Code:

Date: March 30

Time: 12:40 PM - 1:40 PM

Room: Jefferson

Many companies start off with a simple data mart for reporting. As the company grows, users become dependent on the data mart for monitoring and making decisions on Key Performance Indicators (KPI).

Unexpected information growth in your data mart may lead to a performance impacted reporting system. In short, your users will be lining up at your cube for their daily reports.

How do you reduce the size of your data mart and speed up data retrieval?  This presentation will review the following techniques to fix your woes.

Techniques:
1 – What is horizontal partitioning?
2 – Database sharding for daily information.
3 – Working with files and file groups.
3 – Partitioned views for performance.
4 – Table and Index partitions.
5 – Row Data Compression.
6 – Page Data Compression.
7 – Programming a sliding window.
8 – What is different in Azure SQL database?
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Platform Architecture/Design

Level: Intermedia

Session Code:

Date: March 30

Time: 3:00 PM - 4:00 PM

Room: Jefferson

The cloud is just using someone else's compute. You still need to care about and optimize for performance.  Just as a dropped call frustrates cellular customers, a BI report with data issues, high latency, connection timeouts will create the same frustration for users.  Do you want to catch the performance issues before your customers?  Do you want to automatically identify database issues and quickly drill down into details? Azure provides built in tools just to do that. 

In this session I will show you 4 of those tools.  You will learn how these tools can provide Performance overview of a database and recommendations that can improve workload performance.  Find top resource consuming queries, deeper insight into your databases resource (DTU) consumption and learn when to let Azure  automatically optimize your database. 

At the end of this session you will walk out knowing how to identify and tune Azure SQL database performance  issues with built in tools in Azure Portal.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
BI Administration and Performance

Level: Intermedia

Session Code:

Date: March 30

Time: 11:20 AM - 12:20 PM

Room: Adams

What is Intelligent Data Integration? SSIS (SQL Server Integration Services) packages developed using tried and true design patterns, built to participate in a DevOps enterprise practicing DILM (Data Integration Lifecycle Management), produced using Biml (Business Intelligence Markup Language) and executed using an SSIS
Framework.

Attend a day of training focused on intelligent data integration delivered by an experienced SSIS consultant who has also led an enterprise team of several ETL developers during multiple projects that spanned 2.5 years. And delivered. 

Attendees will learn:
- a holistic approach to data integration design.
- a methodology for enterprise data integration that spans development through operational support.
- how automation changes everything. Including data integration with SSIS.

Topics include:
1. SSIS Design Patterns
2. Executing SSIS in the Enterprise
3. Custom SSIS Execution Frameworks
4. DevOps and SSIS
5. Biml, Biml Frameworks, and Tools
Speaker:

Accompanying Materials:

No material found.

Session Type:
PreCons (480 minutes)

Track:
BI Administration and Performance

Level: Intermedia

Session Code:

Date: March 29

Time: 8:30 AM - 4:30 PM

Room: Adams

“Python” and “R” are two well-known data science languages being used today. Both of these languages are part of the open source community and have many free modules available for your use.

Which one of the languages do you choose as an enterprise standard?

My money is on the “Python” language, due to the fact it can be used to solve business problems other than ones related to data science.

Python is a general purpose programming language created by Guido van Rossum in 1991. It was designed for readability and easy syntax by using significant whitespace. The main goal was to allow programmers to solve problems using fewer lines of code.

During this pre-conference course, we will be covering the following topics.

Python Programming Basics
Introduction to Data Science with Python

This course is meant for beginners who want to learn Python. At the end of the day, you will have a solid understanding of the language and an introduction to the data science libraries.
Speaker:

Accompanying Materials:

No material found.

Session Type:
PreCons (480 minutes)

Track:
Advanced Analysis Techniques

Level: Intermedia

Session Code:

Date: March 29

Time: 8:30 AM - 4:30 PM

Room: Jefferson

Most database professionals know there are two different database design patterns - normal forms for OLTP databases and star schemas for data warehouses. We tend to discuss these separately. But these two designs actually work together when we create our table schemas.

In this session, we will review the basics of both normal forms and star schemas. We'll compare and contrast the two designs. We will then discuss how a normalized database design influences a star schema design and vice versa. 

By the end of the session, you will better understand how using the two designs together gives you a greater insight to how you use your data throughout its lifecycle.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Advanced Analysis Techniques

Level: Beginner

Session Code:

Date: March 30

Time: 3:00 PM - 4:00 PM

Room: Monroe

No matter the complexity of your BI application, Master Data Management can provide your organization the tools needed to conform, manage and simplify your dimensions. Attend this session and learn how Analytical MDM can forge quicker and more valuable insights.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Administration and Performance

Level: Intermedia

Session Code:

Date: March 30

Time: 10:10 AM - 11:10 AM

Room: Adams

Containerization and Micro-services are the future of development.  Learn how to structure your data management strategy to simplify the creation and integration of services across your organization.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
BI Development

Level: Beginner

Session Code:

Date: March 30

Time: 12:40 PM - 1:40 PM

Room: Washington

Sessions Found: 35
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