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Sessions Found: 58
Ever wonder how to select what columns need to be in an index definition and what columns should be in the INCLUDE clause.  This session will take a deep dive in looking at two SELECT queries on the AdventureWorks2017 database and what indexes give the best, adequate, and poor performance and their relation to disk space utilization.  Sometime what you have heard (word of mouth) is not always the overall best solution.  In addition ever wonder if covering indexes can be used for UPDATE statements -- answer is yes and a demo will show that.  And a final tidbit will be a demo how an unused index can affect a SELECT statement's performance poorly.  This session is about 60% demos and yields some surprising results.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
DBA

Level: Intermedia

Session Code:

Date: September 28

Time: 11:00 AM - 12:00 PM

Room: DBA2 (4206)

Aggregations are one of the most important optimization methods for managing big datasets in Power BI. Combined with Direct Query storage mode, they allow big datasets to be analyzed efficiently by answering high level analytical queries quickly from memory while sending more detailed queries back to the source database.

In this session, you will learn about the concept of aggregations, different table storage modes in Power BI, different kinds of aggregation tables, how to configure aggregation tables so that they can answer high level user queries, and finally how to use tools such as DAX Studio or Extended Events to determine if the aggregations are actually being used.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
PowerBI

Level: Intermedia

Session Code:

Date: September 28

Time: 10:00 AM - 11:00 AM

Room: Misc2 (4208)

Data Warehousing has been traditionally deployed via on-prem MPP solutions, and due to cloud modernization, and datacenter reduction footprint initiatives, organizations are looking out to establish a relationship with a cloud solution that can help them get off the traditional storage and compute licensing scheme, to easily scale their workloads without spending millions in newly acquired hardware, and to reduce their database administration operational tasks. 
Snowflake, RedShift and Teradata provide a path to migrate workloads into the cloud and allows a very reduced utilization expense for both compute and storage. That is at least, what the marketing says as it has a tacit disclaimer around it. 
Azure SQL Data Warehouse offers scalability, pay-as-you-go compute solutions, with data contained within the database boundaries. 
The presentation shows a side by side comparison, with pros and cons of each platform and debunks some of the myths that have surfaced.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Cloud

Level: Intermedia

Session Code:

Date: September 28

Time: 2:45 PM - 3:45 PM

Room: R5-Cloud (3206)

Are you a DBA or data professional working with out-dated technology or feel your skills are quickly becoming irrelevant? Stay ahead in today's ever changing tech space and take your career to the next level.

Join Mohammad Darab this session to explore the cutting-edge technology that SQL Server 2019 has to offer: Big Data Clusters.

Topics include:
-Big Data Cluster architecture and its components such as: Containers, Kubernetes and the newly enhanced Polybase
-Unique advantage of SQL Server Big Data Clusters
-Data Virtualization, Scale-out Data Marts, and Data Hub concepts
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Big Data/Data Science

Level: Beginner

Session Code:

Date: September 28

Time: 10:00 AM - 11:00 AM

Room: R7-BigData/DataSci (4103)

A data warehouse (DW) is a core component of business intelligence and a central data repository for different sources. This poses many challenges as the schema definition for those sources may be completely different from one another. In this presentation, we discuss how to create a data warehouse model that can support data from multiple systems. Oscar Garcia shows how to build a dimensional model which can enable us to import the data with different shapes into a data warehouse. We then create processes to transform and load the data using Apache Spark. We finally use Power BI to visualize the data from our data warehouse and Spark.


Learning Objectives:

Challenges when using disparate data sources (different models)

Define a common model to support the different model shapes (Star Schema)

Apache Spark Overview

Strategy for loading the different data-sets into the common model

Data analysis and visualization with Power BI
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Big Data/Data Science

Level: Beginner

Session Code:

Date: September 28

Time: 2:45 PM - 3:45 PM

Room: R7-BigData/DataSci (4103)

Usually when developers and DBAs talk about scaling databases we mean 'scaling up' our database server to handle the increased demands of our users.
But what if 'scaling up' isn't the only or best answer? 
What if we're building a multi-tenant SaaS application, and want to have a single front-end for each of our clients, but have multiple back-end databases to segregate customer data?
In this talk, we'll look at ways we can scale our SQL Server Databases 'out' instead of 'up'.
We will touch on a few database design considerations before diving into the Elastic Database Client libraries to see how we can add intelligent data-dependent-routing to our applications, ensuring that each request is routed to the correct database. 
Finally, we will explore how Azure Elastic Database Pools can be used to optimize our database workloads in Azure.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Cloud

Level: Intermedia

Session Code:

Date: September 28

Time: 10:00 AM - 11:00 AM

Room: R5-Cloud (3206)

With the rapid growth of cloud technologies, the role of the DBA is evolving. Data will continue to be one of the most important assets. But how we manage that data it is also evolving. We will discuss the skills needed for DBAs in the cloud with demos of the tasks performed by DBAs in the cloud. We will be using Google Cloud for the demos but the topics will apply to any cloud environment. Key Topics: VM vs Full Managed DBs, Fault Tolerance, Disaster Recovery, Performance, Security, Monitoring and Budget Management. Attendees will be provided  free Hands-on/Live access to run SQL in the Cloud.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Cloud

Level: Beginner

Session Code:

Date: September 28

Time: 11:00 AM - 12:00 PM

Room: R5-Cloud (3206)

You've heard about docker, but haven't found that use case for it yet or simply just don't have the time to learn it.  This session will start off showing you what docker is at a high level, and its many simple use cases.  You'll leave with enough knowledge to either use someone else's docker image or build your own.  All of this without needing to install docker on your machine. We'll go into how to spin up an environment using a cloud resource in minutes.  After that, we'll install a graphical interface for docker in a docker image to help speed up your learning.  From there, we will even spin up an SQL Server in a container that can start and stop in little to no time.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Docker & Powershell

Level: Beginner

Session Code:

Date: September 28

Time: 9:00 AM - 10:00 AM

Room: R4-Dev/Docker (3205)

This session is an introduction to the unique functionality offered by COZYROC to create integration packages that dynamically map columns at runtime. The standard SSIS Data Flow Task can only use static metadata which is defined when the package is initially designed. The mapping of columns is configured and remains unchanged until the package is re-opened and design changes are made, thus costing maintenance time and effort. Data Flow Task Plus extends the capabilities of the standard Microsoft Data Flow task in that it allows you to set up dynamic data flows, thus eliminating maintenance time and effort. Changes to tables and columns are automatically incorporated at run time without the need to change and redeploy the package. Columns and fields are mapped automatically at run time. Furthermore, the initial design time and effort may be greatly reduced when dealing with huge amounts of data in a large number of files and/or databases.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
ETL

Level: Intermedia

Session Code:

Date: September 28

Time: 12:15 PM - 1:15 PM

Room: R8-PowerBI/ETL (4205)

Data is everywhere and Data Science is a very popular topic among data analysts and BI professionals. In this session, I will cover the basic data science principles and methodologies using the Python programming language. I will also present some real-world data analysis case studies using the Python libraries, such as NumPy, pandas, Matplotlib, and SciPy.  This session will benefit to anyone who is looking to get started in the data science/ Data Analytics field.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Big Data/Data Science

Level: Beginner

Session Code:

Date: September 28

Time: 9:00 AM - 10:00 AM

Room: R7-BigData/DataSci (4103)

PolyBase is Microsoft's data virtualization technology, allowing you to integrate SQL Server with external systems such as Hadoop and Azure Blob Storage.  As of SQL Server 2019, PolyBase also allows you to connect to diverse systems such as Oracle, MongoDB, Cosmos DB, Teradata, Apache Spark, and even other SQL Server instances.  In this talk, we will walk through the mechanics of PolyBase, showing how we can write T-SQL queries to access data from heterogeneous sources.  We will investigate the Dynamic Management Views (DMVs) and other resources needed to tease out what the PolyBase engine is doing behind the scenes and where to go when things break down.  Finally, we will look at several interesting use cases for PolyBase in the modern data environment.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Big Data/Data Science

Level: Beginner

Session Code:

Date: September 28

Time: 11:00 AM - 12:00 PM

Room: R7-BigData/DataSci (4103)

In this session we will cover multiple data visualization tips to create more interactive Power BI reports and dashboards. Some of the Power BI features we will cover are report pages tooltips, drillthrough filters, better use of bookmarks, SVG Measures, and many more.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
PowerBI

Level: Beginner

Session Code:

Date: September 28

Time: 9:00 AM - 10:00 AM

Room: R1-PowerBI (3102)

This session focuses on the techniques to discover, retrieve, extract, import, shape, model and analyze the tons of free and interesting data available in the wild. From daily NYC subway turnstile data to coastal accident statistics gathered by the Coast Guard, this data is just waiting to be loaded into your favorite analytics tools like Power BI Desktop or Jupyter Notebooks to yield interesting and often unexpected results.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Big Data/Data Science

Level: Beginner

Session Code:

Date: September 28

Time: 12:15 PM - 1:15 PM

Room: R7-BigData/DataSci (4103)

If you want to use PowerBI, you'll want to learn the DAX language.  We will go over what, when and how to use it along with where to get help!  If you are an excel person, this might be an easy shift.  If you are not, then you will definitely want to understand this language if you or your teams are using PowerBI.
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
PowerBI

Level: Beginner

Session Code:

Date: September 28

Time: 9:00 AM - 10:00 AM

Room: Misc2 (4208)

In this demo driven session you will learn how to: prepare your computer for installation of the dbatools module, install dbatools and pre-requisites, use dbatools commands to automate routine tasks such as migrating logins and jobs, setup log shipping, and add databases to availability groups. 

At the end of the session, you will be able to return to your office with dbatools as a new tool in your toolkit to help you manage your SQL Server estate in a more efficient manner.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Docker & Powershell

Level: Intermedia

Session Code:

Date: September 28

Time: 11:00 AM - 12:00 PM

Room: R6-Misc&Security (4102)

SQL Server Concurrency Model is, perhaps, the most confusing and least understood part of SQL Server Internals. Blocking issues and deadlocks occur unexpectedly and negatively impact performance and user experience in the systems. Nevertheless, this model is well-structured and easy to understand when you analyze it from lock types and their lifetime, and compatibility standpoints. 

This, two-part session will explain why blocking and deadlocks occur, and how to troubleshoot them in your environments. First, it will provide the overview of SQL Server Concurrency Model and describe SQL Server locking behavior and root-causes of typical blocking issues. Next, the session will discuss how to capture and troubleshoot them using standard SQL Server tools, and how to simplify the analysis using Blocking Monitoring Framework developed by Dmitri.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
TSQL

Level: Intermedia

Session Code:

Date: September 28

Time: 1:30 PM - 2:30 PM

Room: R3-TSQL (3104)

This session will cover how to setup your database source code in a source code repository, configure your website application, configure continuous integration and continuous deployments of your database alongside your application using Azure DevOps, Red Gate DLM, and Octopus Deploy.
Speaker:

Accompanying Materials:

Session Type:
Regular Session (60 minutes)

Track:
Developer

Level: Intermedia

Session Code:

Date: September 28

Time: 11:00 AM - 12:00 PM

Room: Misc2 (4208)

Data breaches abound! Do you want to keep your company out of the headlines? What are some of the data privacy laws affecting you? How will encrypting data affect your database performance? What data fields should you encrypt?  What else can you do to protect your sensitive data?
 
In this session, we will review each option to encrypt data within SQL Server, Transparent Data Encryption, Cell Level Encryption and Always Encrypted. While we look at the encryption options, we will review both on-premise and cloud offerings.  This session will deep dive into setting up Always Encrypted encryption and share experiences implementing the encryption.   
 
You will leave this session with a deeper understanding about SQL Server encryption options and how encryption can affect your performance.  Also, you will gather information on how to fully protect and review your sensitive data usage.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
Security

Level: Beginner

Session Code:

Date: September 28

Time: 9:00 AM - 10:00 AM

Room: R6-Misc&Security (4102)

Azure Data Factory Version 2 (ADFv2) Data Flows is the ETL/ELT tool of choice for highly scalable data integration solutions in the cloud. Learn how to build data pipelines with complex logic using Data Flows and how to optimize read and write performance to load modern data warehouses and data lake architectures. Attendees will walk away with a basic knowledge on how to create data pipelines leveraging ADFv2 Data Flows and how to integrate other Azure services for Big Data Analytics and Machine Learning.
Speaker:

Accompanying Materials:

No material found.

Session Type:
Regular Session (60 minutes)

Track:
ETL

Level: Beginner

Session Code:

Date: September 28

Time: 2:45 PM - 3:45 PM

Room: R8-PowerBI/ETL (4205)

If you're using Dynamic Data Masking, Row-Level-Security or just SQL Server and you don't know how to hack it, then come to this session. I have some demos may leave you in aah. I'll show you how to also protect yourself against these hacks, plus how to add your database to source control with Azure DevOps, TFS or GitHub to better manage your database changes/deployments. 

- AGENDA:
1. TDS
2. DDM
3. RLS
4. Database Source Control 

We'll have plenty of time for Q&A. I hope to see you there!
Speaker:

Session Type:
Regular Session (60 minutes)

Track:
Security

Level: Advanced

Session Code:

Date: September 28

Time: 1:30 PM - 2:30 PM

Room: R6-Misc&Security (4102)

Sessions Found: 58
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