Deep Dive into Blocking and Deadlocks Troubleshooting
Abstract: AI is now becoming the part of every software workload. Widespread use of mobile devices and powerful personal computing have driven a major shift among organizations of all types to adopt Artificial Intelligence (AI) using scalable, cost-efficient cloud computing infrastructure. In this talk, you will learn about the application of AI technologies in the cloud. We will help you understand how to add pre-built AI capabilities like object detection, face understanding, translation and speech to applications. We will show how developers can build Cognitive Search applications that understand deep content in images, text and other data. We will also show how the platform can be used to build your own custom AI models for predictive applications and how to use the Azure platform to accelerate machine learning. Key Learning: By the end of this session, developers will know how to leverage new tools and resources to build intelligent apps and customize those apps on Azure.
Abstract: Deploying and managing SQL Servers configuration on a large scale can be a daunting task even for the most experienced of DBAs. In todays cloud world, where speed and agility is a key driver, less manual touch and more automation is the way to go forward. Azure Automation Desired State Configuration (DSC) provides a highly available configuration management solution. It allows DBAs and DevOps Engineers to manage SQL Server configuration as a Code and opening possibilities to automate and reduce unwanted change in their environment. Key Learning: In this session we will explore, how you can consistently deploy, reliably monitor, and automatically update the desired state of all your SQL Servers, at scale from the cloud. It will help the audience to answer the below questions – How do I ensure all of my SQL Servers are matching their intended configuration and remain in the correct state? How do I prevent SQL Server configuration from drifting from the desired state, due to changes made by people, process, and programs? How do I ensure new SQL Server deployments match the configuration of existing deployments? How do I do all of the above, consistently, across on-premises SQL Servers and those in public clouds? Demos: Demos Overview and setup of Azure Automation DSC Deploying SQL Server using Azure automation DSC Managing configuration drift using Azure automation DSC
Open-Talks are 30 minutes free-flowing discussion on a specific topic. No laptops, no PPTs, no demos only discussion and Q & A
Open-Talks are 30 minutes free-flowing discussion on a specific topic. No laptops, no PPTs, no demos only discussion and Q & A
Transportation Accommodation
Abstract: What are bots? Why there is so much talk about bots? How do they work? How can I build an Intelligent bot? Come to this session to get answers for the above questions. In this session you will get to learn on how to build a Bot using Azure Bot Service and add intelligence using Cognitive Services and Machine Learning. You will also get to learn how to integrate your bot with Skype, Slack, Microsoft Teams and other platforms. Finally we will secure the bot using Azure Active Directory. Key Learning: Audience can come and get to learn about how to develop an intelligent bot using Azure Demos: Develop a appointment booking bot and train the bot using Azure Machine Learning and adding intelligence to it using Cognitive Services
Building a Database DevOps Pipeline in the Cloud under 59 minutes
Creating your first intelligent Bot
Abstract: 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 standpoint. 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.
5. Use the Search box on the top right corner of the table. You can search on any keyword including session type, speaker name, session title, track, level, etc. The search is instant and also searches within the abstract.
Azure SQL Database the intelligent cloud database on autopilot that lets you focus on your business
Abstract: This session is all about getting away from manual SSIS packages. Instead of reinventing the wheel every time you need to change or extend a package, lets talk about metadata models and how we can use them to design and describe our data warehouses and packages. We will cover the gamut from initial design, to maintenance and support, and even documentation and compliance. In addition, well see how the Business Intelligence Markup Language (Biml) can help us translate our metadata into a ready-to-use SSIS solution! Key Learning: good understanding about the importance of metadata, especially in a world where more and more Scenarios are migrated from on premise to the Cloud Basic understanding of Biml Tips and Tricks on how to automate SSIS and ADF development based on Meta Data Demos: Build an on premise SSIS solution from metadata, then build the same solution for ADF from the same metadata
Data Partitioning for Database Architects and Mere Mortals
Abstract: There is a natural limit to how many dataflows you can run in parallel in SSIS. Regardless of whether your limit is on the source or destination side, you will eventually reach those limits. You might have set up all your package orchestration in a way that made perfect sense at that time, but over time, some tables grow faster than expected and others dont grow at all. Due to foreign key relationships, you may not be able simply to shuffle the dataflow tasks around to maximize throughput. Manual reengineering along these lines would potentially be very time consuming, and even worse, the result would be obsolete shortly thereafter. This session is about using the Business Intelligence Markup Language (Biml) to monitor and control your orchestration patterns. By automatically analyzing the results in ETL logs, well be able to automate our staging orchestration! Key Learning: Audience will get a basic understanding of Biml (the Business Intelligence Markup Language), then well focus on how we can use it to automatically improve SSIS performance Demos: – Optimizing unit of work (how many Containers to run) – Pattern Evaluation (which connector etc. is best) – Dependencies (get FK Constraints and automatically lay the package out based on it)
Abstract: One of the biggest issues in database performance centers around storage. Its also one of the hardest places to troubleshoot performance issues because storage engineers and database administrators often do not speak the same language. In this session, well be looking at storage, both on premises as cloud, from both the database and storage perspectives.
Azure SQL Data Warehouse and Azure Databricks: Integration for the Modern Data Warehouse
4. Data Platform Summit 2018 has multiple parallel tracks with specific abbreviations: Administration / Database Administration (DBA), Development / Data Driven Development / Application Development (DEV), Architecture (ARCH), Business Intelligence & Advanced Analytics (BIA), Big Data (BD), Data Science / Artificial Intelligence / Machine Learning (DS), IoT, NoSQL & Open Source (IoT, NoSQL, OSS), & Career Growth (CG)
Abstract: SQL Server 2016 comes up with a very exciting feature called Temporal tables. You can make queries to historical data lot easier by using this feature. The mechanism is very simple however you all should know it in depth to make sure you can use it efficiently. And this is exactly what I am going to do during this session show you how to create temporal tables, how to use and manage them Key Learning: WHat is Temporal Tables How to use them How to use them in Hybrid scenario How to manage & optimize Demos: I do ONLY demos, no slides (almost)
Chalk-Talks are 30 minutes sessions focussing on conceptual & architectural understanding, that too with only whiteboard and marker. No Laptops, no PPTs, no demos only whiteboard-ing!
Open-Talks are 30 minutes free-flowing discussion on a specific topic. No laptops, no PPTs, no demos only discussion and Q & A
Abstract: Azure Relational Database Platform- Microsofts fully managed, database-as-a-service offering solves the demands of todays data estate involving omnipresence, heterogeneous and explosion. Built on worlds top relational database management system, SQL Server, as well as popular Community Editions of OSS databases PostgreSQL and MySQL, the platform offers multiple choices to our customers to meet their data needs it consists of three options of Azure SQL Database (singleton, elastic pools and managed instances) as well as Azure Database for PostgreSQL and MySQL. In this session, you will learn about the latest innovations in Microsofts Azure relational database family and how customers are using this to modernize their applications in a number of ways, from simply re-hosting applications and corresponding databases to Azure to refactoring or in some cases re-architecting the application stack in order to take full advantage of the benefits of our managed services in the long run. Our most recent version of Azure SQL Database, PostgreSQL and MySQL combines advanced intelligence, enterprise-grade performance, high-availability, and industry-leading security in one easy-to-use database. Thanks to innovations such as In-Memory OLTP, Columnstore indexes, and our Intelligent Query Processing feature family, customers can rely on Azure Relational Database for their relational data management needs, from managing just a few megabytes of transactional data to driving the most data-intensive, mission-critical applications requiring advanced data processing at global scale. You will also learn how to quickly and seamlessly migrate and modernize your datacentre to the cloud with Azure Database Migration Service. With Microsofts Azure Relational Database Platform, you can focus on your business and leave the rest to us. Key Learning: 1. New offerings in Azure Relational Database Platform such as Managed Instance, PostgreSQL and MySQL 2. Capabilities provided by the new services 3. Simplified migration of database and applications from on-premise datacentre to Azure Demos: Migration of databases from on-prem to Azure SQL Database Managed Instance, PostgreSQL and MySQL
Transitioning from a DBA to a Manager
Travelling in time with SQL Server 2016
Ajay Jagannathan / Sudhakar Sannakkayala
Abstract: Ever wonder why SSIS runs so slow? Watch SSIS author Andy Leonard as he runs test loads using sample and real-world data and shows you how to tune SQL Server 2016 Integration Services (SSIS 2016) packages. Well start by experimenting with SSIS design patterns to improve performance loading AdventureWorks data. We will implement different change detection patterns and compare execution performance for each. Then, well explain a Data Flow Tasks bottleneck when loading binary large objects – or Blobs. Finally, well demonstrate a design pattern that uses a Script Component in a Data Flow to boost load performance to MySql, whether on-premises or in the cloud. Key Learning: SSIS Data Flow Internals and tips on performance-tuning SSIS Data Flow Tasks. Demos: There are three demos in this session: 1. Change detection patterns for performance 2. Blob load performance 3. Improve MySql load performance using the SSIS Data Flow Script Component.
Abstract: Unstructured data is not something infrequent now and not ignorable, it is becoming a part of almost all data-oriented solutions. Therefore, we just cannot ignore them and continue our journey, we should learn how to process them and make them as part of our data solutions. However, unfamiliar platform and technologies such as Hadoop, Hive, Pig, even HDInsight slow down our joining with this arena. But no need to worry, Microsoft has given us a new facility to work with unstructured data using familiar technologies, yes, it is Azure Data Lake Analytics. Join this session to understand Data Lake Analytics, its internal work, difference between Hadoop and ADLA and, how it can be used for processing text-heavy row-oriented unstructured files and images. Key Learning: What is semi-structured and unstructured data What is Hadoop and related sub projects What is Azure Data Lake Analytics and how it helps on processing data What is U-SQL and how to use it for processing data Demos: Creating an Azure Data Lake Analytics account- this shows the way of creating it and areas to be considered Processing unstructured text files using U-SQL, along with C.net Processing images using U-SQL, along with ML libraries
Tips and tricks for successful In-Memory OLTP implementation
Abstract: Real-world data is naturally connected. Learn how to create graph database applications on Azure Cosmos DB and explore the different solutions that it provides to common data scenarios in the enterprise. We will also cover customer cases that currently leverage graph databases in their day-to-day workloads.
Chalk-Talks are 30 minutes sessions focussing on conceptual & architectural understanding, that too with only whiteboard and marker. No Laptops, no PPTs, no demos only whiteboard-ing!
Making unstructured data analysis-ready using Data Lake Analytics
How to Maintain the Same Level of utilities in Cloud Deployments – Securability, Reliability and Scalability.
Abstract: I would like to invite to the session about Microsoft Azure Data Lake and the USQL. I would like to show how quickly you can do data analysis using traditional C and a new language that is a bit similar to the TSQL. I will also show more complicated things -how to run Python and R scripts to perform even more robust analysis Key Learning: USQL – how to start, how to use it, how to manipulate a large datasets, how to play wirh R and python Demos: I do demos, no slides
Test Driven Development in SQL Server how to deploy database code safer
How to build a robot and the data implications
Migrating to Azure SQL Database a real world customer success story
Transportation Accommodation
Open-Talks are 30 minutes free-flowing discussion on a specific topic. No laptops, no PPTs, no demos only discussion and Q & A
Chalk-Talks are 30 minutes sessions focussing on conceptual & architectural understanding, that too with only whiteboard and marker. No Laptops, no PPTs, no demos only whiteboard-ing!
Abstract: Test Dr
1. This is Part 2 of the Session Release. Release Date: 26th June, 2018. Session Count: 95. Third (Final) part will be released in the month of July.
For example, if you type Azure, all sessions that have Azure in their title or abstract will be displayed.6. There might be minor adjustments to the sessions & schedule without any prior notice.7. Errors/Corrections? Write to admin[at]dataplatformgeeks.com & satya[at]dataplatformgeeks.com.8.Learn moreabout DPS 2018 registration.9. The pre-cons (full-day in-depth classroom training) has limited seats now.Learn moreabout Pre-Cons.
Modernize your data estate on Microsofts Azure Relational Database Platform (Azure SQL Database, PostgreSQL, MySQL
Building your Big Data and Advanced Analytics Pipeline on Azure using Azure Data Factory
Abstract: In this demo-tastic presentation, SSIS trainer, author, and consultant Andy Leonard explains the what, why, and how of a custom SSIS framework that delivers metadata-driven package execution. Key Learning: Key takeaways: 1) Attendees will learn a metadata-driven approach to SSIS package execution. 2) Attendees will learn a method for executing packages stored in any Catalog Folder or Catalog Project. Demos: We will hack the SSIS Catalog to generate a stored procedure used to execute SSIS packages stored anywhere in the SSIS Catalog.
Leveraging Microsoft PowerShell for Managing SQL Server VMs on Amazon AWS
Azure Data Factory Customer stories and Roadmap
Whats in an ensemble? An intro to Data Vault
Abstract: In this session, we will focus on Azure Data Factorys orchestration capabilities and how it could meet the ETL needs for Big Data and Advanced Analytics projects. We will use User Interface to create ETL/ ELT pipelines and use Azure Databricks for transforming the data. We will see some end-to-end demos on how Customers leverage Azure Data Factorys Control flow and Data flow in their Data pipelines. Security and Performance will be the major consideration in this session. Key Learning: – ETL/ ELT pipeline orchestrating service on Azure (Azure Data Factory) – Operationalizing Databricks on Azure Demos: – End-to-end Pipeline pulling data from on-premise and Transforming it on Cloud and loading it in a DW – UI authoring in ADF – Databricks notebook orchestration in ADF – Parameterization support and control flow in ADF
Abstract: The SSRS 2017 REST API provides programmatic access to the objects in a SQL Server 2017 Reporting Services report server catalog. The REST API exposes endpoints to navigate the folder hierarchy, discover the contents of a folder, or download a report definition. In this session you will learn a) How to connect to SSRS Report Server catalog using REST API? b) How to use the different REST API endpoints to access Datasets, Paginated reports, Mobile Reports, Folders, Comments, Subscriptions? c) How to test API Requests and Responses using Postman? d) How to embed SSRS reports in MVC Core applications? Key Learning: Learn how to query and use the new SSRS 2017 REST API in your applications Demos: Demo a ASP.NET Core Web Application that loads all SSRS 2017 reports using the SSRS 2017 REST API
Chalk-Talks are 30 minutes sessions focussing on conceptual & architectural understanding, that too with only whiteboard and marker. No Laptops, no PPTs, no demos only whiteboard-ing!
How to take advantage of scale out graph in Azure Cosmos DB
Abstract: Azure SQL Database is Microsofts fully managed, database-as-a-service offering based on the worlds best relational database management system, SQL Server. It consists of three deployment options – managed singleton database, managed elastic pools and managed instances that will help you with your data estate modernization. In this session you will see how Azure SQL Database, uses machine learning and best practices to ensure your database is always performing at its best. In this session you will learn about features like Adaptive Query Processing, Auto-tuning and Performance Recommendations, to see how Azure SQL Database can help you spend more time developing applications and less time managing your databases. You will also learn about new security features like Vulnerability Assessment, Information Protection, Thread Detection and Always Encrypted to see how Azure SQL Database is securing your data in the most secure database on the planet. With Azure SQL Database, you can focus on your business and leave the rest to us. Key Learning: 1. Learn how performance capabilities such as Adaptive query processing, auto tuning and performance recommendations help alleviate common database administration headaches 2. Learn how to easily secure your database using features like Vulnerability Assessment, Information Protection, Threat detection and Always Encrypted. Demos: 1. Auto tuning 2. Performance recommendations 3. Vulnerability Assessment 4. Information Protection 5. Always Encrypted
Row Level Security now and in the past – my working solutions
Deploy and Manage SQL Server Configuration as a CODE
Abstract: Managing SQL Server VMs on Amazon AWS can be cumbersome if you simply rely on the graphical user interface. Imagine having to manage multiple SQL Server VMs as part of your day-to-day operations. You can leverage Microsoft PowerShell to automate repetitive tasks that involve managing SQL Server VMs on Amazon AWS. In this session, learn how to use the AWS Tools for Windows PowerShell, the different PowerShell cmdlets for managing SQL Server VMs on Amazon AWS and how to write scripts to automate DBA repetitive tasks. Key Learning: 1) Explore the AWS Tools for Windows PowerShell 2) Learn how to manage SQL Server VMs on Amazon AWS using PowerShell 3) Learn how to automate operational SQL Server administrative tasks using PowerShell scripting Demos: Walkthrough of using AWS Tools for Windows PowerShell to deploy and manage a SQL Server VM on AWS
Getting Started with Linux for the SQL Server DBA
Improving data quality with Data Science and Machine Learning (no math required!)
How Artificial Intelligence (AI) will transform modern workspace?
Important Notes. Please Read Carefully.
Abstract: Data partitioning is the valuable technique that may dramatically simplify database administration and improve system availability and performance. Contrary to popular believe, it is not limited to partitioned tables and may be implemented with any version and edition of SQL Server. This session demonstrates the data partitioning techniques available in the various editions of SQL Server and discusses benefits, downsides and best use-cases for them. The session will also show how data partitioning helps boost performance of systems handling a mixed workload, improves cardinality estimations with large tables, and reduces the systems storage cost. Demos: Multiple demos (40-50% of content)
Abstract: With the introduction of SQL Server 2017 for Linux, there is no escaping the fact that SQL Server DBAs need to be familiar with the Linux operating system. So, how do you start? In this session, you will learn the most valuable fundamentals and commands that are important to the DBA when managing a database in a Linux environment. You will learn what is common between Windows and Linux so you can leverage information that you already know to get comfortable with managing SQL server on Linux. Key Learning: 1) Learn the fundamentals of the Linux operating system 2) Learn the differences between Windows and Linux that apply to SQL Server 3) Learn the most common commands that SQL Server DBAs need to know in order to perform administrative tasks in Linux Demos: Managing SQL Server on Red Hat Linux via PuTTy and PowerShell
Abstract: As your cloud data warehouse grows, you need to make sure that your implementation is future proof. In this session, you will learn how customers are using Azure SQL Data Warehouse and Azure Databricks to tackle some of the most complicated problems in the industry at scale. Key Learning: After this talk the audience will know: Overall architecture of SQL Data Warehouse Architecture of Azure DataBricks Implementation details on the Azure SQL DW and Databricks Connector. Use cases and scenarios for how and when to use both services to create Modern Data Warehouse Demos: I will have two demos: The first will be an ETL pipeline using Databricks to clean data and write it into SQL DW. The second will be using the connector to pull data from SQL DW and use databricks to do Machine Learning over the data.
Open-Talks are 30 minutes free-flowing discussion on a specific topic. No laptops, no PPTs, no demos only discussion and Q & A
Abstract: DevOps processes encompass both Continuous Integration and Continuous Delivery. Continuous integration is based around automated builds and tests. Continuous Delivery allows both application developers, database developers and DBAs alike to deploy better quality code/software. In this DEMO heavy session, we will start off with source code only. Over the course of 59 minutes we will build a deployment pipeline that starts off with pushing our database and application code to source control. We will utilize Visual Studio Team Services to automate our build and tests and perform Continuous Integration operations. The output of these operations will be a standardized package of our built solution. Utilizing PowerShell in the form of Infrastructure as Code, we will spin up multiple Azure based environments that will be deployed to using automated Continuous Delivery processes. The finished result will be an automated and reliable deployment pipeline that was built under 59 minutes. Key Learning: The audience will learn the fundamentals of DevOps. The DEMO will be instructive and will showcase the presented philosophies of DevOps by using tools and techniques to build a deployment pipeline for our database. The audience will learn how to use Infrastructure as Code, Azure Resource Manager and Azure PowerShell to automate the setup, configuration and deployment of database/application resources used in a cloud based DevOps pipeline. The audience will gain knowledge around vital steps in a DevOps pipeline – namely: Build and Test Automation (Continuous Integration) Deployment Automation (Continuous Delivery) Demos: The DEMO will take an on premises database and source code for a web app and create a deployment pipeline using git source control, SSDT or Redgate tools, VSTS , powershell and Azure. The outcome is a fully deployable pipeline for our database and applications – all under 59 minutes.
3. Breakout sessions are of 75 minutes each.
Abstract: Data Quality is one of those things that we generally dont pay attention to until it comes and bites us, and when it does, its usually a customer that notices it. As always, the poor beleaguered developer and database guy get to pay the price and work long hours and over the weekend to track things down and sort things out. In the good old days we could rely on things like MS Data Quality Services to come to the rescue, however, now we operate in the cloud with a mixture of Vendor products, database types and at different scale, so what are the options open to us, especially on a limited budget? This session will examine using some basic Data Science and Machine Learning techniques along with open source solutions and tools, to help improve your data quality, no matter the format of the data and where it is stored. It will also demonstrate a new Open Source Data Validation/Quality toolkit Allen is developing that runs natively in the cloud for both data at rest and live streaming data in motion. Key Learning: At the end of this session the audience will have a better appreciation for data quality, and the options open to them for providing solutions to the problem. They will learn new techniques for identifying problem areas, and how to use basic machine learning as part of their daily data toolkit. Demos: Demonstration of QA and data validation
Why should we focus more on logical data warehouse than physical data warehouse?
Abstract: In this session we will review the differences between deploying Microsoft SQL Server in Microsoft Azure and on-premises from a Security, Reliability and Scalability perspective. Join us for this fun session and learn how to improve the security, reliability and scalability of your Azure deployments of SQL Server Key Learning: Well review the common mistakes which people make when deploying SQL Server Virtual Machines to Azure which can lead to security problems including data breaches. Well review the common performance problems which people encounter, and how to resolve them. Well review the common scalability misunderstandings of Azure and SQL Server Virtual Machines.
Abstract: Welcome to the dungeon. Yes, SQL Server memory concepts are like entering a dungeon where you are guaranteed to get lost. Its dark and complex out there and not many have come back alive. Join Microsoft Certified Master of SQL Server, Amit Bansal, and find your way out from the dungeon. In this deep-dive session you will understand SQL Server memory architecture, how the database engine consumes memory and how to track memory usage. Complex concepts will be made simple and you will see some light beyond the darkness. This session will be an eye-opener for you. Assured. Key Learning: Welcome to the dungeon. Yes, SQL Server memory concepts are like entering a dungeon where you are guaranteed to get lost. Its dark and complex out there and not many have come back alive. Join Microsoft Certified Master of SQL Server, Amit Bansal, and find your way out from the dungeon. In this deep-dive session you will understand SQL Server memory architecture, how the database engine consumes memory and how to track memory usage. Complex concepts will be made simple and you will see some light beyond the darkness. This session will be an eye-opener for you. Assured. Demos: Welcome to the dungeon. Yes, SQL Server memory concepts are like entering a dungeon where you are guaranteed to get lost. Its dark and complex out there and not many have come back alive. Join Microsoft Certified Master of SQL Server, Amit Bansal, and find your way out from the dungeon. In this deep-dive session you will understand SQL Server memory architecture, how the database engine consumes memory and how to track memory usage. Complex concepts will be made simple and you will see some light beyond the darkness. This session will be an eye-opener for you. Assured.