We are progressively releasing DPS 2020 session recordings for the community. You will have free access. Keep watching this space for more content each week. This repository will have 150+ session recordings in due course of time. Also, note that Data Platform Virtual Summit 2021 has been announced.
|Raj Pochiraju & Mukesh Kumar||Data Administration||Database modernization best practices and lessons learned through customer engagements||In this session you will learn the real-world ins and outs of how we successfully migrated customers to Azure data platform.|
You will get a detailed view of Microsoft investments accelerating Azure SQL migrations, the migration lifecycle phases, and specific tools/ services help you in the migration journey.
You will listen to real world customer migration case studies, the specific migration strategies adopted and best practices implemented.
#AzureSQL #DMS #SQLMigration
|Melony Qin||Data Administration||Administrating Big Data Clusters ( BDC )||SQL Server Big Data Clusters (BDC) is a cloud-native, platform-agnostic, open data platform for analytics at any scale orchestrated by Kubernetes, it unites SQL Server with Apache Spark to deliver the best data analytics and machine learning experience. Join this session if you are interested in the administration scenarios of the big data clusters, including tooling for monitoring, how to deploy and secure the environment, and to learn about the latest improvements.|
#SQLServer #BigDataClusters #Kubernetes
|Tejas Shah||Data Administration||Deployment, High Availability and Performance guidance for SQL Server on Linux in Azure IaaS ecosystem||SQL Server on Linux has been one of the fasted growing database on Linux platform over last couple of years. At the same time many customers are looking to migrate their SQL Server instances and SQL based applications to the cloud to take advantage of scalability, flexibility, advanced high availability and disaster recovery options, optimized licensing scenarios, access to Azure monitoring & Azure security and advisory technologies. If you are considering SQL Server on Linux in cloud, look no further than Azure. In this session you will learn about how to quickly deploy production grade SQL Server on Linux in Azure ecosystem, including new fully supported High Availability configuration. Youll learn how to configure AD authentication reliably and quickly with new and improved experience. Youll also see suggestions on how to get best performance out of SQL Server on Linux in Azure. We look forward to seeing you there!|
|Mihaela Blendea||Architecture||Gain insights with SQL Server Big Data Clusters on Red Hat OpenShift||Big Data Clusters (BDC) is a set of capabilities introduced in SQL Server 2019 to help achieve data-driven business insights from ever increasing sources and amounts of data. With BDC, organizations can run containerized Apache Spark and Hadoop Data File System (HDFS) in an integrated matter side by side with SQL Server, in a single, secure and unified data platform. BDC requires Linux containers and Kubernetes, and recently Red Hat OpenShift was added as a commercially supported Kubernetes platform for BDC. OpenShift helps achieve the desired agility, consistency, flexibility, scalability, portability, etc. for data science and application development workflows. In this session, you will learn about BDC on OpenShift architecture, key capabilities and use cases, best practices, and technical resources to get you up to speed.|
|Javier Villegas||Data Administration||Monitoring And Troubleshooting SQL Server Environments Using Free Community Tools||In this session we will see how to monitor and troubleshoot different SQL Server environments using free tools developed by community experts|
We will cover First Responder Kit , Diagnostics Queries, BPCCheck, dbatools / dbachecks and more
|Harsh Chawla||Professional Developement||DBA to Data engineer||How transition from monolithic to Microservices applications brought this radical change|
Evolution of Data engineering and data scientist roles
Transition from Data warehouse to Modern data warehouses
Transition from Data mining to Advanced data analytics
Real time and batch mode data processing
Lambda and Kappa Architecture
Anatomy of Modern data warehouse and Advanced data analytics solutions
|Michelle Gutzait||Architecture||Hey! I really need to save on SQL Server license costs, would you help me consolidate?||Abstract In this session, Michelle will talk about consolidation options for SQL Server environments, discuss license costs reduction, Cloud alternatives and provide examples from real customers.|
Tags: #sqlserver #consolidation #azure #sqlserverconsolidation #sqlazuredatabase
|Daron Yondem||Development||Cosmos DB: Jack of All Trades, Master of Many||How would it look like if you were building a wishlist for an imaginary database; turnkey global distribution, 5 well-defined consistency levels, SLAs across 4 dimensions (High Availability, Performance Latency, Performance Throughput, and Data Consistency), Schema-agnostic automatic indexing, Key-Value, Tabular, Document, Graph, Relational Data Models, MongoDB, Gremlin, T-SQL API support... Did we go too far? Not really. So far we have just listed some of the features of CosmosDB. Come and join me to take a closer look and see if it is all blue skies, or maybe not?||Watch Now|
|Tracy Boggiano||Professional Developement||Mental Health and Wellness in IT: Safeguarding our most precious resource||One in four Americans suffers from a mental health challenge each year. In the tech community, this number rises to 42%. The stigma associated with discussions around mental health, as well as how it can negatively impact your work and home life, make people reluctant to discuss the topic. Now is the time to start discussing mental health in tech and how to take advantage of the opportunity to safeguard our most precious resource: people. We\'ll discuss how mental health affects job quality, including sharing examples from my professional life. We\'ll discuss the four primary workplace factors which play a pivotal role in mental health challenges in the tech community. I\'ll provide tips on what is best to say and not say to people you know whose lives are being affected by their mental health. Lastly, we\'ll cover how to make your workplace a safe place where mental health can be talked about and how to encourage your company to offer resources to help maintain everyone\'s mental health.||Watch Now|
|John Morehouse||Data Administration||Optimizing Query Performance In Azure SQL Database||Many think that moving to the cloud will not only help brighten your teeth but also solve all of your bad coding practices that give you poorly performing queries. If it's done correctly, implementing Azure SQL Database can help with one of those two and while it can mask things well, the best solution is to fix the bad code. In this hour-long session, we'll examine several different methods that you can utilize to help fix bad performance starting with the underlying service tier. Next, we'll investigate what options are available directly from the Azure portal to determine where the bottlenecks might reside along with possible ways to fix them. Lastly, we will interrogate which native SQL Server tools exist within Azure SQL Database that can really help solve any performance issues you might be having. You'll leave this session with a solid understanding of how to trouble shoot performance issues in Azure SQL Database and what you might be able to do to help fix them.|
#azuresql #azure #performancetuning #sql2019
|Ginger Grant||Business Intelligence & Advanced Analytics||Machine Learning with Spark and Azure Synapse||Azure Synapse Analytics contains a number of different features, and this session will focus on how to use the integrated Spark clusters to analyze data using Auto ML and other coding examples. See how you can use Azure Synapse to create data pipelines and do exploratory analysis without creating a SQL Pool. This session will provide real world examples showing you how you can use Azure Synapse to create solutions with your data and the demos will explain how to make it possible.|
Tags: #AzureSynapse #ApacheSpark #MachineLearning
|Marco Russo||Business Intelligence & Advanced Analytics||Inside The VertiPaq Engine||The VertiPaq engine used by SQL Server Analysis Services Tabular, Power BI, and Power Pivot, is a columnar database capable of incredible performances, both in speed and compression ratio. In this session, we will perform a deep dive in the internals of the database architecture, discovering how Vertipaq stores information, in order to gain better insights into the engine and understand the best way to model your data warehouse to leverage the features of VertiPaq. We will show common and useful techniques to increase the compression ratio and obtain better performances from your Tabular data model.||Watch Now|
|Marsha Pierce||Data Administration||Migrate Your Database Like A Rockstar||We often have to migrate databases between servers. It could be for a SQL Upgrade or it could be for a Hardware Upgrade. When you move servers there are a ton of things that can cause your move to fail. Learn from someone who has moved 1000s of instances. I will show you how to move your databases to a new server with just a few minutes of downtime and how to reduce the risk of needing to rollback. We will account for everything except an IP change including replication and not having to reseed it.||Watch Now|
|Julie Koesmarno & Alan Yu||Development||Azure Data Studio Notebooks Power Hour||Join this session to learn more about Notebooks in Azure Data Studio. We'll demo new features in notebooks in Azure Data Studio, through the different use case lenses. Learn how to author notebooks, convert + organize your scripts to more manageable and shareable notebooks, all the way to fun + productive tricks that you can try at home! DBAs, Data Engineers and all data professionals are welcomed.|
#AzureDataStudio, #Notebook, #AzureSQL, #ClientTooling
|John Q. Martin||Data Administration||SQL Server And Network Security||The network is often forgotten when securing SQL Server is completed. However, this is a primary attack vector which needs to be designed and configured properly to help add the layers of protection needed.|
In this session we will explore the network architecture you should look to implement as well as how to leverage Operating System Firewalls as well as Azure Network security configurations. When combined this will add more depth to the defence of your SQL Server security and help you meet compliance and regulatory requirements.
#Security #SQLServer #Azure
|Thomas Leblanc||Business Intelligence & Advanced Analytics||Building an Agile Data Warehouse||The Data Vault method can be used in agile development. If you follow 2.0 structure the hubs, links and satellites only have inserts. The difficult or more time consuming part is the Information Mart. This is where views for reporting can be used for reporting or converted into tables. The view code can be used, with some date manipulation, to schedule updates for structured dimensional model tables. The dimensional Data Mart is what most reporting or visualization tools (Power BI or Tableau) are programmed optimally.|
It still gives those power query writers (T-SQL experts) the ability to see the archival data in the Data Vault if they so desire. What really becomes apparent is the integration of new applications that replace the existing applications. Satellites are great at structuring the hard rules of the data to tables and relationships. Again, the Information Mart views or tables is where the soft rules will be applied to help reporting queries.
|Eva Pardi & Alan Smith||Data Science (AI/ML)||Reinforcement Learning in gaming||Microsoft uses reinforcement learning in many ways to improve our products and services. AI and machine learning can help accelerate game development by providing more realistic worlds and challenges as well as support automation and live operations.|
At Game Stack Live, Microsoft Research announced Project Paidia, a research effort aimed at exploring new opportunities created with AI based reinforcement learning in gaming. During this session, attendees will be able to get started with Reinforcement Learning for gaming with the use of Azure Machine Learning.
Tags: #AzureML #Microsoft #ReinforcementLearning #ProjectPaidia
|Mihail Mateev||Data Science (AI/ML)||Anomaly Detection, Powered By Azure AI And Digital Twins||Detecting the Onset of System Failure using Anomaly Detection Techniques is one of the key demands in Industry 4.0. Nowadays implementation of this functionality is often related to two concepts: Digital Twins and Anomaly Detection with AI|
Anomaly detection is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically, anomalous data can be connected to some kind of problem or rare event such as e.g. bank fraud, medical problems, structural defects, malfunctioning equipment etc.
Digital twins have been around for several decades, the rapid rise of the internet of things (IoT) is that they have become more widely considered as a tool of the future. Digital twins are getting attention because they also integrate things like artificial intelligence (AI) and machine learning (ML) to bring data, algorithms, and context together
In this presentation will be discussed various techniques that can be used to detect the onset of failure occurring in systems in the context of Microsoft Azure, using Azure Digital Twins Service and Azure Cognitive Service Anomaly Detector API.
Azure Digital Twins is a game-changer in the modern IoT and AI solutions. This a SaaS offering easy to build digital models of complex systems.
The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning. This feature adapts by automatically identifying and applying the best-fitting models to your data, regardless of industry, scenario, or data volume.
This talk is covering the whole content from Digital Twins and Anomaly Detection concepts via Azure based implementation demonstrating real use cases and demos.
#DigitalTwins #IoT #AI #AzureDigitalTwins #MicrosoftAzure #CognitiveServices #AnomalyDetector #Azure.
|Shikha Agrawal||Business Intelligence & Advanced Analytics||Harnessing Data With Synapse Analytics||Today organizations deal with a variety of data, both structured and unstructured. Azure Synapse has unique ability to provide a unified experience for data analysts looking forward to perform descriptive/predictive analysis on any Big Data/SQL Data Warehouse scenario. It adds layers of productivity by serving as single stop shop solution for building your data estate, starting with ingestion of data into data lake to executing ml training jobs on curated data or to create BI dashboards. Let us get a detailed description of how all this is facilitated in this session!|
#Data Analytics #Big Data #Azure Data Lake #Spark #SQL Data Warehouse
|Gary Pretty||Development||Developing sophisticated virtual assistants using the Microsoft Conversational AI Platform||Today, organizations are responding to increased demand from customers and employees looking for information and support. In this session, you will see how you can build your own Conversational AI applications using the Microsoft AI Platform - using Bot Framework Composer to rapidly create sophisticated and personalized conversational experiences which can be surfaced wherever your end users are, including Teams, WebChat, Alexa and more!|
#ConversationalAI #Azure #BotFramework #Microsoft
|Alex Whittles||Data Science (AI/ML)||Machine Learning In Power BI||Two of the hottest topics in data are Machine Learning and Power BI, but how to the work together? In this session we'll look at what ML tools and features are available in the Power BI world, and how you go about using these in your data and reports. This will include using both built in and 3rd party Power BI visuals, consuming Azure Cognitive Services, as well as the new ML features available in data flows.|
#PowerBI #ML #AI #CognitiveServices
|Monica Rathbun||Data Administration||Mastering Tempdb||Have you experienced performance problems caused by contention in TempDB? Have you ever wondered why your TempDB is suddenly 3 TB? In this session, you will learn about all the various components of SQL Server that use TempDB. Whether it be AlwaysOn Availability Groups, Read Committed Snapshot version stores, spills, or simply temporary tables, learn about how to identify what SQL Server or your applications are doing in TempDB. Once you understand all the ways SQL Server uses this critical resource, and how to proper configure it, you'll be better prepared for your workloads whether it be an Azure VM, a physical server, or a container.||Watch Now|
|Krishna Doss Mohan||Industry Solution||Challenges to Overcome while Building Machine Translation Models for Indian Languages||Microsoft Translator has shipped machine translation support for 10+ Indian languages. In this session, we will use Indian languages as example to cover why itâs important to build machine translation models for digitally low resourced languages and challenges you would face during data acquisition and building machine translation models.Â You will learn tips to overcome those challenges.Â We will demo how those machine translation models makes societal and business impact.|
#MachineTranslation #Azure #CognitiveServices #IndianLanguages #AI #ML #DataEngineering
|Neha Rajput||Data Science (AI/ML)||Inside QnA Maker||This session is to give an overview of Microsoft Cognitive Service: QnA Maker. You can create a conversational layer over your data with no/low code experience. QnA Maker can be used to create your own bot in minutes without writing a single line of code. It uses deep learnt models which understands the user query and returns the best possible answer for them.||Watch Now|
|Miguel Martinez & Peter Myers||Business Intelligence & Advanced Analytics||Monitor Your Data in Real-time with Microsoft Power BI||Why make decision based on data from yesterday when you can learn what is happening now? Wouldn't it be better to look forward instead of the rear-view mirror? Learn about the real-time data visualization capabilities for datasets, reports, and dashboards|
In this session you will learn:
How to create dashboards, reports, and visuals with data that's always up to date.
Different options for real-time datasets: streaming, push, et.
How to monitor critical events with automatic page refres.
#real-time #dataviz #streaming
|Sunitha Muthukrishna||Development||Build Modern Cloud Native Applications With Kubernetes And OSS Databases (MySQL & Postgres)||With changing customer requirements, you need to think about modernizing your approach to application development to be cloud-ready. In this session, we will show you how to modernize your application with Azure Kubernetes Service (AKS) and MySQL on Azure. We will walk through on how to migrate an application that uses PostgreSQL or MySQL to Kubernetes using AKS and Azure Database for MySQL. In additional to the migration, you will also learn how to optimize AKS to work best with Postgres or MySQL on Azure and to simplify migration and operational efficiency resulting in increased scalability, improved performance, and reduced costs.||Watch Now|
|Benjamin Kettner||Development||Cloud-Based ETL With Azure Data Factory And Azure Functions||Today, many ETL workloads and Data Warehouses move to the cloud. But also the data sources and requirements have changed. How can you process streaming data for a cloud-bourne DWH? How can you pull data from REST APIs in batches? What tools do you have for processing data in the cloud? In my session I will discuss scenarios that can be solved using the Azure Data Factory, scenarios that are beyond ADF capabilities and how Azure Functiosn can be employed in both scenarios. I will show real-life examples utilizing Storage queues for asynchronous processing, durable entities for streaming data and orchestrator functions.|
#ETL, #Azure, #ADF, #AzureFunctions, #ModernDWH, #DWH, #Cloud
|Vin Yu||Data Administration||What is Azure Arc Enabled Managed Instance?||Have you checked out Azure Arc yet? Azure Arc enabled Managed Instance enables you to run SQL Server compatible workloads with the added management capabilities anywhere. In this session, well bring you quickly up to speed on Azure Arc enabled Managed Instance, discuss use cases, and demo this product. Well also cover how you can get easily get started with this product.|
|Prashant G Bhoyar||Industry Solution||Applied AI Practical Use Case : Content Classification of Network drives||Most of the organizations have humongous file shares/network drives where the contents are not organized and labeled as per the organizations liking. This poses a high problem when organizations want to move the legacy contents in the public cloud. In this demo-driven talk, we will cover the case study of a recent file share migration project we did where we used Microsoft Cognitive Services (Applied AI) for intelligent content classification.||Watch Now|
|Reza Rad||Business Intelligence & Advanced Analytics||Power BI for Ticketing and Subscription: A design pattern review||This session explains one of the common design patterns for Power BI implementation. A design pattern that can be used for subscription or ticket systems. Through this session you will learn the structure of the data model, the data preparation steps to get there, DAX expressions to support analytics.|
This is not a beginner-level session, you should have some understanding of Power BI, Power Query, and DAX already.
Tags: #PowerBI, #PowerQuery, #DataModeling, #StarSchema, #DAX #Analytics
|Dejan Sarka||Data Science (AI/ML)||Text Mining With TSQL||Analyzing text is another modern hype. You have many tools, packages, and languages available. But did you know that you can do really a lot of text mining also in pure Transact-SQL? Yes, your SQL Server can also become a text mining engine. In this advanced session, you will learn how to analyze text in multiple languages with pure T-SQL, using also features from the full-text search (FTS).|
|Charley Hanania||Business Intelligence & Advanced Analytics||Querying best practices for Azure Synapse Analytics||Data warehousing is evolving into the Cloud so it's time to get on board. With Azure Synapse Analytics there are now more ways to transform, manage and present your data pipelines with scale and performance in mind. Recent experiences from clients on the platform have shown that if you just try to dump data into the platform and use it without understanding the underlying architecture and capabilities, you'll leave fairly quickly as you see your costs skyrocket and the benefits decline. Join this session to get an understanding of what options are available to reduce your query times and lower your costs while allowing more users to access the data that's been loaded into the platform. In this session we'll cover: 1. Introduction to Azure Synapse Analytics Components 2. Azure Synapse Analytics Architecture Overview (querying-focused) 3. Best Practices & Tips for Querying data from Azure Synapse Analytics|
Tags: #Azure #Synapse #Analytics #Loading #Polybase
|Joshua Higginbotham||Business Intelligence & Advanced Analytics||Functional Python for the ETL Developer||Python has been around for close to 2 decades now, with it\'s popularity and adoption growing larger each day.Â As Data Professionals moving towards a cloud approach, we will find Python as an offering in the majority of areas in the cloud environment.Â To be able to support this language, we can begin the adoption early on while still on-premises, replacing some of our traditional ETL\'s while increasing efficiency and accuracy of our existing solutions.|
In this session:
We will leverage commonly used packages across the open source community that lowers your cycle time from start to completion.Â Building out reusable and scalable functions that facilitate commonly used ETL processes across your estate.
Tags: #DataEngineering #Analytics #ETL #Python
|Jeremy Frye||Business Intelligence & Advanced Analytics||Power Apps and AI - A Flow of Location Events||The Microsoft Power Platform has become an innovative bridge between data interaction, visualization and analytics.Â The possibilities have become almost endless for businesses to engage with their data in amazing ways.|
In this session, I will show you an application using Power Apps and location services to track latitude and longitude coordinates on Bing maps.Â Attendees will learn how to configure and use the application on a mobile device. Â I will also show two approaches using AI within the application by using Azure SQL Database, Cognitive Services and Power Automate.
An end-user will be able to leverage Bing Search for location-aware web searches while an administrator will be able to leverage the Azure SQL Database and Power Automate to send alerts based on predefined metrics.
|Reid Havens||Business Intelligence & Advanced Analytics||Unlocking New Visualizations and Features in Power BI||Power BI is a great sandbox environment for report design. However, knowing how to leverage visuals and features in a way that adds additional value can be challenging. New visualizations and features can be created a number of ways including: layering visuals, customizing visual formatting, and/or utilizing DAX measures. The session will include a series of visualization and reporting techniques that you'll be able to leverage in your company's reports to take them to the next level.|
Tags: #PowerBI #Visualizations #Storytelling #CustomVisualizations #Reporting #KPI
|David Pless & Brian Carrig||Data Administration||SQL Server 2019: Building A Foundation With Persistent Memory||Data volumes have exploded. There is much more data at rest than ever before with only a small amount of the ingested data ever processed. Intel estimates that this is less than 1% of the volume ingested. Yet, we continue to produce data at record levels and systems can barely keep up to meet the demands.|
In this session we will cover some of the benefits of a hyper-converged infrastructure, Storage Spaces and Storage Spaces Direct in Windows Server 2019, the capabilities of Intel Optane DC Persistent Memory, and how SQL Server 2019 can build upon these technologies.
Intel Optane DC Persistent Memory is an innovative memory technology that delivers a combination of large capacity storage and support for data persistence. Persistent Memory can help with increased capacity needs and unique memory modes, lower the overall total cost of ownership while maximizing virtualization densities, and increase memory security with automatic hardware-level encryption.
Persistent Memory can be a powerful technology for larger systems such as SQL Server, SharePoint, and private cloud deployments.
We will cover how SQL Server can take advantage of Persistent Memory today and where the opportunities lie for all supported versions.
We will cover SQL Server data access performance (block access), persisted log buffer (tail-of-log caching), enlightened I/O (with Direct Access), and Hybrid Buffer Pool capabilities.
Finally we will address the scenarios where applications and platforms can best take advantage of hyperconvergence with persistent memory as a complete solution a foundation to build upon.
We look forward to seeing you there!
#PersistentMemory #SQLServer2019 #SQLServer #Virtualization #Hyperconvergence
|Lindsey Allen||Data Science (AI/ML)||Azure AI, Power new possibilities for every organization||AI and data is at the center of the digital feedback loops. The quintessential characteristic of every application going forward will have AI, we have invested in a comprehensive portfolio of AI tools, infrastructure and services. We are also pushing the bounds of how computers and AI can generalize learning beyond narrow domains. We work with our partners on our collective pursuit to democratize AI and its benefits for everyone. Come to this session to get an update of Azure AI with demos.||Watch Now|
|Paul Turley||Business Intelligence & Advanced Analytics||Paginated Reports: the New Old Operational Reporting Platform||Power BI Paginated Reports (aka SQL Server Reporting Services) was old but now it's new again. Available on-premises or in the Power BI service with flexible licensing, you have multiple options to implement operational reports. This session will briefly cover the differences between analytic and operational reports; and help you understand the advantages and trade-offs using Power BI Paginated Reports, Power BI Report Server and SQL Server Reporting Services. Material from our forthcoming book: Paginated Report Recipes.||Watch Now|
|Leila Etaati||Data Science (AI/ML)||AI Builder: AI in Power Apps and Power Automate||There are many ways to extend the AI capabilities inside Power Apps and Power Automate. In this session, you will see an overview of different capabilities with a brief demo on create an application to scan a business card and store back the result into Microsoft Outlook with help of AI builder and Power Automate.||Watch Now|
|Melissa Coates||Data Administration||What You Can Learn From The Power BI Activity Log And REST APIs||The Power BI Activity Log and the Power BI REST APIs are a goldmine of information for understanding usage patterns and activities in your Power BI environment. In this demo-packed session, we will look at examples of the type of data you can obtain and how this data can make a significant contribution to your Power BI governance, security, management, and adoption efforts.||Watch Now|
|Ben J Miller||Data Administration||SQL Server Encryption Unplugged||There are so many ways to encrypt data today, so you need to get your game on. From TDE, Always Encrypted, cell encryption and Backup encryption, there are some key pieces of information and methods that will help you get these all right. This session covers a lot of ground and will be over 60% demos. I will take you through each one of these and show you how it works. As an added bonus, we will hook TDE on premises up to Azure Key Vault too. We will also take you through rotation of the keys for TDE. Join me for a fast and furious demo packed session to get your data encrypted like a pro.|
|Will Velida||Development||Introducing Graph Databases With Azure Cosmos DB||Graph databases are an absolute game changer when it comes to storing our data! Data in the wild the more naturally connected than we might force it to be in a traditional relational database. However, you may not even know what a graph database is and how you can get started building one!|
In this session, I'll cover the basics of what graph databases are and how we can build a graph database in the cloud thanks to Azure Cosmos DB's Gremlin API. Then I'll discuss how we can model our graph data in Cosmos DB, how we can query our data that's stored in a graph database and how we might apply graph databases to a variety of different use cases.
By the end of this session, you'll leave with an understanding of what Graph databases are, what you can use graph databases for and how we can use Azure Cosmos DB to build a graph database.
#azure #cosmosdb #graphdb
|Stefano Tempesta||Data Science (AI/ML)||AI-Powered SharePoint Intranets||This session combines the agility of building pages and web parts in SharePoint Framework, with the power of the Microsoft AI platform. Specifically, I'll present a dashboard in SharePoint that displays Machine Learning-powered sentiment analysis of your intranet contributions; an automatic document and image classification with Cognitive Service, and a content filtering engine that learns from new entries and improves accuracy of detection over time.|
|Louis Davidson||Development||Matters Of Concurrency||OLTP databases can be constantly written to and reporting databases are written to at least periodically. In order to ensure consistent results, connections must be isolated from one another while executing, ideally with the lowest possible cost to concurrency. How this isolation is handled is based on the isolation level, whether the classic lock based or the newer optimistic scheme of the in-memory OLTP engine is used, or even if both engines are enlisted in the same transaction. In this session we will look at examples of how SQL Server isolates reading and writing operations from other writing operations to explore how this may affect your application through error messages and performance hits.|
Tags: #Concurrency #MemoryOptimizedTables #SQL Server 2019
|Ferenc Csonka||Business Intelligence & Advanced Analytics||XMLA Read-Write Endpoint: The Cornerstone For Power BI As An Enterprise BI Solution||Since the release of Power BI Premium in 2017, Microsoft has been continuously expanding the list of features that differentiate its solution running on a dedicated capacity from the shared capacity version. A game-changer step in this process is the release of the XMLA read-write endpoint, which makes Analysis Services Tabular models of Power BI reports deployed on Power BI Premium available for both reading and writing. This makes a myriad of applications and techniques previously developed for on-premises Analysis Services Tabular and Azure Analysis Services models available for developing and operating Power BI reports, taking Power BI Enterprise BI solutions to the next level. In this session, we present several practical use cases for XMLA read-write endpoint: migrating existing Analysis Services Tabular models to Power BI Service, significantly improved application lifecycle management for Power BI artifacts, debugging, monitoring and tracing functionalities for Power BI reports, much more sophisticated incremental refresh solutions, using such Analysis Services Tabular-specific features which are not available in Power BI, etc.|
Power BI Premium, XMLA, Analysis Services, monitoring, ALM, incremental refresh
|Argenis Fernandez||Data Administration||Advanced Storage Troubleshooting for SQL Server||In this session we will go over the tools and tricks used to track down nasty storage issues as they affect SQL Server databases on hypervisor plus storage array or hyper-converged configurations. We will go ver the different places in the stack where I/O could be stuck, queued, or just flat out slow.|
This is an advanced session and as such you can expect tons of bits and bytes being shown!
|Martin Cairney||Architecture||My Top 5 Omissions From Azure SQL Database Applications And How To Fix Them||As a consultant, I am often called upon to help troubleshoot Azure SQL Database applications. Most of these could have been addressed with better design and planning.|
Come along to this session and discover the common omissions from a robust Azure SQL Database implementation and how you can go about fixing these in your own environment before they bite you.
|Haniel Croitoru||Architecture||Manage Your Power Automate Governance Like A Rockstar||You've managed to get Power Automate introduced and even adopted within your organization, which is awesome. But are you sure that everyone is using it the way they should? Are you up at night wondering whether|
- Do my flow makers know the confined in which they can and should build flows?
- Are there flows that are beyond the rights and capabilities of my flow makers?
- Is any of my organizational business data being compromised?
- Do my flow makers able to leverage Power Automate for their business needs without negatively impacting themselves or their peers?
- Are my flow makers following organizational best practices recommended by my IT department?
- Is my IT department being taxed with additional support for flow makers beyond their means?
If you've answered yes to any of these questions, then you shouldn't miss this session, where I will introduce and demonstrate topics such as
- Data Loss Prevention in Power Automate
- Automating Power Automate onboarding and training for new flow makers
- Building a governance matrix to establish what flows should be owned by whom
- Leveraging the Power Apps Center of Excellence to audit and report on flow usage within your organization
- Create an audit trail of activities performed by users
- Creating organizational templates
|Andrew Brust||Business Intelligence & Advanced Analytics||AI And Analytics With Apache Spark And Azure Databricks||Open source technology Apache Spark is the analytics and machine learning platform of choice for many companies. While Spark has manifested in numerous parts of the Microsoft stack, including HDInsight, Synapse Analytics and even SQL Server 2019, Microsoft's go-to Spark service is Azure Databricks.|
The service, from Microsoft and Databricks (the company founded by Spark's creators), is a versatile one, geared towards data lake management, analytics, data engineering and data science. Azure Databricks lets developers work in notebooks, offline, interactively with running clusters, or scheduled as production jobs that provision Spark clusters on-demand.
This session will cover the concepts, service mechanics, and code necessary for you to do analytics and machine learning on Azure Databricks, and integrate it with other Microsoft cloud services and on-premises technologies.
You will learn:
About the fundamentals of Apache Spark, Spark SQL and Spark MLlib
How to use Databricks notebooks and manage clusters
The rigors of integrating Databricks with Azure Storage, Azure SQL Database and Power BI
How to write Python code for both analytics and machine learning
Cool new Databricks features, like Delta Lake, Delta Engine and MLflow
#ApacheSpark #Databricks #Azure #MachineLearning #AI #ML #DataEngineering #DeltaLake #MLflow
|Gilbert Quevauvilliers||Business Intelligence & Advanced Analytics||How I Reduced My Power BI Dataset By 60%||How to optimize Power BI Datasets to ensure that they can run as fast as possible with the smallest amount of memory possible.|
The session will cover the following topics:
Data Modelling with the Star Schema
Looking at columns in the dataset
Data Types and how this affects the size of your dataset
Using DAX Studio for analysis of datasets
Real world optimizations that I put into practice
|Torsten Strauss||Architecture||Microsoft SQL Server - In-Memory OLTP Design Principles||In this session we will look at the design principals of the in-memory OLTP engine. We will understand how the in-memory engine optimizes data storage for main memory, eliminates latches and locks, and uses native compilation to reduce the CPU overhead.|
For this we will compare the traditional on-disk engine with the in-memory engine to decide when it makes sense to use in-memory OLTP.
|Abhishek Narain||Architecture||Architecting enterprise-grade data pipelines with Azure Data Factory||Azure Data Factory is the modern data integration service (hybrid, server-less, cloud scale) that enables customers to build their ETL/ ELT pipelines for their Modern Data Warehouse (MDW) from Big Data. What truly makes Azure Data Factory an enterprise-ready ETL service is the in-built security features. In this talk we will learn all security fundamentals and best practices while building data pipelines in Azure Data Factory.|
|Anthony Nocentino||Architecture||Containers - What's Next?||You've been working with containers in development for a while, benefiting from the ease and speed of the deployments. Now it's time to extend your container-based data platform's capabilities for your production scenarios.|
In this session, we'll look at how to build custom containers, enabling you to craft a container image for your production system's needs. We'll also dive deeper into operationalizing your container-based data platform and learn how to provision advanced disk topologies, seed larger databases, implement resource control and understand performance concepts.
By the end of this session, you will learn what it takes to build containers and make them production ready for your environment.
|Alicia Moniz||Data Science (AI/ML)||Data Stewardship In An AI-Driven Ecosystem: InterpretML, FairLearn, WhiteNoise||At the core of Microsoft's AI are the principles of fairness, reliability & safety, privacy & security, inclusiveness, transparency & accountability. As AI capabilities increase along with adoption, it is important that we also leverage tools that enable us to practice AI responsibly.|
Responsible ML provides us with tools to ensure that as practitioners we
Understand machine learning models - Are we able to interpret and explain model behavior? Are we able to assess and mitigate model unfairness
Protect people and their data - Are we actively working to prevent data exposure with differential privacy?
Control the end-to-end machine learning process - Are we documenting the machine learning life cycle?
Announced at Build this year were multiple Responsible ML open source packages. The accessibility of these freely available tools enables every machine learning developer to consider incorporating Responsible ML into the development cycle of their AI projects.
InterpretML - An open source package that enables developers to understand their models behavior and the reasons behind individual predictions.
A python package that enables developers to assess and address fairness and observed unfairness within their models.
WhiteNoise - An open source library that enables developers to review and validate the differential privacy of their data set and analysis. Also included are components for data access allowing data consumers to dynamically inject 'noise' directly into their queries.
Datasheets for Models - A python SDK that enables developers to document assets within a model, enabling easier access to metadata about models
It is import that we design sustainable AI systems with ethics in mind. Join us for an overview and demo of these packages!
|Peter Myers||Business Intelligence & Advanced Analytics||Working With Different Power BI Data Model Architectures||Power BI provides you with different data model architectures. It's all controlled by setting the storage mode of model tables, as either Import, DirectQuery, or Dual. In this presentation, learn why and how to develop the model that best fits your data and circumstances. Also, learn how you can extend an existing Power BI data model with new data and calculations.||Watch Now|
|Warner Chaves||Architecture||Global Analytics with Azure Cosmos Db and Synapse Analytics||Cosmos Db is Azure's NoSQL Database as a Service, born in the cloud and designed to take advantage of the flexibility, elasticity and global reach of cloud computing.|
Synapse Analytics is Azures data analytics services that integrates on-demand SQL querying, Spark big data, Data Lake Store Gen2 as well as an integrated authoring experience.
Together these two services can be used to develop solutions in a simple and elegant way that would have been incredibly complex before. The most ambitious is the capability of doing Global Analytics, being able to do analytical queries over your live operational data coming from anywhere in the planet. All without having to handle one piece of infrastructure yourself.
In this demo-heavy session we will look at the C# code, features and configuration of Cosmos Db and Synapse and see the Global Analytics in action live.
#CosmosDB #NoSQL #Synapse #BigData #ADLS2 #Analytics
|Bob Ward||Data Administration||Inside Waits, Latches, and Spinlocks Returns||This session marks the return of a popular session dive into the internals of waits in SQL Server including latches and spinlocks. In this session, you will learn how SQL Server implements waits, how you can monitor and troubleshoot waits, and a deep dive into specific common wait types. This session will include new wait types specific to Azure SQL. The session will include plenty of demos and back by popular demand the use of the Windows Debugger to peek inside how waits are truly implemented in SQL Server.|
|Sasha Nosov||Architecture||Azure Arc Enabled SQL Server||Even if you cannot migrate or modify your SQL Server application, you can leverage Azure. Whether your existing SQL server instances deployed to your private infrstraucture, AWS or GCP, you can use Azure Arc to manage your global inventory, protect SQL Server instances with Azure Security Center or periodically assess and tune the health of your SQL Server configurations.|