Abstract: In this session, we will learn about the different options for SQL deployments in Azure. After this session, you should be able to understand the key differences between SQL Server On-Premises, SQL in an Azure VM (IaaS), and using Azure SQL DB (Single database, Elastic Pools, and Managed Instances.) In addition, we will evaluate different service tiers within Azure SQL DB to determine different workloads and business requirements. (Serverless, Hyperscale, General Purpose, and Business Critical.)

Speaker: John has been a Microsoft Certified Trainer (MCT) for over 20 years teaching Azure, SQL Server, Exchange Server, and Windows Server networking courses. He is currently a Data Customer Engineer for Microsoft. He is an MCT Regional Lead for the Eastern United States and a former Data Platform MVP.

When: Sep 14th – 6:PM EST

Microsoft Teams Link : https://teams.microsoft.com/dl/launcher/launcher.html?type=meetup-join&deeplinkId=e3ce3074-ff0c-44be-8ed0-4d7b59428d08&directDl=true&msLaunch=true&enableMobilePage=true&url=%2F_%23%2Fl%2Fmeetup-join%2F19%3Ameeting_Mzk1Nzg0NDMtNzE4OS00NmViLWFjZTQtYzVhYjI5MTAyMjZk@thread.v2%2F0%3Fcontext%3D%257b%2522Tid%2522%253a%252272f988bf-86f1-41af-91ab-2d7cd011db47%2522%252c%2522Oid%2522%253a%2522af70c7c4-b3b9-4396-9f98-804640f6bdb4%2522%257d%26anon%3Dtrue&suppressPrompt=true

Abstract: As Organizations are looking to transform into data driven organizations. Stream analytics has emerged as an integral part of Enterprise Data platform architectures along with batch ETL. Stream analytics help to gain maximum value from user-interaction events, applications and machine logs. Ingesting, processing, and analyzing these data streams quickly and efficiently is critical in fraud detection, click stream analysis, sentiment analytics, online recommendations and IOT Scenarios among many examples. In this session we will look at options available in azure for real-time analytics and deep dive into Azure Stream Analytics. Build streaming jobs that can blend and aggregate data as it arrives to drive live Power BI dashboards. Plus, we’ll explore how a complete lambda architecture can be created when combining stream and batch data together and finally how it integrates with Azure ML.

Speaker Bio: Sriharsh Adari is a technology strategist and Cloud BI Architect. He has around 16 years of experience helping customers with setting up Data Platforms focused on Microsoft BI. He has helped multiple global customers across different industry verticals set up enterprise data platforms using the Microsoft Data Platform and Business Intelligence stack. Over the past few years, he has been helping customers migrate on-premise data workloads onto Cloud Data Platforms – Azure, AWS, and set up new data platforms on cloud. Sriharsh is passionate about all things related to data, big data and Business Intelligence.

Abstract: Microsoft’s Synapse DB is based on a Massively Parallel Processing (MPP) architecture.  When your DB is designed right, all that compute and parallel workload can get answers to your queries fast.  Designed wrong and a lot of that MPP power is used compensating for our design mistakes.  This session will have an overview of the MPP architecture and how it influences design decisions around table types and storage type.  Then we will review some best coding practices for Synapse DB and see how for large Upserts a CTAS (create table as select) and partition switch is the way to go. Lastly, since despite our best efforts we will write some poor performing code, we will take a look at troubleshooting and tuning techniques and how they were used in some real world examples.

Speaker Bio: Ted Tasker is a Data Architect at Insight Digital Innovations.  Ted started working with SQL Server 4.21 in 1993 and has had a career centered on SQL Server ever since.  The release of SQL 7 / OLAP shifted Ted’s focus  to data warehousing and he led a team in deploying Disney Online’s first DW and OLAP reporting solution.  After years of leading DW and BI teams, Ted joined Microsoft and was the technical lead for the first sale in the world of Microsoft’s PDW (Parallel Data Warehouse).  He returned to consulting with a focus on Microsoft’s MPP database platforms and continued to work with PDW as it became APS, then Azure SQL DW and now the relational db platform for Azure Synapse.

Event Details:

Monday, April 13, 2020 – 6:00 PM to 7:00 PM EDT

https://www.meetup.com/Central-Ohio-Azure/events/blcjqrybcgbrb/?rv=ea2_v2&_xtd=gatlbWFpbF9jbGlja9oAJDI1MzBiNmNlLTJmOGQtNDI5My1iMGU5LTgwNTM3MDQ4NjJkMw