Jason Horner
Global Thought Leader and International Man of Leisure
Denver, Colorado, United States
Hi, my name is Jason I'm a Independent consultant and trainer focused on the Azure Data Platform. I spend most of my day helping clients solve business problems mostly in the Data and Advanced Analytics spaces. Sometimes this involves various and sundry cloud technologies including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Store, Azure Databricks, HDInsight and Azure SQL Database. I'm fluent in several languages including: SQL, C#, Python, and PowerShell.
I'm a Microsoft Certified Master of SQL Server (MCM) and have been recognized for my technical excellence and evangelism efforts by Microsoft by being previously awarded the Most Valuable Professional (MVP) for the 6 years.
I'd love to speak at your upcoming event or user group don't hesitate to email me or reach out on linkedIn or twitter.
In my off hours I like to snowboard, karaoke, ride roller coasters and play arcade games
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Area of Expertise
Topics
Turbocharge your DBA / Developer Productivity with Stream Deck
With more and more people working from home, you might be looking for ways to outfit your home office to maximize your productivity join me to see how a tool like Stream Deck can help improve your productivity by doing more in less time.
In this session, we are going to show you seven ways you can use Stream Deck in the workplace to help improve DBA and Developer productivity by automating common, repetitive tasks.
Synapse Serverless Pool Security Overview
In this session, we will look at the security model in synapse serverless pools. Along the way we will cover basic permissions, setting up users and logins, and techniques for securely accessing external data
Azure Synapse Analytics: Picking the Right Pool
Azure Synapse analytics has several different types of pools but how do you know which one to use? This session covers the main uses cases for each of the Azure Synapses Analytics Pools: Spark, Dedicated SQL, Serverless SQL and Data Explorer.
Along the way, we will review some example architectures and best practices for managing costs and environment configuration.
A Head First Dive into Azure Synapse Analytics Data Explorer Pools
Do you need to explore log or telemetry data at scale? Whether you need to ingest the data in a streaming fashion or use a more traditional batch mechanism, Azure Synapse Analytics Data Explorer Pools allows you to unlock data insights by using the powerful KQL "Kusto" query language. Along the way, we will explore the overall architecture for Data Explorer Pools, uncover the options for data ingestion, and look into the KQL Query language. At the end of this session, you will have a better understanding of the key scenarios and use cases that make sense to employ this technology.
Real World Production Data Pipelines with Azure Databricks
You’ve decided to build your first Azure Databricks solution, or perhaps you have already built out a proof of concept. Maybe you already have a significant background using spark on-premises and are looking to migrate. How can you ensure that the solution you deliver will be easy to evolve and maintain as well as efficient and secure? In this session we will look at many of the best practices for designing robust production data pipelines in Azure Databricks. Along the way, we'll cover operational areas like DevOps, alerting and monitoring, performance tuning, and managing costs.
Azure SQL Monitoring Fundamentals
Migrating you on-premises Database to Azure SQL DB was easy but now comes the hard part how do you setup monitoring and alerts? While there are many 3rd party options what comes standard with Azure, how can you be sure your azure SQL Database isn't under or over allocated, so that your costs are optimize d. How can you project what future costs maybe. What tools from your on-premises sql server toolkit will still work and what new capabilities exists. Join this session to ensure you are getting the most out of your Azure SQL database monitoring.
Real World Production Data Pipelines with Apache Spark
You’ve decided to build your first Apache Spark solution, or perhaps you have already built out a proof of concept. Maybe you already have a significant background using Spark on-premises and are looking to migrate to the cloud. How can you ensure that the solution you deliver will be easy to extensible, easy to maintain, and efficient and secure? In this session, we will look at many of the best practices for designing robust production data pipelines in the cloud using spark. Regardless of whether you are using Azure Synapse Analytics or Azure Databricks this session will help understand the use cases and best practices for working with Apache Spark. Along the way, we'll cover operational areas like DevOps, alerting and monitoring, performance tuning, and managing costs.
Join The Spark Side: Spark Sql
Want to get started with data transformation but feel left out because you don't know Python or Scala? This session is for you! We will learn how to author notebooks to perform basic transformation, cleansing, and data enrichment using the familiar SQL Language you already know from the relational world. Specific topics include: windowing functions and CTE's, interreacting with Delta lake tables and Basic DML and DDL Operations. Along the way we will cover the basics of notebooks, Hive Metastore integration, and using Spark SQL in the new SQL Analytics Preview.
Every day I'm shuffling: Improving query performance in Azure Synapse Analytics
They said the query performance would make you lose your mind. Instead, your query performance has suffered since moving to Azure Synapse Dedicated Pools. In this demo heavy session, we will cover the basics of effective MPP table design, including table distribution choices such as round-robin, hash, and replicated. We will also learn to how to interpret DSQL query plans and how to understand some common causes of underperforming queries in a MPP Environment including data movement, data skew and over partitioning.
Attend this session and make sure you and your Synapse Dedicated Pool queries have a good time.
Event Driven ETL With Synapse Pipelines
In this session, we will look at how to use synapse pipeline to orchestrate event driven data pipelines in Azure Synapse. Along the way we will cover basic flow control, metadata driven pipelines, and techniques for securely storing secrets in azure key vault.
The 7 Habits of Highly Effective Data Warehouses
Many Data Warehouses fail to live up to the business user's expectations. Data Warehouses can suffer from a variety of problems including distrust in the data, Taking too long to implement
slow performance, and lack of discoverability. In this session, we explore the seven habits that will help ensure that your data warehouse is used and loved by end-users.
Real-World Data Movement and Orchestration Patterns using Azure Data Factory
In this session, we will start with an overview of Azure Data Factory concepts, then show you how you can use metadata to quickly build scalable serverless pipelines to move data from disparate data sources including On-Premises and Platform As A Service. Next, we will look at how to integrate the solution using continuous integration and deployment techniques. Finally, we will look at how to schedule, monitor and log our solution.
Whether you are just getting started with Azure Data Factory or looking to make your current data factory robust and enterprise-ready this session will take you to the next level.
Real-World Azure Data Lake Design and Implementation patterns for success
A poorly designed data lake can be hinder adoption and cause limitless frustration to end users. Come join Jason and as he unlocks the secrets to a well-designed data lake.
ARM Yourself: A beginners guide to using ARM Templates
The cloud provides agility but if you are manually creating resources via the portal or even if you are using PowerShell you may not be taking advantage of the best way to deploy resources to Azure. ARM Templates take a declarative approach that is critical for implementing repeatable and automated deploys. Leveraging ARM templates can move you from a DevOps Dreamer to a DevOps Doer.
Azure Analytics Platform Quickstart
Are you struggling to get your analytics and data projects started on Azure? Overwhelmed by where to start or which services to choose? This hands-on session is for you. We will start with a brief overview of the Azure platform, followed by a complete guide through getting an environment set up. Along the way
, we'll answer your questions, talk about specific pitfalls and decisions, and ensure you are able to continue to build on your newly acquired knowledge.
Dimensional Modeling Design Patterns: Beyond Basics
This session will provide a deeper dive into the art of dimensional modeling. We will look at the different types of fact tables and dimension tables, how and when to use them. We will also some approaches to creating rich hierarchies that make reporting a snap. This session promises to be very interactive and engaging, bring your toughest Dimensional Modeling quandaries.notepad++
Jason On JSON
JSON is all around us in the systems we use every day. Many systems use it for configuration, data interchange and logging. SQL server 2016 introduced native support for JSON, but when should we use this new capability? and how can we ensure optimal performance? Join Microsoft Master of SQL Server Jason Horner as we look at the basics of JSON and how to query, transform, and store it. Whether you are working with a data warehouse or transactional processing system working with sql server on premises or in the cloud. This session will get you up to speed.
Data Lake Design Patterns
Data lakes have been around for several years and there is still much hype and hyperbole surrounding their use. This session covers the basic design patterns and architectural principles to make sure you are using the data lake and underlying technologies effectively. We will cover things like best practices for data ingestion and recommendations on file formats as well as designing effective zones and folder hierarchies to prevent the dreaded data swamp. We’ll also discuss how to consume and process data from a data lake. And we will cover the often overlooked areas of governance and security best practices. This session goes beyond corny puns and broken metaphors and provides real-world guidance from dozens of successful implementations in Azure.
Back the Truck Up: Data Loading Design Patterns for Azure Synapse Analytics
Azure Synapse Analytics recently released to much fanfare but just what makes this right platform for your data loading and processing? Is the whole greater than the sum of its parts? This session will cover a brief overview into the basic components and synapse architectural concepts. We then look at code-free ETL orchestration and how to work with the embedded spark engine directly. Along the way, we also cover some of the best practices around table design and data cleansing, enrichment and loading.
A Head First Dive Into Azure Synapse Sql Serverless Pools
Do you need to build a logical data warehouse, explore data, or perform large scale transformations on CSV JSON or Parquet stored in Azure Storage as part of your ETL / ELT process? This session is for you.
Serverless SQL pools are a new On-demand query service over the data in your data lake. It enables you to access your data through the existing tools and the robust T-SQL language you are using today. Since it is a scalable and elastic serverless, pay as you go service, it scales to meet your needs at a low cost.
Learn how to leverage the power of serverless pools to help solve your toughest data exploration and transformation challenges.
Intro to Azure Data Factory
In this session, we will start with an overview of Azure Data Factory concepts, then show you how you can use metadata to quickly build scalable serverless pipelines to move data from disparate data sources including On-Premises and Platform As A Service. Next, we will look at how to integrate the solution using continuous integration and deployment techniques. Finally, we will look at how to schedule, monitor and log our solution.
Whether you are just getting started with Azure Data Factory or looking to make your current data factory robust and enterprise-ready this session will take you to the next level.
Azure Synapse Analytics Deep Dive
Azure Synapse Analytics was released to much fanfare but just what makes this right platform for your enterprise data warehouse? Is the whole greater than the sum of its parts? This full day deep dive session will cover a brief overview into the basic components and synapse architectural concepts we then look at code-free ETL orchestration and how to work with the embedded spark engine directly. Along the way, we will also cover some of the key operational features such as workload management, advanced security, and networking. Finally we look at analytic capabilities possible with Power BI and Azure Machine Learning integrations that will enable you to have a true end to end modern data warehouse
Whether you are a Data Engineer, Data Scientist, or Database administrator This session is everything you to be able to build a modern data warehouse based on Azure Synapse Analytics.
Building Incremental Data Pipelines Using Azure Data Factory
One of the most common and challenging problems in Data Engineering is how to efficiently and accurately detect changed data. In the cloud, relying on a full load pattern can be both time consuming and costly. In this session we will look at some common design patterns for detecting and loading new and updated data using Azure Data Factory. Along the way we will also explore some common techniques to make pipelines more dynamic and add additional auditing and logging.
Azure Synapse Analytics Spark Pools @HybridVC
Ever wanted to get started with data transformation with Spark but feel left out because you don't know Python or Scala?
Azure Synapse Spark Pools allow you to process structured, semi-structured, and unstructured data with ease and we shall show you how!
Along the way, we will explore the overall architecture for Spark Pools, look at notebook organization, design best practices, and see how the Spark SQL Language can solve common ETL problems and integrate with Serverless pools.
By the end of this session, you will have another tool at your disposal to cleanse, transform and enrich data!
Azure Data Lake @ San-Francisco Data Platform
Data lakes have been around for several years and there is still much hype and hyperbole surrounding their use. Jason Horner will cover the basic design patterns and architectural principles to make sure you are using the data lake and underlying technologies effectively.
You will learn:
• Best practices for data ingestion
• Recommendations on file formats
• Designing effective zones and folder hierarchies
• How to consume and process data from a data lake
• Governance and security best practices
SQL & Azure SQL Conference Fall 2021 Sessionize Event
DataSaturdays #13 - Minnesota - Oct 16 2021 Sessionize Event
Azure SQL Monitoring Introduction @SQLIreland
Migrating you on-premises Database to Azure SQL DB was easy but now comes the hard part how do you setup monitoring and alerts? While there are many 3rd party options what comes standard with Azure:
- How can you be sure your azure SQL Database isn't under or over allocated, so that your costs are optimized.
- How can you project what future costs maybe.
- Using Azure Log Analytics to monitor databases
- What tools from your on-premises SQL server toolkit will still work and what new capabilities exists.
Join this session to ensure you are getting the most out of your Azure SQL
A Head First Dive Into Azure Synapse SQL Serverless Pools @ DenverSQL
Do you need to build a logical data warehouse, explore data, or perform large scale transformations on CSV JSON or Parquet stored in Azure Storage as part of your ETL / ELT process? This session is for you.
Serverless SQL pools are a new On-demand query service over the data in your data lake. It enables you to access your data through the existing tools and the robust T-SQL language you are using today. Since it is a scalable and elastic serverless, pay as you go service, it scales to meet your needs at a low cost.
Learn how to leverage the power of serverless pools to help solve your toughest data exploration and transformation challenges.
Azure Analytics Platform Quickstart @ Southlands PASS
Are you struggling to get your analytics and data projects started on Azure? Overwhelmed by where to start or which services to choose? This hands-on session is for you. We will start with a brief overview of the Azure platform, followed by a complete guide through getting an environment set up. Along the way
, we'll answer your questions, talk about specific pitfalls and decisions, and ensure you are able to continue to build on your newly acquired knowledge.
Into to ADF @ BostonBI
In this session, we will start with an overview of Azure Data Factory V2 concepts, then show you how you can use metadata to quickly build scalable server less pipelines to move data from disparate data sources including On-Premises and Platform As A Service. Next, we will look at how to integrate the solution using continuous integration and deployment techniques. Finally, we will look at how to schedule, monitor and log our solution.
Whether you are just getting started with Azure Data Factory or looking to make your current data factory robust and enterprise-ready this session will take you to the next level.
Intro to ADF @ Arizona Data Platform Users Group
In this session, we will start with an overview of Azure Data Factory concepts, then show you how you can use metadata to quickly build scalable serverless pipelines to move data from disparate data sources including On-Premises and Platform As A Service. Next, we will look at how to integrate the solution using continuous integration and deployment techniques. Finally, we will look at how to schedule, monitor and log our solution.
Whether you are just getting started with Azure Data Factory or looking to make your current data factory robust and enterprise-ready this session will take you to the next level.
The 7 Habits of Highly Effective Data Warehouses @ Sacramento SQL Server User Group
The 7 Habits of Highly Effective Data Warehouses - Jason Horner
Many data warehouses fail to live up to the business user's expectations. Data warehouses can suffer from a variety of problems including distrust in the data, taking too long to implement, slow performance, and lack of discoverability. In this session, we explore the seven habits that will help ensure that your data warehouse is used and loved by end-users.
Azure Analytics Quickstart @ PASS MN
Are you struggling to get your analytics and data projects started on Azure? Overwhelmed by where to start or which services to choose? This hands-on session is for you. We will start with a brief overview of the Azure platform, followed by a complete guide through getting an environment set up. Along the way, we'll answer your questions, talk about specific pitfalls and decisions, and ensure you are able to continue to build on your newly acquired knowledge.
SQLBITS 2020 - Azure Data Lake Design Patterns
presented talk on Azure Data Lake
Colorado Springs SQL User Group
presented Jason on JSON
SLC SQL Server Users Group - Azure Data Factory Overview
presenting an overview of Azure Data Factory
SLC SQL Server Users Group - Azure Analytics Quickstart
presented Azure Analytics quickstart session
Jason Horner
Global Thought Leader and International Man of Leisure
Denver, Colorado, United States
Links
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