Welcome to this Microsoft solutions workshop on SQL Server in on-premises, in-cloud and hybrid solutions. In this one-day workshop, you'll learn how SQL Server 2019 and Azure SQL help you solve real-world challenges.
The Modules in this workshop lead you through conceptual and hands-on topics ranging from the newest technical features in SQL Server to its implementation in all the platforms it runs on. You'll learn not only specific technologies, but how to assemble them into a complete solution based on customer needs and requests.
You'll start by learning about the latest improvements in SQL Server 2019, work with the Big Data Clusters configuration, and then learn about the ways you can leverage SQL in Microsoft Azure (and how to get there) - all with a focus on how to extrapolate what you have learned to create other solutions for your organization. You'll end the day with a "What to Use When" module explaining how to create your own solutions.
This Workshop contains lecture and hands on lab work, and is particularly useful for Solution Architects, Data Architects, Application Architects, Technical Sellers, and Application Developers. A laptop, Microsoft Azure account, and experience with SQL is considered a prerequisite.
This README.MD file explains how the workshop is laid out, what you will learn, and the technologies you will use in this solution.
(You can view all of the source files for this workshop on this GitHub site, along with other workshops as well. Open this link in a new tab to find out more.)
In this day-long, hands-on Workshop you’ll learn how to:
- Articulate the key differentiators between SQL Server on-prem, in Azure VM, in Azure SQL, and hybrid configurations
- Explain the different service tiers within Azure SQL, and what to choose when
- Understand how Azure SQL is secured and address security concerns
- Explain hybrid configurations for Azure SQL and SQL Server in common examples
- Experiment with various features of SQL Server and Azure SQL
- Understand additional Azure platform features for data pipelines and security
- Understand what services are available to migrate and modernize your entire SQL Server stack
- Make informed decisions about how your business or customers should modernize their data estate
- Use Big Data solutions
The concepts and skills taught in this workshop form the starting points for:
- Solution Architects and Developers, to understand how to put together an end to end solution.
- Data Professionals and DevOps teams, to implement and operate SQL Server systems on premises and in the cloud.
- Data Scientists, to understand the environment used to analyze and solve specific predictive problems.
Businesses require near real-time insights from ever-larger sets of data from a variety of sources. Many have not explored the improvements made in the latest versions of SQL Server, and some are only now exploring the cloud as a computing platform. As time has progressed, a more dramatic upgrade process may be required.
In addition to traditional Online Transaction Processing (OLTP) and Online Analytic Processing (OLAP) workloads, some industry examples of data processing from multiple sources of data at scale are:
Industry | Example |
---|---|
Retail | Demand Prediction Market-Basket Analysis |
Finance | Fraud detection customer segmentation |
Healthcare | Fiscal control analytics Disease Prevention prediction and classification Clinical Trials optimization |
Public Sector | Revenue prediction Education effectiveness analysis |
Manufacturing | Predictive Maintenance Anomaly Detection |
Agriculture | Food Safety analysis Crop forecasting |
The information covered in this workshop includes the following technologies and topics - although you are not limited to these, they form the basis of the workshop. At the end of the workshop you will learn how to extrapolate these components into other solutions. You will cover these at an overview level, with references to much deeper training provided.
Technology/Concept | Description |
---|---|
SQL Server 2019 improvements (on-prem and in-cloud) | Covers challenges and solutions in performance, security, availability, data virtualization, and Linux and containers in SQL Server 2019 spanning on-premise, containers, Kubernetes, and cloud platforms. |
Big Data Clusters for SQL Server (on-prem and in-cloud) | Explains the architecture for Big Data Clusters for SQL Server in on-premises installations, containers, Kubernetes, and on the Microsoft Azure platform and in hybrid configurations |
SQL Server Virtual Machines in Microsoft Azure | Covers the tools, processes and procedures for SQL Server Virtual Machines on the Microsoft Azure platform |
Azure SQL | Covers the tools, processes and procedures for Azure SQL (Managed Instance, Single Database, and Elastic Pool) |
Migrating SQL Server installations to Microsoft Azure | Explains the tools and processes to migrate on-premises SQL Server installations to the Microsoft Azure platform |
"What to Use When" | Teaches a complete set of tools and processes used to determine the best architecture for a given customer scenario on the Microsoft Azure platform |
You'll need a local system or Virtual Machine that you are able to install software on. The workshop demonstrations use Microsoft Windows as an operating system and all examples use Windows for the workshop. Optionally, you can use a Microsoft Azure Virtual Machine (VM) to install the software on and work with the solution.
You must have a Microsoft Azure account with the ability to create assets, specifically the Azure Kubernetes Service (AKS).
This workshop expects that you understand data structures and working with SQL Server and computer networks. This workshop does not expect you to have any prior data science knowledge, but a basic knowledge of statistics and data science is helpful in the Data Science sections. Knowledge of SQL Server, Azure Data and AI services, Python, and Jupyter Notebooks is helpful for the Big Data Clusters feature. AI techniques are implemented in Python packages. Solution templates are implemented using Azure services, development tools, and SDKs. You should have experience working with the Microsoft Azure Platform.
If you are new to these, here are a few references you can complete prior to class:
A full prerequisites document is located here. These instructions should be completed before the workshop starts, since you will not have time to cover these in class. Remember to "Stop" any Virtual Machines from the Azure Portal when not taking the class so that you do incur charges (shutting down the machine in the VM itself is not sufficient).
The following roles will find this workshop useful. Others may also attend, as described in the Secondary Audience section.
Primary Audience: | Solution Architects and Data Professionals tasked with implementing modern Data Systems, Big Data, Machine Learning and AI solutions |
Secondary Audience: | Security Architects, Developers, and Data Scientists |
Level: | 300 |
Type: | In-Person or Self-Paced |
Length: | 8-9 hours |
This is a modular workshop, and in each section, you'll learn concepts, technologies and processes to help you complete the solution. The times shown below are for an instructor-led course, you may also take the modules in a self-paced fashion.
Module | Time | Topics |
01 - Introduction and Workshop Methodology | 9:00AM-9:15AM | Workshop introduction, logistics, setup check |
02 - Modernizing Your Data Estate with SQL Server 2019 | 9:15AM-11:15AM | This module covers challenges and solutions using the latest version of SQL Server including:
|
03 - Working with Big Data and Data Science (Big Data Clusters for SQL Server 2019) | 11:30AM-12:30PM | Abstraction levels, frameworks, architectures and components within SQL Server big data clusters |
04 - SQL Server on the Microsoft Azure Platform | 1:30PM-2:30PM | Covers the multiple ways to use SQL Server technologies on the Microsoft Azure Platform, along with the fundamentals of SQL in Azure with additional deeper resources provided. Topics covered include:
|
05 - Migrating SQL Server to Azure | 2:45PM-3:45PM | Covers the migration workflow and tools for assessing, planning, and migrating SQL workloads to Azure that meets the business requirements. Some of the tools and topics (not exhaustive) covered are:
|
06 - What to use When | 3:45PM-5:00PM | Covers the decision process and provides tools for deciding on the proper technologies on-premises and in-cloud for a solution based on requirements and constraints. |
Next, Continue to Prerequisites