Welcome to this Microsoft solutions workshop on creating a modern data estate using SQL Server in on-premises, in-cloud and hybrid solutions. In this one-day workshop, you'll learn how to use the latest improvements in SQL Server 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 auditing your current data estate and how to evaluate any gaps, moving on to understanding the latest improvements in SQL Server, 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 data estate architecture.
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.
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This README.MD file explains how the workshop is laid out, what you will learn, and the technologies you will use in this solution.
In this day-long, hands-on Workshop you’ll learn how to:
- Evaluate your current data estate and identify any gaps you have for leveraging data to make intelligent decisions
- Articulate the key differentiators between SQL Server on-prem, in an Azure Virtual Machine, in Azure SQL Managed Instance, Azure SQL offerings, 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 new 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
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. Business and Organizations may not be aware of the security, performance, reliability and programming capabilities in the latest version of SQL Server and the improvements in Microsoft Azure, and need to know how to evaluate those improvements to see if they warrant a change in their data estate.
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 |
|---|---|
| Data Architectures | Evaluating and configuring data architectures to match an organization's application needs |
| SQL Server | Services, Files, maintenance, tuning, recovery and programming the Microsoft SQL Server platform |
| Microsoft Azure | Services, control and use, authentication and access to the Microsoft Azure Platform |
| Hybrid Data Systems | Processe and procedures for connecting data systems from on-prem to Cloud Computing serivces, and visa-versa |
| Upgrading and Migrating SQL Server | Processes and procedures for planning and implementing a migration to a new version or platform for SQL Server, accounting for application transition and fallback strategies |
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 a Microsoft Azure SQL Database.
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 but not required. AI techniques are implemented in R and 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, Data Virtualization, 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 | Topics |
| 01 - Setup and Workshop Methodology | Workshop introduction, logistics, setup checks |
| 02 - Auditing your Data Estate Architecture | This module shows the processes and tools you can use to audit your current data estate and how to identify gaps for leveraging data to make intelligent decisions |
| 03 - SQL Server Improvements | Explains the improvements in SQL Server's manageability, availability, performance, security and more. |
| 04 - Improvements in SQL on the Microsoft Azure Platform | Covers the improvements in SQL Server technologies on the Microsoft Azure Platform, along with the fundamentals of SQL in Azure with additional deeper resources provided. |
| 05 - Extending SQL Server to Azure | Details the methods of connecting your on-premises data systems to cloud platforms such as Microsoft Azure and Amazon's AWS, migration workflows and tools for assessing, planning, and connecting and/or migrating SQL workloads to Azure that meets the business requirements. |
Next, Continue to Prerequisites