As a leading Azure partner, we are pleased to invite you to our series of free online Azure Immersion Workshops in H1 2023.

The series focusses on four topics: AI, Modernise .NET Apps, Data & AI and Database Modernisation. Workshops offer a deep dive into the subject matter area (sessions are typically three hours or longer) and are hosted by senior subject matter experts, including our Chief Technology Officer. You’ll also participate interactively in corresponding hands-on labs.

These sessions are suitable for Foundational to Intermediate learners and we welcome professionals from multiple disciplines: business and technical decision makers, architects, developers, data engineers, data scientists and IT professionals.

AI | Thursday 26 January 2023 (10:00 - 13:30 GMT)

Level 200 | Intermediate

Whether you’re business or tech-focussed, Azure-driven AI is a real asset. Join us to cover best practices and scenarios, check out the latest demos, and get hands-on with Azure AI. We’ll also look at Machine Learning/Azure Synapse and AML, knowledge mining, cognitive services and chatbots.

• Data Migration overview

• Using Data Migration tools and frameworks

• Hands-on lab: Azure SQL Database Managed Instance

Modernise .NET Apps | Tuesday 14 February 2023 (10:00 - 14:30 GMT)

Level 100 | Foundational

Learn how to evaluate and prioritise your .NET applications, prepare them for migration, and host them on purpose-built Azure managed services such as App Service and SQL DB. We’ll show you how to map out your migration strategy and get hands-on with .NET App modernisation.

• Introduction to application modernisation on Azure

• Design session

• Hands-on lab: .NET App modernisation

Register here

Database Modernisation | Wednesday 15 February 2023 (10:00 GMT)

Level 200 | Intermediate

Join us in Manchester, UK, to elevate your skills at a free Microsoft Azure Immersion Workshop: Database Modernisation. During this immersive, guided, and collaborative lab experience, you’ll explore best practices for migrating and modernising applications and databases to Azure and for utilising Azure Arc, Azure SQL, and open-source databases on Azure.

You’ll also see how to modernise cloud environments with analytics using Azure Database for MySQL and PostgreSQL.

• Hands-on lab: .NET App modernisation

• Not sure if this workshop is right for you? To better understand the technical depth of the content that will be presented, check out this sample lab.

After completing this workshop, you will be able to:

• Identify the benefits and best practices for applying fully managed cloud database services to your business.

• Extend your knowledge and accelerate progress in your journey to the cloud.

• Put your new skills to work to make an impact in this deep dive into migration and modernisation

Address:Microsoft UA92 CampusTalbot Road, Trafford,Manchester, England, United KingdomM16 OPU

Register here

Data & AI | Friday 17 February 2023 (10:00 - 13:30 GMT)

Level 200 | Intermediate

Whether you’re business - or tech-focussed, Azure-driven AI is a real asset. Join us to cover best practices and scenarios, check out the latest demos, and get hands-on with Azure AI. We’ll also look at Machine Learning/Azure Synapse and AML, knowledge mining, cognitive services and chatbots.

• Data Migration overview

• Using Data Migration tools and frameworks

• Hands-on lab: Azure SQL Database Managed Instance

Fully booked

Database Modernisation | Friday 24 February 2023 (10:00 - 14:30 GMT)

Level 200 | Intermediate

Join us to explore the value and process of migrating apps and databases to Azure. We’ll be using SQL Database, SQL Infrastructure-as-a-Service (IaaS), and other Azure data modernisation services and techniques.

• Data migration overview

• Use advanced data-migration tools and frameworks

• Hands-on lab: Azure SQL Database Managed Instance

Register here

A Proof of Concept (PoC) is a high-value component of software development projects.

It’s a time-bound, fixed-scope exercise that tests the feasibility of a technical concept using measurable goals and success metrics. PoCs act both as a way for organisations to discover and learn about new technologies, and a way for organisations to manage the risks associated with exploring new technologies. However, as with any project, PoCs entail inherent limitations and pitfalls that can create cost, time and resource implications. Here’s my top 3.

1. Lack of business readiness.

One of the main pitfalls with a PoC is the inability of the broader business to adapt to the new capability it demonstrates. In practical terms, this can mean that a level of business transformation is often required beyond the original scope of a PoC, to adopt to a new technical system or process. It may be as simple as individual employees changing their workflows, or as complex as reconfiguring multiple business units. This can lead to a sort of ‘false positive’ from a successful PoC: the concept may be technically feasible, but broader adoption may present obstacles.

It’s vital to consider business process change when implementing a PoC into production, and is a crucial consideration in how an MVP (Minimal Viable Product) should be scoped.

2. Defining the wrong success metrics.

Technology is just a tool. Selecting the right tool for the right job is dependent upon having identified the right job to begin with.

Creating a PoC to answer a broad technical question - rather than applying technology to identify a specific business question - is a common pitfall. Consider the statement:

“Let’s see if we can use Machine Learning in Azure to help our business”

This is a difficult thing for a PoC to prove as it has no clear outcome, and it pre-supposes that Machine Learning is the right tool to solve this undefined need. Instead, we could add clarity to our goal by reframing:

“Let’s see if we can use Azure Data Services to help reduce time spent producing financial reports.”

This is a good starting point, and we can quickly refine the key technologies that need to be proved and simple ways of measuring the factors that define success. Good problem statements for PoCs are as specific as possible, often dealing with the viability of very low-level technical challenges such as integrations or data migrations with very narrow success criteria.

3. Building a PoC for production.

It is common wisdom that a PoC should not be put into production. Although this is almost completely true, it is an often-misunderstood statement. A PoC is immediately compromised if it is built to be productionised. This is because the additional considerations and work entailed in creating a production-grade solution adds significant overhead without knowing if the solution is even feasible, often increasing costs and risk against an uncertain outcome. However, if a PoC is deemed a success, that does not mean all the work undertaken needs to be thrown away by default. It means it can be objectively evaluated, and any viable component parts can be reused and carried forward into a follow-on project to build a production-ready MVP.

Moving to a production-grade solution means a much greater focus on code quality, reusability, security, testing and NFRs (non-functional requirements) among other things. Whilst all imperative in production systems, these will often add little value to the goals of a PoC. However, it is always wise during development to adhere to best practices to maximise the potential for possible expansion and refactoring, preventing the solution from becoming entirely disposable.

A good PoC will be rooted in a business value-based outcome and undertaken to prove that the proposed capability through a new application of technology or data is not only realistic, but the proposed approach is also feasible.