What DevOps Look Like in Microsoft Fabric

~ Hamish Watson ~ Leave a comment

Microsoft Fabric (not to be confused with the more general term “fabric” in DevOps) is an integrated data and analytics platform designed for modern data-driven workloads, such as data engineering, business intelligence, and machine learning. With the introduction of Git integration in Microsoft Fabric, DevOps practices are becoming more accessible in the platform, allowing teams to implement collaborative, automated workflows that are common in DevOps environments.

Here’s what DevOps might look like when applied to Microsoft Fabric:

  1. Version Control with Git: With Git integration in Fabric, data teams can now manage their code, data pipelines, notebooks, and models in a version-controlled environment. Just like developers use Git for code, data professionals can track changes to their work, collaborate with others, and ensure that different versions of their projects are clearly documented.

    Example: A data engineer might develop a complex data pipeline in Fabric. With Git, they can version control their scripts, track changes, and collaborate with other team members to improve and enhance the pipeline.

  2. CI/CD for Data Pipelines: In a traditional DevOps environment, CI/CD is used to automate code deployment. In the case of Microsoft Fabric, CI/CD can now be applied to data pipelines as well. Changes to data pipelines, analytics reports, or machine learning models can be tested and deployed automatically, ensuring that updates are released reliably.

    Example: When a change is made to a data transformation script, the change is automatically tested in a development environment through a CI pipeline. After passing tests, the change is automatically deployed to production, ensuring that data updates or changes are delivered seamlessly.

  3. Infrastructure as Code (IaC): Just as DevOps practices encourage automating the provisioning of infrastructure in cloud environments (such as AWS, Azure, or Google Cloud), the same principles can be applied to managing data infrastructure in Fabric. This means provisioning resources such as storage accounts, compute clusters, and data pipelines using code instead of manual intervention.

    Example: A team can define their data infrastructure as code, using tools like Azure Resource Manager (ARM) templates or Terraform, to automatically provision the resources needed for Fabric to run. This ensures that infrastructure is consistent, repeatable, and scalable.

  4. Monitoring and Observability: In a DevOps setup, monitoring application performance in real time is critical. In Fabric, data engineers and operations teams can leverage built-in monitoring tools to track the health and performance of data pipelines, machine learning models, and analytics processes. This enables proactive issue resolution and continuous optimisation of the system.

    Example: By integrating monitoring tools with Fabric, teams can track metrics like pipeline execution times, resource usage, and data quality. If a pipeline fails, they get immediate alerts to investigate and fix the issue.

  5. Collaborative Workflow: DevOps encourages teams to collaborate and share feedback early and often. With Git integration, teams working in Fabric can collaborate on code, data, and workflows. Data scientists, data engineers, and analysts can seamlessly share their work and iterate on solutions together, ensuring that the entire team is aligned and that new features or fixes can be rolled out quickly.

    Example: A data scientist might develop a new predictive model in Fabric. Using Git, they can collaborate with data engineers to test the model in real-world environments, refine it, and deploy it as part of a data pipeline, all while working in parallel with the development team.


Extended Reading

In a traditional DevOps environment, you see a strong focus on the integration of development and operations through automation, continuous delivery, and collaboration. With the addition of Git integration in Microsoft Fabric, these practices are now applicable to data-driven projects as well. DevOps in Fabric will enable teams to work more collaboratively, automate data workflows, and manage the lifecycle of data projects just like software development. By merging DevOps principles with the lifecycle management tools that Fabric provides, organisations can deliver better software and data solutions faster and more efficiently, while also ensuring that their infrastructure and workflows remain scalable and maintainable.inks that

Deployment Pipelines in Fabric – What Are They?

~ Hamish Watson ~ Leave a comment

In the realm of software development and content creation, the deployment pipeline serves as a crucial bridge between innovation and implementation. Whether you are fine-tuning code, testing new features, or releasing a polished product to end-users, the deployment pipeline guides your content through distinct stages, each playing a vital role in ensuring a smooth and efficient journey from development to production.

The Structure of Pipelines

Here’s how the stages of a Microsoft Fabric deployment pipeline typically work:

1. Development Stage: The journey begins here. Developers and creators upload fresh content, tweak designs, and build the foundations of their projects. This stage serves as the birthplace of ideas, where the initial spark of innovation ignites the development process.

2. Test Stage: Once the development work is complete, the content moves to the test stage for scrutiny and refinement. Testers and reviewers come into play, ensuring that the content meets quality standards and functions as intended. It’s here that load tests, user experience trials, and final checks take place to iron out any creases before the big reveal.

3. Production Stage: The ultimate destination of the deployment pipeline, the production stage heralds the grand unveiling of your content to the wider audience. Here, the final version is shared with business users, marking the culmination of the creative journey and the beginning of a new phase in the content’s lifecycle.

Item Pairing

Pairing is basically Fabric’s way of keeping things in sync across your deployment stages. Think of it like matching socks: one sock in the dev stage pairs with its twin in the test stage. That “twin” could be a report, a dashboard, or a semantic model. Pairing happens when you assign a workspace to a deployment stage, or when you deploy new content that hasn’t been paired yet (what Fabric calls a clean deploy).

Why care about pairing? Because it determines what gets copied, what gets overwritten, and, sometimes, what causes a deployment to throw a tantrum. Here’s the tricky part: just because two items have the same name, type, and folder, doesn’t mean they’re paired. If they aren’t, a deployment won’t overwrite the old item. Instead, Fabric creates a new copy and pairs it with the item in the previous stage.

Paired items show up neatly on the same line in your pipeline content list. Unpaired items? They get their own lonely line. And here’s a fun twist: once items are paired, they stay paired—even if you rename them. But any new items you add after assigning a workspace to a pipeline won’t automatically pair, so you could end up with identical items in adjacent workspaces that aren’t actually linked.

Deployment Methods

Deployment pipelines are where the magic happens. They give content creators a “production playground” where teams can collaborate, manage, and promote organisational content through its lifecycle.

Think of a pipeline as a series of stages. You get to decide how many—anywhere from two to ten, with three being the default, each stage representing a checkpoint of development, test, and production. When you deploy, Fabric copies the selected content from the source stage to the target stage, following the aforementioned pairing rules. Fabric keeps the folder hierarchy intact in the target stage, which allows you to pick items only from the same folder level, and cherry-pick items across folders, no matter where they live in your workspace.

When deployment happens, paired items in the target stage get overwritten, while items with no match stay untouched. This ensures updates land exactly where they should, without breaking anything else.

Extended Reading

If you’re ready to get hands-on and see exactly how to set up deployment pipelines, pair items, and move content across stages in Microsoft Fabric, Microsoft has some great step-by-step guides. Check out these resources for all the details:

Get started with deployment pipelines

The deployment pipelines process

Compare content in different deployment stages

Deploy content using Deployment pipelines

Automate your deployment pipeline with Fabric APIs

What is ALM in Fabric?

~ Hamish Watson ~ Leave a comment

As someone who’s worked with data for over 20 years and with many cloud platforms, my main focus has always been on helping teams streamline their development process. A key area of my expertise is mentoring engineers to adopt DevOps principles to optimise workflows, automate infrastructure provisioning, and deliver value to clients more efficiently. With Microsoft Fabric’s Git integration, this opens up a powerful chapter for teams looking to enhance their DevOps capabilities. But it’s not just about adding Git; it’s about leveraging Microsoft Fabric’s lifecycle management tools to bring real, measurable improvements in how we deliver software.

Lifecycle Management in Microsoft Fabric

One of the standout features in Microsoft Fabric is its comprehensive lifecycle management tools. These tools provide a standardised approach for communication and collaboration across all members of a development team. This is crucial because it ensures that everyone, from developers to operations teams, is on the same page throughout the lifecycle of a product. Effective lifecycle management accelerates the process of getting new features and bug fixes into production, creating an ongoing flow of improvements without bottlenecks.

The beauty of lifecycle management in Fabric lies in its two key components: Git Integration and Deployment Pipelines. By integrating Fabric’s Git-based workspace updates, your teams can automate the build, test, and release pipelines to ensure that your development cycles are faster, more reliable, and less prone to human error. This makes it easier to deliver new content to production quickly, whether it’s a bug fix, a security patch, or a shiny new feature that adds value to the end users. Git integration plays a central role here, allowing seamless version control and collaboration, enabling developers to work on different features concurrently without stepping on each other’s toes.


DevOps in Fabric: The Missing Piece

Now that Microsoft Fabric has Git integration, we can start applying true DevOps principles within the platform. DevOps isn’t just about automating processes—it’s about fostering collaboration, improving communication, and breaking down silos. As I work with teams, one of the first things I do is help them understand how automation and lifecycle management can be paired with DevOps practices to create a more efficient and cohesive workflow.

Mentoring engineers is one of the most rewarding aspects of my role. I work closely with teams to automate secure code builds and the infrastructure that provisions those builds. This enables development teams to focus more on coding and less on worrying about the underlying infrastructure. In a Microsoft Fabric environment, this could mean automating the deployment of entire data pipelines or deploying updates to dashboards and reports with minimal manual intervention. By streamlining these processes, development teams can release new features or updates much more quickly, which is a key tenet of both DevOps and successful software development in general.

Helping Clients Realise Value

Ultimately, the goal of applying DevOps principles to cloud platforms like Microsoft Fabric is to help my clients deliver more value to their customers. Through optimising tooling, refining delivery processes, and looking for better ways for teams to work together, I help businesses improve not just their speed of delivery but also the quality of the product. Whether it’s reducing the risk of deployment failures or ensuring that the infrastructure is cost-effective and scalable, the right approach to lifecycle management in Fabric can make all the difference.

In short, with Git integration now a part of Microsoft Fabric, it’s easier than ever to put DevOps practices into action. By leveraging the platform’s lifecycle management tools and automating infrastructure provisioning, we can help our clients unlock the full potential of Fabric, delivering better software faster and with more confidence. That’s what excites me about the future of DevOps in this space, and it’s what I’m looking forward to helping my clients achieve in the months and years ahead. 

Extended Reading

DevOps in Microsoft Fabric isn’t just about turning on Git—it’s about understanding how lifecycle management, pairing, and deployment pipelines work together. Here are some articles if you want to see exactly how to configure these features to put your ideas into reality.

What is application lifecycle management in Microsoft Fabric?

Application lifecycle management in Fabric

Get started with Git integration

The Most Successful Startups in 2025 — And What They Have in Common

~ Hamish Watson ~ Leave a comment

2025 belongs to the AI startups. If you peek into the tech headlines, you’ll see companies like OpenAI, Anthropic, Gemini, Lovable, and Poolside AI dominating the conversation. Different names, different cities, different vibes, but somehow they all seem to be drinking from the same startup magic potion.

They Solve High-Impact Problems

All these startups targeted areas with huge potential value. Some focus on general intelligence, others on AI safety, some on unlocking insights from massive datasets, and others on providing high-quality training data. What unites them is that the problems they solve are not only technically interesting but also commercially and socially significant. When the problem matters, the world takes notice.

They Build Strong Data Foundations

AI is nothing without data. The best startups treat data as a core asset from day one. They collect, clean, and structure it strategically so that every model has quality inputs. Without this foundation, even the smartest algorithm is like a car without fuel: it won’t go far.

They Iterate Fast and Fearlessly

Success in AI rarely comes from a single leap. It comes from relentless experimentation. These startups prototype quickly, test aggressively, and learn faster than anyone else. Failures aren’t setbacks; they’re data points that guide smarter iterations. Speed plus learning beats perfection every time.

They Align Vision With Trust and Ethics

AI moves fast, and so do the risks. Leading startups don’t just chase performance; they consider safety, fairness, and transparency. By embedding ethics into their operations, they gain credibility, user trust, and long-term resilience, as adoption depends on more than just clever algorithms.

Conclusion

If you look closely, the magic potion isn’t magic at all. It’s a disciplined mix of solving important problems, attracting top talent, building strong data systems, iterating relentlessly, and prioritising ethical impact. Startups that embrace these patterns dominate. And that’s the real recipe for AI success in 2025.

Yip.

Upcoming speaking events in May (Australia)

~ Hamish Watson ~ Leave a comment

Are you looking to boost your skills and knowledge in Database DevOps, learn how to transition to the cloud, and work across multiple databases?

Join me and fellow speakers/experts at three different locations across Australia (Brisbane, Sydney and Melbourne)to find out how your business can tackle the complex challenges of database management throughout the entire DevOps lifecycle, no matter what database you’re using or where it’s located. Hear from industry experts as we share our experiences on boosting efficiency, reducing errors, and protecting business-critical data.

This event is designed for database professionals who want to stay ahead in the fast-paced world of DevOps. Whether you’re an end-user looking to level up your skills or a tech enthusiast eager to dive into advanced solutions, the Redgate Seminar is your ticket to staying informed and empowered in the rapidly changing field of Database DevOps

A bit about me :

I am a Microsoft Data Platform MVP and VMware Expert with a passion for efficient database and application deployment using DevOps methodologies. I have 19 years’ of IT experience in managing and deploying large scale databases on SQL Server technologies.

I’ve been managing SQL Server since SQL Server 2000, and pragmatic approaches to delivering business value to clients is his career passion. Educating and helping others learn is a driver for me and I’m a PASS Chapter Leader, international speaker, and a repeat guest lecturer at a local university.

If you’re in any of these cities and this sounds like your thing, be sure to check it out and register with the links below!

Join us in Brisbane on 2nd May. Discover how your business can benefit from solving complex challenges of database management across the entire DevOps lifecycle on any database, anywhere. Hear from industry experts as they share experiences of how to increase efficiency, reduce errors and safeguard business-critical data.

Join us in Sydney on 7th May. Discover how your business can benefit from solving complex challenges of database management across the entire DevOps lifecycle on any database, anywhere. Hear from industry experts as they share experiences of how to increase efficiency, reduce errors and safeguard business-critical data.

Join us in Melbourne on 9th May. Discover how your business can benefit from solving complex challenges of database management across the entire DevOps lifecycle on any database, anywhere. Hear from industry experts as they share experiences of how to increase efficiency, reduce errors and safeguard business-critical data.

Hope to see you at one of these!!.

Yip.

Test Data Management – 2024 is your year to do it

~ Hamish Watson ~ Leave a comment

This blog post is about Test Data Management – or my take on it.

I just saw that a video I did for my good mates at Redgate is just over 100,000 views.

DevOps Trends – Testing Data – Hamish Watson | Redgate

Test data management (TDM) is all about handling the data used in software testing. It’s basically making sure you’ve got the right tools before starting a job – in this case, ensuring your test data is spot-on for checking if your software works as it should.

Now, in the world of DevOps, TDM is super important because it helps keep testing on track with the speedy development process. Pretty much meaning you need the right stuff to keep you going without slowing down.

How does TDM fit into DevOps?

  1. Being Nimble: DevOps is all about being quick on your feet. TDM makes sure your testing can keep pace with development by giving you the right data when you need it. It’s like having your gear sorted so you can jump into action without missing a beat.
  2. Making Things Easy: DevOps loves automation, and TDM is no different. It’s about setting things up so your testing practically runs itself. Just like having your chores automated so you can spend more time chilling out.
  3. Setting Up Camp: DevOps likes to set up testing environments on the fly. TDM ensures these spots have everything they need for a good test run. It’s like having your camping gear ready to go whenever you feel like hitting the road.
  4. Keeping Things Private: Test data often has sensitive info. TDM makes sure this stuff stays safe and sound during testing. It’s like keeping your personal info locked up tight so no one gets their hands on it.
  5. Testing Early and Often: DevOps wants testing to happen early on. TDM helps make this possible by getting the test data ready ahead of time. It’s like doing your homework early so you can kick back and relax later.

So, in a nutshell, good TDM is the secret ingedient that keeps the DevOps machine running smoothly. It’s all about having the right stuff in the right place at the right time, so you can keep moving forward without missing a beat.

So for 2024 – what are you doing about managing your test data management?
Is it in the too hard column/basket? If so – don’t worry I am gonna be writing about this a lot…..

Yip.

Interview around DevOps, Data, AI and Microsoft Fabric

~ Hamish Watson ~ Leave a comment

A few weeks ago I did an interiview with Nagaraj Venkatesan – a good friend of mine who works for Microsoft Singapore.

You can watch video below – I talk about all things DevOps – where it relates to data, Microsoft Fabric and my thoughts on the impact of AI:
https://www.youtube.com/watch?v=jBseLdRH1FU

I hope you enjoy it as much as I did doing it.

Yip.

Goals for 2024

~ Hamish Watson ~ Leave a comment

Way back in 2019 I set some goals…. well I wrote some goals and posted them here

2019 seems a lifetime ago…..that was the year I travelled 200,000 air kilometres (about 125,000 air miles) helping communities learn, I helped a community that was grieving here in Christchurch, ran for the PASS Board, established my first foundational client, wasn’t scared of a cough and paid my mortgage off. Oh and I was married, but that’s a whole different story.

Fast forward 5.25 years and here I am, about to write about goals again. Now that doesn’t mean that I have not had goals in that time – one of my goals of 2021 was to survive a messy divorce and live for my kids every day. My goal for 2022 was to rebuild my life and establish my new home base. My goals for 2023 were to accelerate what I was doing and go forward at a frenetic pace that is how I live life. This involved setting up my company as a Professional Services company with consultants working through it, rather than just me doing keyboard things.

In 2024 my initial vision for this year was to innovate – whilst still maintaining my life based around my children, helping mates out with work stuff, doing great community things and enjoying great food/wine.

So here are my goals for 2024 – a year that I hope will encompass diversification of what I do in industry while maintaining good stable financial outcomes (that sounds wordy doesn’t it… I used my words carefully).

My strategic goals for 2024 are around FinOps, Real-Time Analytics, DevOps, and Artificial Intelligence (AI) which I hope will significantly enhance my company’s (Morph iT Limited) efficiency, innovation, and competitive edge….. or maybe I establish an awesome start-up dedicated to all these things (more on that in another post). Why real-time analytics you might be asking…

…..well, I am a Data Platform MVP with Microsoft and data is core to everything I have done in the past 25 years.

FinOps Goals

I want to help companies realise these benefits:

  1. Cost Optimization and Transparency: Implement comprehensive monitoring and reporting mechanisms to provide real-time visibility into cloud spending across different departments and projects. Help clients get a 20% reduction in unnecessary cloud expenditures through more informed decision-making (using data) and waste elimination.
  2. Cross-Functional FinOps Team: Using my existing DevOps coaching skills to write material that will help clients establish a cross-functional FinOps team that includes finance, operations, and development leaders to ensure alignment of cloud investment with business outcomes.
  3. FinOps Training and Certification: Ensure I am certified in FinOps principles by the end of June 2024 to be able to help clients embed FinOps culture deeply within their organisation.

Real-Time Analytics Goals

  1. Speak more about a Unified Data Platform: Yip, this is about Azure Data Explorer a real-time analytics platform that consolidates data across various sources, reducing the time to insight from hours to minutes. This will be around how it integrates into the Microsoft Fabric ecosystem.

DevOps Goals

These goals are more around what areas I want to focus on in 2024, you could call them trends I foresee…
I spoke about trends in these YouTube videos:

https://youtu.be/0yR0GhDv1q8
https://youtu.be/FyLVOht7T1w
https://youtu.be/L2Cy1zu-egk
  1. Growth of AI and Machine Learning in DevOps (AIOps)
    AI and machine learning will increasingly be integrated into DevOps tools and processes, enabling more sophisticated analysis of data, predictive analytics, and automation. AIOps can help teams anticipate issues, optimize performance, and automate routine tasks, leading to more proactive and intelligent operations.
  2. Emphasis on DevSecOps
    Security will continue to be a critical focus, with an emphasis on integrating security practices throughout the development lifecycle rather than treating them as an afterthought. DevSecOps practices, which incorporate security early in the development process, will become more prevalent, driven by the need to address security challenges in a more agile and efficient manner.
  3. Serverless Architectures and Functions as a Service (FaaS)
    The move towards serverless computing and FaaS is expected to accelerate, offering teams the ability to focus on coding and deploying code without worrying about the underlying infrastructure. This shift supports more scalable, cost-effective, and efficient software development and deployment processes.
  4. Infrastructure as Code (IaC) Maturity
    As organizations seek more scalable and manageable infrastructure provisioning, the use of IaC will mature and expand. Tools like Terraform and Ansible will continue to evolve, enabling more dynamic and flexible management of infrastructure, which is particularly crucial in multi-cloud and hybrid environments.
  5. Enhanced Focus on Observability
    Observability will become even more critical as systems grow more complex. The ability to monitor, log, and trace system activities in real-time allows teams to understand the health of their applications deeply and respond quickly to issues. Enhanced observability tools and practices will become a staple in DevOps toolchains.
  6. Sustainability in DevOps
    Sustainability and green computing will start to influence DevOps practices, with an increasing focus on optimizing resource usage, reducing waste, and considering the environmental impact of software development and deployment activities.

These will be core tenants of what I want to do both in the community and for clients of my company.

Artificial Intelligence Goals

  1. AI-Driven Products and Services: Launch a new product or service offering powered by AI to address customer needs and create new revenue streams.
  2. AI for Operational Excellence: Implement AI algorithms in my own activities to improve operational efficiency, such as predictive maintenance, inventory management, and demand forecasting, targeting a 30% reduction in operational costs.
  3. Ethics and Responsibility in AI: Develop and implement a comprehensive AI ethics policy to guide responsible AI development and usage within any organisation, including transparency, privacy, and fairness considerations.
  4. Upskill in AI and Machine Learning: I want to understand all things AI and machine learning fundamentals to build my own capabilities.

By focusing on these goals, I want to leverage the transformative potential of FinOps, real-time analytics, DevOps, and AI to help the corporate and educational communities realise the benefits of driving cost efficiency, operational excellence, innovation, and sustainable growth.

Sounds like some good goals to have to help #makeStuffGo….

Yip.

DevOps: It’s About the Team, Not Just the Tech

~ Hamish Watson ~ Leave a comment

In November 2023 I did a session at PASS Summit and one of my sessions was voted https://passdatacommunitysummit.com/about/news/have-you-watched-some-of-the-most-popular-sessions-from-summit-2023/

That session was called DevOps is about Growing People rather than using Cool Tools basically DevOps is not just about using the latest and greatest tools to automate software development & deployment processes. It is a culture that emphasizes collaboration, communication, and continuous improvement.

DevOps, a term that merges ‘development’ and ‘operations,’ often conjures images of technology, tools, and software. However, at its core, DevOps is far more about people and how they work together than the technologies they use. It represents a cultural shift, emphasizing collaboration, communication, and integration between software developers and IT operations teams.

This approach aims to create a more agile, responsive, and efficient workflow for building, testing, and releasing software.Here are some more of my thoughts around this area:

Understanding DevOps: Beyond Tools and Automation

The essence of DevOps extends beyond merely implementing the right tools or automating processes. While these elements are important, the true power of DevOps lies in its ability to transform how teams collaborate and innovate together. It challenges traditional siloed structures by fostering a culture where sharing, mutual respect, and continuous improvement are paramount. This cultural shift can lead to more effective and efficient practices, ultimately driving better outcomes for both the team and the organization.

The Human Element: Key to DevOps Success

At the heart of DevOps is the recognition that software is created by people, for people. Thus, focusing on the human aspect—how team members interact, share knowledge, and support one another—is crucial. This human-centric approach encourages a more engaged and motivated team, leading to higher quality work and innovation. It’s about creating an environment where continuous feedback, learning, and adaptation are part of the daily routine, enabling teams to respond swiftly and effectively to changes and challenges.

Building a Collaborative Culture

Adopting a DevOps culture means breaking down barriers between departments and promoting open communication. It’s about moving away from a mindset where development and operations teams have separate goals and responsibilities. Instead, DevOps advocates for shared objectives, mutual accountability, and collaboration throughout the software lifecycle. This integrated approach not only accelerates delivery times but also enhances the reliability and quality of software products.

Continuous Learning and Improvement

A pivotal component of DevOps is fostering a culture of continuous learning and improvement. This involves regular reflection on processes, outcomes, and team dynamics, followed by proactive efforts to address issues and capitalize on opportunities for growth. Encouraging experimentation and accepting failures as learning opportunities are key aspects of this mindset. By continuously seeking ways to improve, teams can adapt to evolving needs and technologies, ensuring they remain competitive and effective.

The Role of Leadership

Leaders play a critical role in driving the cultural change necessary for successful DevOps implementation. They must champion the values of collaboration, transparency, and continuous improvement, setting the tone for the entire organization. Leaders should also provide the support and resources needed for teams to experiment, learn, and grow together. By embodying the principles of DevOps in their actions and decisions, leaders can inspire their teams to embrace this transformative approach.

So remember:

DevOps is not just a set of practices or tools; it’s a philosophy that prioritizes the human elements of software development and operations. By fostering a culture of collaboration, continuous improvement, and shared responsibility, organizations can unlock the full potential of their teams. This people-centric approach to DevOps can lead to more innovative solutions, faster delivery times, and higher quality software, ultimately benefiting both the team and the wider organization.

I really enjoyed doing the session, people are core to DevOps and presenting about it and how it can positively affect your life is core to me.

Yip.

KQL Series – KQL the next query language you need to learn – a video from Data Exposed

~ Hamish Watson ~ Leave a comment

I love KQL so much I even made a video and if you compare it to my last blog post – yeah my hair has changed a bit…
And my beard.
And my clothing…

Check out Data Exposed here – it is an AWESOME site:

https://learn.microsoft.com/en-us/shows/data-exposed/

If you want to see a longer version of a session on KQL then do visit my last blog post here