Category: Uncategorized

Fusion Development – Introduction

The roles of technology, data, and systems are rapidly transforming, leading to democratization in data and development within organizations. This shift introduces Data Products and Citizen Developers and Analysts, empowering individuals without IT backgrounds to create and analyze data-driven solutions. A collaborative approach called Fusion Development maximizes these roles, breaking silos and encouraging shared problem-solving. These trends can potentially reshape the digital world across various sectors and industries.

How we interact with technology, data, and systems is transforming significantly. Traditional boundaries that define roles and responsibilities are blurring, leading to new opportunities and challenges. One of the most fantastic opportunities is democratizing data and development within organizations. The ability to translate something you imagine into a computer program or data visualization is no longer limited to people with computer programming backgrounds and the education and training that go with them.

Data Products are tools that transform intricate data into intelligible and actionable insights. They process and render data into a more palatable format, thereby bestowing individuals — regardless of their technical acumen — with the power to make data-driven decisions. By presenting data in a user-friendly manner, data products serve as bridges that connect raw data to meaningful insights. They democratize data, making it accessible not just to data aficionados and specialists but to everyone, fostering a culture where data-driven insights become the cornerstone of decision-making processes.

Citizen Developers are individuals who, despite lacking formal IT backgrounds, take the initiative to create applications or solutions tailored to address specific needs. Propelled by the advent of user-friendly platforms, like Microsoft Power Platform, these professionals venture into realms traditionally reserved for programmers, democratizing the software development process. They translate ideas into functional solutions, bridging gaps and fostering innovation without being encumbered by the intricacies associated with traditional software development. Their endeavors often reflect a pragmatic understanding of the problem, coupled with creatively utilizing available resources to devise solutions.

Similarly, Citizen Data Analysts are individuals from diverse professional backgrounds who leverage data products to interpret and analyze data, amalgamating their domain knowledge with analytical tools to extract meaningful insights. Unlike traditional data scientists, who specialize in statistics, data processing, and analysis, Citizen Data Analysts bring their professional background and experience to analyze data in any role. By harnessing the power of data products, they can transcend the technical barriers that often surround data analytics, delving into data-driven inquiry to uncover actionable insights that can inform decision-making within their respective domains.

The essence of Citizen Developers and Citizen Data Analysts lies in their ability to lower the barriers to entry in software creation and analytics, empowering a broader spectrum of individuals to contribute to the digital solutions landscape. This ability, in turn, accelerates problem-solving and cultivates a more inclusive and innovative development ecosystem. Through their efforts, professionals not only contribute to the rapid prototyping and deployment of solutions but also to the broader digital transformation narrative, reshaping how organizations approach software development, analytics, and problem-solving.

Fusion Development encapsulates a collaborative approach where professional developers, citizen developers, and citizen data analysts converge to collaborate on projects. By combining the technical prowess of trained developers with the practical insights and domain expertise of citizen contributors, fusion development aims to cultivate solutions that are both technically robust and practically relevant. This collaborative ethos enables a richer understanding of problem domains and fosters a more inclusive, innovative environment for solution creation.

In the fusion development paradigm, synthesizing diverse skill sets and perspectives engenders a more holistic approach to problem-solving. Professional developers bring their technical acumen, coding skills, and understanding of software development lifecycles. In contrast, citizen contributors, with their understanding of end-user needs and domain-specific challenges, contribute practical insights that ensure the development of solutions tailored to real-world needs.

The beauty of fusion development lies in its ability to break down the traditional silos that often exist within organizations between technical and non-technical personnel. It fosters a culture of collective problem-solving and shared ownership of projects, thereby accelerating the pace of innovation and ensuring that solutions are both technically sound and user-focused. Through this cross-functional lens, fusion development not only augments the quality and relevance of digital solutions but also cultivates a more inclusive, dynamic environment for technological innovation, ensuring that the digital solutions produced are well-aligned with user needs and organizational goals.

Over the next four weeks, we will look at these ideas in depth in the context of an elementary school and how various citizen developers and data analysts can increase their productivity and impact. While the series uses an elementary school as a backdrop to illustrate these concepts, the lessons, and principles are applicable across various sectors and industries. The goal is to provide readers with a clear understanding of how these trends are reshaping the digital world and the potential they hold for organizations and individuals alike.

How Not to Need to Kill it with Fire

Over the holidays, I tried to do a bit of professional reading to keep my mind fresh and help me be a bit more productive with some work that I’m currently doing. To this end, I read Marianne Bellotti’s Kill it with Fire: Managing Aging Computer Systems (and Future Proof Modern Ones).

I’m not sure what I expected, but I got much more. The book provides excellent case studies, tips, and history to keep everything grounded in modernizing computer systems. This is a critical skill in a world where any time we walk in a new door, we may see infrastructure and codebases between fifty years and five minutes old. Bellotti gives tools for both the technological and strategy and the critical parts of building team morale and driving stakeholder buy-in on modernization projects. 

One of the book’s first points is that technological development is highly cyclical and that if you wait long enough (or live long enough), the wheel always returns to the same ideas. The critical thing to remember is that those ideas never recombine in the same ways. Hence, modernization efforts are complicated even when the ideas rhyme, much less when they’re on opposite sides of the pendulum swing. This is increasingly an important realization, as the nature of cloud computing can appear deceptively similar to older ideas of shared compute, such as mainframes and minicomputers that we are often modernizing today. Still, all of the supporting technologies and ideas are so very different.

The book continues into the almost eternal conversation about “why modernize and why is it so risky?” One of the points made throughout the book is that technological modernization should only happen when it makes business sense, not simply because there is a new technique available. There is a tendency among so many engineers and developers to try to perfect every problem, even the ones that are already solved. So often, when these kinds of technology modernizations are divorced from the business, it leads to failures. Many times, these are not just failures of the project but the underlying tools that the organization had come to rely on, causing disruptions and outages. Bellotti reminds us, “[a]dopting new practices doesn’t necessarily make technology better, but doing so almost always makes technology more complicated, and more complicated technology is hard to maintain and ultimately more prone to failure.” These failures are damaging, not only for the organization, but for the reputation of IT, as memories of broken promises, downtime, and loss of functionality last far longer than delivered problems and months, years, or decades with minimal downtime.

Other discussions of use are on how to deal with technical debt, how to migrate to a services architecture, and handling performance issues. Each of these topics is covered from a strategic and business perspective, including the “why” of each and how to recognize when that is the problem. There are also techniques for breaking these problems down into incremental development as used in a modern development process – that also is easier for the business to understand.

Finally, a large chunk of the book approaches what to do when, as a leader, you gain a modernization project in progress and how to go about dealing with the many common problems that crop up inside a failing modernization process. This section is instrumental in identifying ways to avoid the typical “spiraling” issues that occur when a poorly executed or planned modernization program starts to go off the rails.

This book is excellent, and I’d recommend it to anyone who has to deal with or touch legacy systems, and by that, I mean any system that’s already in production.

Distance Learning (Or: Getting Back in the Saddle)

I want to talk a bit about some of how I think the incredible challenges this year are going to affect the way we operate as educational data scientists.

Wow! It’s been almost three years (be nice) since I updated this.

I wish that I could say that it’s been busy (though it has) or that I haven’t had anything to say, but it’s more that I’ve been letting my tendencies towards procrastination get the better of me. I’m going to try to make this a more regular thing, though, in the future.

Thanks to current events, my group at work has largely moved to working from home, and don’t click away thinking this will be another piece telling you how to work (or teach!) from home, I’m the last person in the world to be giving advice on either one of those topics. I want to talk a bit about some of the ways that I think these changes are going to affect the way we operate as educational data scientists.

Continue reading “Distance Learning (Or: Getting Back in the Saddle)”

EduDataSci YouTube Channel

So, I’m launching a YouTube Channel.

So, I’m launching a YouTube Channel. For the most part, I’m going to be hosting introductory videos on Data Visualization, Programming and Data Science on it.

I’m a big believer in the idea that you don’t have to have a ton of experience or tools to get started in this field, so my current thought is to target this at people with very little experience in data science, and build up individual skills.

My first video is going to be a short introduction to the general idea of data visualization, with some history. After that, I’m hoping to release one a week. Let me know if there’s anything that you think would be a good idea to include!