Technical Topics

The integration of AI into requirements management signals a transformative juncture, promising heightened efficiency, insightful perspectives, and streamlined processes. While challenges persist, a methodical approach to AI implementation offers a pathway to reaping these benefits. Organizations poised to embrace AI stand to elevate their requirements management processes, fostering superior project outcomes and innovation-driven success.

This is no different from the technology dilemma that many BAs find themselves in as they work to advance their BA career. There is no way you can learn everything at one time, but you can take gradual steps to continue to advance your skills.  So don't fear, I am here with some tips on how to approach this dilemma and lessen some of that overwhelm that plaques business analyst. And I truly believe the reason this is a stress is because you want to stay relevant in the field of business analysis if you are currently in a BA role or working to obtain a BA role.

Software development methodologies are an essential part of the software development process. Custom software development may use various methodologies for managing their daily operations. There are many benefits and drawbacks to using software development methodologies. The primary purpose of methodologies is to provide smooth software development per your project requirements.

There are different methodologies that have been introduced in the market in the last decade. The only intention of introducing these frameworks is to help developers make better software and business projects. However, it’s not possible to get one methodology for each development team. Hence, let’s see some top software development methodologies that are used popularly. Let’s begin then!

As a general-use technology, artificial intelligence (AI) is being likened to the steam engine and its effects on the economy in the 17th century. As a result, it is generally agreed that AI and its applications have the potential to significantly alter entire industries through the disruption of value creation and the impact of business models and organizations through a number of mechanisms, such as the redistribution of decision-making authority. Artificial intelligence is changing the nature of work and the workplace as a whole through its integration into processes and activities. Developing a more in-depth comprehension of the consequences and implications for future companies and professions is essential for a new technology like AI. AI is transforming the way we produce software in general, from enhancing code quality to shortening the time required for repetitive chores like debugging and testing. The many advantages brought to the table by artificial intelligence would help engineers become more productive and efficient, thereby revolutionizing the software development process. It is relevant and important to not only investigate how AI might improve process productivity and efficiency but also to take the first steps toward understanding how to adopt a technology that is here to stay. Some of the potential AIs tools we may consider are ChatGPT, Copilot, and TabNine. ChatGPT is a chatbot powered by a big language model. It makes use of an AI designed to have in-depth conversations with humans in order to provide solutions to complicated problems. Its capacity to have natural-sounding conversations and respond in ways that make it seem human is quite astonishing. Copilot or “AI pair programmer” is a language-agnostic AI that can provide coding ideas through natural language questions, having been trained on billions of lines of code. TabNine is an artificial intelligence code completion helper to get extended snippet ideas and focused line code completions. TabNine reuses an organization’s common coding patterns to reduce unnecessary developer toil.

Whether you’re purchasing a package (also called commercial off-the-shelf, or COTS, products) as part or all of the solution for a new project or implementing a solution in the cloud, you still need requirements. Requirements let you evaluate solution candidates so that you can select the most appropriate package, and then they let you adapt the package to meet your needs.

Where an organization opts to move into agile methodologies that help to provide quick and customized solutions, it is imperative to use a technology that supports agile workflow and application development.

There are several Frameworks and Programming Languages in the market that help in building Agile Solutions but as compared to all the available Stacks, PHP is the one that Comes up with a collection of Potential Frameworks that are actually contributing well in developing effective Application Development.

The PHP frameworks are a set of process conventions and technologies that simplify and accelerate application development and maintenance. A framework provides certain functionalities to an application through ready-made features and practices.

I’ve written this article to provide an overview of AWS (Amazon Web Services) for Business Analysts.

The cloud (in particular AWS) is now a part of many projects. If you’ve been in meetings where people have mentioned: ‘EC2’, ‘ELB’, ‘AZs’ and thought ‘WTF’ then this article should help you.

This article will provide:

• an overview of AWS (what is it, why its popular, how it’s used)
• typical AWS architecture for a project (e.g. VPN, Regions, AZs)
• cheat sheet for other key terms (EBS, EFS etc)

I spent a lot of time in the past half-century doing software work: requirements, design, user experience, programming, testing, project management, writing documentation, process improvement leadership, writing 7 books and many articles, consulting, and training. Sure, there were some side trips along the way,.... But basically I’m a software guy. Over all that time, I’ve accumulated numerous insights about the software business. Here I offer 66 of those lessons. Perhaps you’ll find them as helpful as I have.

After some research, I was taken back with so many machine learning applications already in use: weather forecasting, medical diagnoses, law enforcement, and self-driving vehicles. Also, I did not realized that it was the advancements of big data and faster computing that allowed the break-thru of AI in our daily lives. Most of us, I believe, think that artificial intelligence is still science fiction. Not so! We as business analysts need to pursue AI education and recognize the many business opportunities opening up to all of us.

Capability-based planning is a growing practice in the field of enterprise architecture. Its success is due to the fact that it provides actual value to practitioners and the organizations that employs them. Indeed, capability-based planning helps in a number of ways, from providing a clear understanding of existing capabilities to promoting effective Business-IT alignment. Considering these benefits, we thought it useful to address this practice and bring some clarity to the subject for the benefit of all who might not yet have a good handle on the topic.

DevOps is based on a culture of trusted partners. This partnership is between software development, quality assurance, security and controls, and operations. The result is a smooth and fast transition of software from development to operations. However, like Dover, if the trusted partners are somehow reorganized into formal handoffs each with their own software acceptance procedures, the movement of software is no longer smooth nor fast.

The function of a technical business analyst is to bridge between business and technical teams. This can be undertaken in various forms. First, the bridging can be done by translating business requirements into technical artifacts. The analyst must be able to assess the business and note the basic requirements of that particular business at that given time. Using their skilled knowledge in technology they must be able to translate the given come up requirements into technological terms. The requirements must, therefore, be taken care of technologically for efficiency and accuracy.

If you have some experience in modeling real-life, full-size architectures for large-scale organizations – preferably in the ArchiMate language, of course – you have likely come across the challenge of organizing your models in logical and manageable ways. In the following pages, we’re going to share our top 6 ways to organize your architecture models. These methods should help you keep your models neat and tidy, while also supporting better outcomes for your strategic initiatives. Let’s see what they are.

Strategists, architects, process experts, software developers, data managers and other professionals involved in changing the enterprise often put substantial effort in creating all kinds of useful models of their designs. In many cases, such business models, enterprise architecture models, business process models, software models, or data models are only used to specify some design, i.e. to describe what should be built. 
But there is much more value to be had from these models, by using powerful analysis techniques to elicit new insights. In the following pages I will cover 7 of these analyses, discussing the business outcomes you can achieve with their help.

The purpose of this article is to explore feature files. Feature files are documents that contain those Gherkin scenarios & requirements – they can be very useful to teams working on BDD projects. Feature files may be a key deliverable for BAs.  Feature files are where BAs store requirements & can create the bridge between requirements and automated tests (more on that later).