Bridging the Gap
MARCH 30, 2023
You get into those specific technical requirements even though you don’t know how to write the code that underlies it. Technical Skill 2: Wireframes for Visual Requirements The second requirements model that can be helpful in expressing technical requirements like this is wireframes.
The BAWorld
MARCH 13, 2024
Process Modeling: Unveiling the Flow Imagine a roadmap outlining your business processes, visualizing workflows, decision points, and interactions. Process modeling , this visual representation, empowers stakeholders to identify inefficiencies, streamline workflows, and maximize resource utilization.
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Bridging the Gap
OCTOBER 12, 2023
A System Context Diagram is an elegant solution and visual powerhouse that will have your business and technical stakeholders nodding in agreements as you confidently navigate the intricacies of scope. It was a great way to really establish the scope of the project visually. You can claim your free copy now by clicking below. >>
Bridging the Gap
NOVEMBER 17, 2023
We miss requirements either when we don’t involve the right stakeholders (i.e., apply the right communication skills) or overlook key areas of requirements because we are only looking at one view. Data modeling is critical on all kinds of projects, but especially data migration and system integration projects.
Astera
FEBRUARY 1, 2024
Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?
Bridging the Gap
SEPTEMBER 7, 2023
This is a type of visual model that’s a great way to elicit a lot of information and create a shared understanding of both your current state and your future state process relatively quickly. In addition to the user facing functionality of the software, the business analyst may identify elements of the information model as well.
Astera
JANUARY 23, 2024
Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.
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