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Waterfall Development

What is Waterfall Development?

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What is Waterfall Development?

Waterfall Development is a traditional, plan-driven practice for developing systems, focusing on detailed planning and executing in gated stages such as requirements gathering, planning, designing, development, testing, and deploying. It is well-suited for projects with low uncertainty, a well-defined solution, and requires a linear workflow.

  • Advantages: Quick team onboarding, adherence to timescales, budget predictability, simplified testing, clear outcomes, and manageable design issues.
  • Disadvantages: Challenges in defining needs and potential for slower progress.

How does Waterfall compare to Agile?

Agile and Waterfall are two contrasting project management methodologies. Agile is flexible and iterative, allowing for adaptable planning and continuous risk management with minimal documentation. Waterfall is linear and structured, emphasizing extensive planning at the project's start, rigid role assignment, comprehensive documentation, and straightforward time and cost estimates.

  • Adaptability: Agile offers more adaptability, while Waterfall provides structured predictability.
  • Planning: Agile involves continuous planning, whereas Waterfall requires upfront, linear planning.
  • Risk management: Agile includes ongoing risk management, in contrast to Waterfall's initial risk planning.
  • Documentation: Agile requires less documentation compared to Waterfall's extensive documentation needs.

When to choose Waterfall over Agile?

Choosing between Waterfall and Agile depends on the project's nature and goals. Waterfall is ideal for projects with a clear end result known from the beginning, requiring a step-by-step approach with a high level of planning and control. Agile is better suited for projects that require fast pacing, frequent direction changes, and where the final product is not fully known at the project's outset.

  • Waterfall suitability: For well-defined projects with limited scope and few variables, where planning and predictability are paramount.
  • Agile suitability: For projects that benefit from flexibility, iterative development, and continuous collaboration among team members.

What are the key differences in planning between Agile and Waterfall?

Agile planning is a continuous, flexible process that allows for changes and adaptability throughout the project. In contrast, Waterfall planning is a one-time, linear process conducted at the project's inception, outlining the entire project's scope and schedule. Agile's adaptability to change contrasts with Waterfall's structured and predictable planning.

  • Agile Planning: Iterative and adaptable, accommodating changes and new insights.
  • Waterfall Planning: Linear and detailed, with a comprehensive upfront plan.

What are plan-driven methodologies in project management?

Plan-driven methodologies are systematic approaches in project management where all activities are planned in advance, and progress is measured against this plan. These methodologies are suitable for small, well-defined projects with a limited scope and few variables. They emphasize thorough planning, clear documentation, and predictable project outcomes.

  • Characteristics: Emphasizes thorough upfront planning, detailed documentation, and predictable outcomes.
  • Applicability: Best suited for projects with well-defined requirements, limited scope, and few uncertainties.

Related terms

Data governance for Tableau

Data Governance is becoming more important as organizations move away from standard models of data management and towards individualized projects with multiple teams in multiple locations. To ensure accuracy and consistency, organizations need to properly set up Data Governance. Tableau and secoda are two tools to simplify this process. Tableau can be used to visually monitor, identify, explore, and analyze data discrepancies, while secoda offers an automated data lineage tracking system that can not only give data lineage visibility but can also help quickly detect errors. Set up for both of these tools starts by properly cataloging your data sources, data model objects, and transformations. This can be done via Tableau’s Data Visualization Paths feature or secoda’s Graph feature. Tableau then allows for data profiling and provides data level security. Also, Tableau allows you to automate routines with scripts that can be used to automate data summarization and instance updates. Secoda enables users to track data lineage and impact through capturing dependencies between tables and detect anomalies between source and target. This helps ensure data accuracy and make data governance easier. Both Tableau and secoda support a variety of governance strategies such as data privacy, data quality monitoring, and data access control. By properly setting up Data Governance with Tableau and secoda, organizations can ensure accuracy and consistency while still having access to reliable sources of data. This increases the value and improves the ROI of data-driven projects.
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