| import streamlit as st | |
| def run(): | |
| st.title("Business Understanding") | |
| st.write("## Overview") | |
| st.write(""" | |
| The Business Understanding phase is the first step in the CRISP-DM process. It involves understanding the project objectives and requirements from a business perspective, and then converting this knowledge into a data mining problem definition and a preliminary plan. | |
| """) | |
| st.write("## Key Concepts & Explanations") | |
| st.markdown(""" | |
| - **Business Goals**: Clearly define the problem (e.g., Predict customer churn). | |
| - **Constraints**: Time, budget, available data, legal considerations. | |
| - **Success Metrics**: Accuracy, revenue impact, efficiency gains. | |
| """) | |
| st.write("## Introduction") | |
| st.write(""" | |
| Business Understanding is crucial for the success of any data science project. It ensures that the project is aligned with the business objectives and that the results will be actionable and valuable to the organization. | |
| """) | |
| st.header("Objectives") | |
| st.write(""" | |
| - **Understand the Business Objectives**: Gain a clear understanding of the business goals and how they translate into data mining goals. | |
| - **Assess the Situation**: Evaluate the current situation, including resources, constraints, and risks. | |
| - **Determine Data Mining Goals**: Define specific data mining goals that align with the business objectives. | |
| - **Produce a Project Plan**: Develop a detailed project plan that outlines the steps, resources, and timeline for the project. | |
| """) | |
| st.header("Key Activities") | |
| st.write(""" | |
| - **Identify Business Objectives and Constraints**: Work with stakeholders to identify the key business objectives and any constraints that may impact the project. | |
| - **Define Success Criteria**: Establish clear criteria for success, including key performance indicators (KPIs) and metrics. | |
| - **Develop a Project Plan**: Create a comprehensive project plan that includes a timeline, resource allocation, and risk management strategy. | |
| """) | |
| st.write("## Detailed Steps") | |
| st.write(""" | |
| 1. **Determine Business Objectives**: | |
| - Interview stakeholders to understand their goals and expectations. | |
| - Identify the key business questions that need to be answered. | |
| 2. **Assess the Situation**: | |
| - Conduct a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats). | |
| - Review existing resources, including data, tools, and expertise. | |
| 3. **Define Data Mining Goals**: | |
| - Translate business objectives into specific data mining goals. | |
| - Ensure that the goals are measurable and achievable. | |
| 4. **Produce a Project Plan**: | |
| - Outline the project phases, tasks, and deliverables. | |
| - Allocate resources and assign responsibilities. | |
| - Develop a risk management plan to address potential challenges. | |
| """) | |
| st.write("## Quiz: Conceptual Questions") | |
| q1 = st.radio("What is the main purpose of the Business Understanding phase?", ["Define project goals", "Collect data", "Build models"]) | |
| if q1 == "Define project goals": | |
| st.success("✅ Correct!") | |
| else: | |
| st.error("❌ Incorrect. The main purpose is to define project goals.") | |
| st.write("## Learning Resources") | |
| st.markdown(""" | |
| - 📘 [CRISP-DM Guide](https://www.sv-europe.com/crisp-dm-methodology/) | |
| - 🎓 [Understanding Business Objectives](https://www.datasciencecentral.com/profiles/blogs/understanding-business-objectives-in-data-science) | |
| - 🔬 [Business Understanding in Data Science](https://towardsdatascience.com/business-understanding-in-data-science-1a1d5e8b1c3d) | |
| """) | |