Data Analytics With Tableau Project knowledge session - 3

Welcome and Session Overview

Introduction to Knowledge Session

• The session begins with a welcome message to participants, confirming audio visibility.

• Participants are encouraged to invite friends to join the session via shared links.

• The speaker reviews previous sessions covering project orientation and phases one and two, including problem statements and requirement analysis.

Objectives of Today's Session

• The focus is on completing the project design phase and project planning phase.

• Key templates for today include the problem solution kit, proposed solution, solution architecture, and a single project planning template.

Project Design Phase

Templates Overview

• The session will cover three templates in the project design phase: problem solution fit, proposed solution, and solution architecture.

• Emphasis is placed on teamwork during this phase for better understanding of projects.

Problem Solution Template

Understanding Problem-Solution Fit

• An example of startup phases is introduced: problem-solution fit, product-market fit, business model-market fit.

• Importance of having a clear mission statement for startups is highlighted as essential for competitive success.

Stages in Building a Startup

• Key stages include committing to vision, validating ideas through minimum viable products (MVP), scaling operations, and establishing market presence.

Case Study: Food Delivery Startup

Example Scenario

• A food delivery startup called "Quick Eats" is used as an example to illustrate problem-solution fit by addressing home-cooked food delivery challenges.

Steps in Developing Quick Eats

• Concept: Define solutions like app development connecting chefs with customers.

• Validation: Gather feedback from initial users regarding service quality.

Scaling Strategies

Expansion Plans

• Focus on scaling operations by hiring more delivery partners as demand increases.

• Secure funding from investors for further growth.

Data Analytics Project Example

Application in Retail Stores

• Discusses using data analytics to reduce customer churn in retail stores through predictive dashboards based on purchase history.

Development Process Breakdown

• Commitment: Forming core teams dedicated to developing the dashboard prototype.

• Validation: Testing MVP with real users at retail locations for feedback collection.

Problem Solution Fit Template Details

Filling Out the Template

• Explanation of how each section of the template should be filled out focusing on customer identification and unique selling propositions.

Importance of Problem-Solution Fit

• Highlights that effective problem-solution fits enhance trust among customers while meeting their needs effectively.

Proposed Solution Template Overview

Components of Proposed Solutions

• Introduces elements such as defining problems clearly along with potential solutions that address those issues effectively.

Understanding the Problem Statement

Defining the Problem

• The initial step is to clearly articulate the problem being addressed, focusing on its current situation and impact. This clarity is essential for developing a solution.

• A well-defined problem statement sets the foundation for identifying effective solutions. It should be specific and confident in its articulation.

Idea and Solution Description

• The proposed solution must be described simply so that anyone can understand how it addresses the identified problem. This includes detailing how the solution works and why it is superior to existing alternatives.

Novelty and Uniqueness

• It's crucial to identify what makes your solution unique compared to existing ones. This involves analyzing current solutions to highlight distinctive features or approaches that provide an advantage.

Social Impact and Customer Satisfaction

Benefits of the Solution

• Consideration of how the solution benefits society or individuals is vital, including aspects like ease of life, safety, or overall improvement in quality of life. Customer reactions should also be anticipated based on these benefits.

Business Model Development

Revenue Generation

• The business model should outline how revenue will be generated from the proposed solution, even if exact financial details are not available initially. Identifying potential users or buyers is key here as well.

Scalability of Solution

• Discuss whether your solution can grow or expand effectively without losing its effectiveness when handling more users or entering different markets. This scalability aspect is critical for long-term success.

Real World Scenario: Restaurant Example

Problem Statement in Context

• An example involving restaurants illustrates a common issue: food waste due to inaccurate cooking quantities leading to customer dissatisfaction when meals are unavailable or excess waste when too much food is prepared. A predictive system could mitigate this issue by forecasting daily demand accurately using machine learning techniques based on historical data such as past sales trends, weather conditions, and holidays.

Social Impact Analysis

Stakeholder Benefits

• Customers benefit from timely meal availability while restaurants save money through reduced waste; additionally, there are positive environmental impacts due to less food waste contributing to pollution reduction. Thus, all stakeholders gain from implementing this predictive system in restaurants.

Business Model Structure

Subscription Model Overview

• Restaurants would pay for access to an ML system designed for predicting food needs through a subscription model alongside one-time purchase options for system installation; premium versions could offer advanced features beyond basic functionalities at additional costs.

Scalability Insights

Broad Applicability

• The proposed AI-driven prediction model can cater not only to large restaurant chains but also small cafes and supermarkets, indicating significant scalability potential across various sectors within the food industry as more data enhances system accuracy over time.

Introduction to Solution Architecture

Blueprint Importance

• Solution architecture serves as a blueprint outlining how different components interact within a project—covering data sources, processing steps, storage methods, and final product delivery mechanisms which collectively solve identified problems efficiently.

Components of Solution Architecture Diagram

Key Elements

• Essential components include user interfaces (UI), project logic (processing brain), databases (data storage), external services/APIs (integration with other tools), security layers (protection against unauthorized access), and communication networks—all interconnected effectively within a diagrammatic representation.

Minimum Viable Architecture (MVA)

Efficient Project Building

• MVA emphasizes starting with essential parts necessary for functionality rather than building complex systems upfront; this approach allows quicker launches at lower costs while enabling gradual improvements based on evolving requirements over time.

Agile Planning Phase

Step-by-Step Management

• Agile planning facilitates project management through iterative updates rather than extensive upfront planning; each step aims at delivering useful outputs while allowing flexibility based on user feedback throughout development cycles.

This structured markdown file provides an organized overview of key concepts discussed in the transcript along with relevant timestamps linked directly back to their respective sections for easy reference during study sessions.

Understanding Burn and Velocity Charts in Project Management

Burn Chart Overview

• A burn chart is utilized to track the duration of tasks within a sprint, indicating how long each task takes to complete compared to its planned duration.

Velocity Chart Insights

• The velocity chart displays the time taken for each sprint (Sprint 1, Sprint 2, etc.) and the number of story points committed versus completed. This helps assess team performance over multiple sprints.

Role of the Product Owner

• The product owner is responsible for organizing and prioritizing backlogs, breaking down large tasks into smaller, manageable pieces for team distribution.

What are Story Points?

Definition and Importance

• Story points measure the effort required for a task by considering work difficulty, time needed, and associated risks. They assist teams in better planning by simplifying larger tasks into smaller ones.

Fibonacci Sequence in Estimation

• Story points often utilize a Fibonacci sequence where each number is derived from adding the two preceding numbers (e.g., 1, 2, 3, 5). This method aids in estimating task complexity effectively.

Project Planning Template

Template Structure

• The project planning template includes fields for team ID, project name, functional requirements (epics), user stories with corresponding story points.

Understanding Sprints and Epics

• A sprint is defined as a fixed period during which specific tasks are completed. An epic represents a significant task that can be broken down into smaller stories or sub-tasks.

Task Classification Based on Difficulty

Categorization of Tasks

• Tasks are classified based on their difficulty: very easy, normal, moderate, and difficult. Each category corresponds to specific story point values using the Fibonacci series.

Example of Data Collection Epic

Breakdown of Data Collection Tasks

• In an example epic focused on data collection:

• Gathering data has two story points due to its importance.

• Loading data is assigned one story point as it’s considered easier.

• Totaling three story points for this epic emphasizes its priority level.

Data Preparation Epic Details

Handling Various Data Issues

• The data preparation epic involves handling missing values and inconsistencies. Each sub-task's complexity influences its assigned story points based on estimated effort levels.

Clarifying Key Terms: Sprint, Epic & Story Points

Definitions Recap

• Sprint: Duration allocated to complete project milestones.

• Epic: Major milestone encompassing several related tasks.

• Story: Subtasks under each epic that contribute towards completion.

• Story Points: Numerical representation of task complexity aiding estimation processes.

Calculating Total Story Points

Summation Process

• To calculate total story points per sprint:

• Sum individual story point values assigned to each task within that sprint.

• For instance:

• Sprint One totals twelve story points while Sprint Two totals twenty after summing respective tasks' complexities.

Finalizing Project Templates

Completing Documentation

• Fill out tables with details such as total story points achieved per sprint along with start dates and release dates. This documentation aids tracking progress throughout project phases.