Data_Visualisation_Data_Science_content.pptx

Data visualization presentation for learning purpose

1. DATA VISUALISATION TEAM : Anusuya.L – 310623104015 Bavishika.S - 310623104026 Divya.D -310623104040 Hafsa.O – 310623104049 Harini.A - 310623104051 Course Name: Foundation of Data Science Course code: 231CSC304T

2. INTRODUCTION TO DATA VISUALISATION Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, maps, and other visual tools, data visualization helps to make complex data more accessible, understandable, and actionable.

3. IMPORTANCE OF DATA VISUALISATION IMPROVES UNDERSTANDING REVEALS PATTERNS AND TRENDS ENHANCES COMMUNICATION FACILITATES DATA EXPLORATION BETTER DECISION MAKING

4. DATA VISUALISATION CONSIDERATIONS AESTHETICS INTERACTIVITY REVEALANCE ACCURACY CLARITY AUDIENCE

5. Data Visualization Factors Simplicity Accessibility Comparability Data Integrity Data Granularity

6. Types of Data Visualization: Charts : Pie Chart Histogram Bubble Chart Graphs : Scatter Plot Network Graph Tree Map Best Practices for Data Visualization:- Use colors effectively Label and annotate visualizations Avoid 3D and unnecessary complexity- Use interactive visual

7. ADVANTAGES OF DATA VISUALISATION Simplifies Complex Data Identifies Trends and Patterns Improves Communication Saves Time Enhances Decision Making

8. DISADVANTAGES OF DATA VISUALISATION Misleading Representations Over Simplification Requires Skill and Knowledge Data Overload

9. What is Tableau? Tableau is a powerful data visualization tool that helps users turn raw data into interactive and intuitive dashboards Why do we need tableau? Simplifies Data Interpretation Enhances Decision-Making Encourages Data Exploration

10. FEATURES OF TABLEAU 02 Data Visualization 01 Data Connectivity and Integration 04 Data Management 03 Collaboration and Sharing

11. Data Types in Tableau Number: Whole numbers, decimals, or percentages. String : Text values, such as names, descriptions, or categories. Date : Dates and times, which can be used to create time-series analysis.

12. Creating a Basic Visualization in Tableau STEPS : 1. Connect to Data 2. Create a New Worksheet 3. Drag and Drop Fields 4. Choose Visualization Type 5. Customize the Visualization 6. Add Filters(Optional) 7. Save and Share

13. Chart which is accessible in Sheet 1

14. Create a dual-axis chart in Tableau: STEPS : 1. Create a Basic Chart 2. Combine the Charts Using Dual Axis 3. Synchronize Axes (if needed) 4. Finalize

15. Dual axis (Row)chart

16. In sheet 1 Right click on the visual to see the dual axis option where it can be selected.

17. Creating a Dashboard in Tableau 1.Open Tableau and Connect to Your Data 2. Create Charts By making sheets 3. Make a Dashboard 4. Arrange Charts In whatever order that one might prefer 5. Save and Share

18. CREATING A NEW DASHBOARD

19. APPLICATIONS 1.Objective: Let’s take an example of the Superstore data from the Tableau repository. I want to look at the profit earned by each category. Load the data Dimensioned field named Category added to the Columns shelf Measured field named Profit added to the Rows shelf

20. 2.Objective: Let’s take an example of the Superstore data from the Tableau repository. We want to know the average sales in each category. Drag dimension category and measure Sales Right click on the Sales field and select average method Drag the sales field from the canvas area to the label property under the marks shelf

21. CONCLUSION Data visualization plays a crucial role in data science by transforming complex datasets into intuitive and actionable insights.ableau supports real-time data connections and live updates, making it possible to monitor and respond to changes in data instantly. This is crucial for applications that require up-to-date information for timely decision-making.