Post #2571

✅Data Analyst Interview Questions with Answers: Part-7 61. Why is data visualization important? Data visualization converts raw numbers into visual formats so humans can understand patterns, trends, and problems quickly. • Humans process visuals faster than tables • Managers don’t read SQL or Excel sheets • Decisions are made in meetings, not databases Example: A line chart instantly shows sales are declining for 3 months > Data visualization helps stakeholders quickly understand insights and take action without analyzing raw data. 62. Difference between bar chart and line chart? • Bar Chart: Used for comparison between categories • Line Chart: Used for trends over time > If time is involved → line chart. If comparison is involved → bar chart. 63. When do you use a pie chart? Pie charts show percentage or share of a whole. • Use for fewer categories (≤ 5) • When proportions matter more than exact values > Pie charts are best for showing part-to-whole relationships with limited categories. 64. What is a dashboard? A dashboard is a single screen view that tracks key metrics and performance indicators. • Monitor business health • Track KPIs in real time • Support quick decisions > A dashboard provides a high-level summary of business performance at a glance. 65. What makes a good dashboard? A good dashboard is clear, focused, and actionable. • One business goal per dashboard • KPIs at the top • Consistent colors • Minimal clutter > A good dashboard answers business questions clearly and helps decision-making. 66. What is a KPI card? A KPI card displays one critical metric clearly. • Highlighting performance • Comparing actual vs target > KPI cards highlight the most important metrics for quick evaluation. 67. Common visualization mistakes? • Using wrong chart type • Too many colors • No axis labels • Showing everything on one page > Poor visualization can mislead users even if the data is correct. 68. How do you choose the right chart? • Comparison → Bar • Trend → Line • Distribution → Histogram • Relationship → Scatter • Part-to-whole → Pie > Chart selection depends on the goal. 69. What is drill-down? Drill-down allows users to move from summary to detailed data. • Yearly sales → Monthly → Daily • Region → City → Store > Drill-down helps users explore deeper insights without cluttering the dashboard. 70. What is data storytelling? Data storytelling combines data, visualization, and narrative. • Example: “Sales dropped by 10% because website traffic declined in the North region after ad spend was reduced.” > Data storytelling turns insights into actions by explaining what happened, why, and what to do next. Double Tap ♥️ For Part-8