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Data Analyst

Analyze data, write SQL queries, and generate insights.

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"Hi! I can help you write SQL queries and analyze datasets."

Use Cases

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Data Interpretation

Analyze datasets and extract meaningful insights, trends, and patterns.

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Report Generation

Create professional data reports with visualizations and executive summaries.

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SQL Query Building

Generate complex SQL queries to extract exactly the data you need.

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Statistical Analysis

Perform statistical tests, correlation analysis, and hypothesis testing.

See It In Action

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Your Prompt
Analyze this sales data and identify trends:
Q1: $1.2M, Q2: $1.5M, Q3: $1.1M, Q4: $2.1M
Products: A(40%), B(35%), C(25%)
Regions: North(50%), South(30%), West(20%)
$output:insights
$output:insights
Data Analyst Response

📊 Sales Analysis Report

Key Findings:

1. Revenue Trend

- Total Annual Revenue: $5.9M

- Average Quarterly: $1.475M

- Growth: Q4 showed 91% increase over Q3 (strongest quarter)

• Concern: Q3 dip suggests seasonality or issue worth investigating

2. Product Performance

| Product | Revenue | Share |

|---------|---------|-------|

| A | $2.36M | 40% |

| B | $2.07M | 35% |

| C | $1.48M | 25% |

• Product A is the clear leader

• Consider investing more in Product B marketing (close second)

• Product C may need repositioning or discontinuation analysis

3. Regional Distribution

- North region drives 50% of revenue—critical market

• South is underperforming relative to population

• West shows growth potential (20% share but often has higher spending power)

Recommendations:

1. Investigate Q3 decline—seasonal? Competitor action?

2. Double down on Q4 strategies (what worked?)

3. Expand West region presence

4. Consider Product C lifecycle analysis

Generated Outputs
Quarterly Revenue
Q1: $1.2M | Q2: $1.5M | Q3: $1.1M | Q4: $2.1M
Key Insights
• 91% Q4 growth • North region dominates (50%) • Product A leads (40%)
Examples:
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Key Features

Trend analysis SQL generation Report writing Statistical analysis

How To Use

1.
Share your data - Paste datasets, tables, or describe your data structure
2.
Specify output - Use $output:insights, $output:report, or $output:visualization
3.
Set SQL dialect - Add $dialect:postgresql or $dialect:mysql
4.
Request specific analysis - Ask for trends, correlations, or forecasts

Who Is This For?

Data analysts, business intelligence professionals, marketing teams, product managers, and executives who need data-driven insights.

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