Data Processing

Use AI for efficient data analysis, transformation, and preparation.

Data Analysis

Statistical Evaluations

Analyze this data table:
[Insert data]

Calculate:
- Mean, median, standard deviation
- Minimum and maximum
- Quartiles
- Correlations between variables

Trend Analysis

Identify trends in this time series data:
[Data with timestamp]

Analyze:
- Growth rates
- Seasonal patterns
- Anomalies
- Forecast for next period

Data Preparation

Data Cleaning

Clean this raw data:
[CSV/Excel data]

Tasks:
- Remove duplicates
- Handle missing values
- Standardize formatting
- Identify outliers

Data Transformation

Transform this data from format A to format B:

Input format: [Description]
Target format: [Description]

Example mapping:
[Input] → [Output]

Data Visualization

Chart Descriptions

Describe a suitable chart for this data:
[Data type and purpose]

Recommend:
- Chart type
- Axis labels
- Color scheme
- Important data points

Dashboard Concepts

Develop a dashboard concept for:
- Target audience: [Who uses it]
- Metrics: [KPIs]
- Update frequency: [How often]

Layout:
- Main metrics at top
- Detailed views
- Filter options

Data Interpretation

Business Intelligence

Interpret this business data:
[Revenue, costs, etc.]

Find:
- Main drivers for changes
- Problem areas
- Optimization potential
- Action recommendations

Market Research

Analyze these survey results:
[Raw data]

Create:
- Summary of key findings
- Demographic breakdown
- Sentiment analysis
- Strategic implications

Tip: Always start with exploratory data analysis before moving on to specific questions.