Allows users to query and analyze data using plain English commands.
Uses AI algorithms to forecast trends and outcomes based on historical data.
Identifies and corrects data errors, duplicates, and inconsistencies automatically.
Generates charts and graphs that adapt to data insights for better understanding.
Connects with various data sources, APIs, and platforms like Google Sheets and Excel.
Enables real-time team collaboration on spreadsheets with AI-assisted features.
Predict future revenues, expenses, and cash flows using historical financial data and AI models.
Analyze sales trends, customer behavior, and performance metrics to identify growth opportunities.
Optimize stock levels, predict demand, and reduce waste by forecasting inventory needs.
Measure campaign effectiveness, ROI, and audience engagement through data-driven insights.
Analyze employee data for retention, performance evaluation, and workforce planning.
Process and analyze large datasets for research projects, enabling efficient data interpretation.
Manage patient records, predict health trends, and optimize resource allocation in healthcare settings.
Forecast supply needs, monitor logistics, and reduce costs through predictive analytics.
Segment customers based on behavior and demographics for targeted marketing strategies.
Evaluate business risks, such as market fluctuations or operational issues, using AI-driven models.
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