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trend-analysis

Analyze multidimensional performance data to classify groups and forecast future values.

4.9k|347|Updated Apr 14, 2026
Search Tags:#performance#data analysis#visualization#prediction#forecast#trend
One-click install
npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill trend-analysis-opensensenova
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trend-analysis
Source: https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-da-excel-workflow/capability/excel-data-analysis/trend-analysis
Command: npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill trend-analysis-opensensenova

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables users to analyze complex datasets by assessing performance, setting tiers, and predicting future trends, streamlining performance evaluation processes.

Core Features & Use Cases

  • Data Segmentation and Tier Setting: Classifies data groups into high, medium, and low performance tiers based on specified criteria.
  • Trend Prediction: Calculates future values using differential growth rates, supporting scenarios like sales forecasts or performance benchmarking.
  • Use Case: A company wants to forecast next quarter's sales by analyzing current multi-region data and visualizing projected growth, aiding decision-making.

Quick Start

Load your dataset, configure grouping and target columns, then run the prediction and visualization steps to obtain trend insights.

Frequently Asked Questions about trend-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I forecast future sales trends from multi-dimensional performance data?▼

Forecast future sales trends by loading your multidimensional dataset, configuring grouping and target columns, then calculating future values using differential growth rates to generate projected growth insights.

What is the best way to classify business performance data into high, medium, and low tiers?▼

Classifying business performance data into tiers involves assessing multidimensional datasets against specified criteria to automatically segment groups into high, medium, and low performance categories.

Can I visualize predicted data growth using pandas and matplotlib for performance benchmarking?▼

Yes, you can visualize predicted data growth for performance benchmarking by running prediction steps that utilize pandas, numpy, and matplotlib to plot projected future values.

How do I calculate future values using differential growth rates for trend analysis?▼

Calculate future values for trend analysis by applying differential growth rate statistical calculations to your configured target columns, estimating future metrics from historical performance data.

Does trend analysis work with multi-region datasets for predicting next quarter's performance?▼

Yes, trend analysis works with multi-region datasets to predict next quarter's performance by analyzing current regional data and visualizing projected growth to aid business decision-making.

What data formats do I need to configure grouping and target columns for trend prediction?▼

You need multidimensional performance datasets that support configurable grouping and target columns, allowing statistical calculations to estimate future values and visualize trend predictions.

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