Is the KPI data real?

No — the dashboard uses NumPy-generated synthetic data designed to look realistic for demo and portfolio purposes. Replace the data layer with your own CSV or database connection for production use.

Can I deploy this to Streamlit Cloud?

Yes. Push to GitHub and connect via share.streamlit.io. Ensure requirements.txt lists all dependencies.

How does this compare to the LangChain Enterprise Dashboard?

The KPI dashboard is a focused BI demo. The LangChain Enterprise Dashboard is a full GenAI workbench with multi-agent routing, RAG, and MLOps tooling — see draketalley.ai/blog/langchain-enterprise-ai-workbench.

What Python version is required?

Python 3.9+ with Streamlit 1.28+. Check requirements.txt in the repository for pinned versions.

Streamlit KPI Dashboard: Executive BI Reporting in Python

Project Summary

Streamlit KPI dashboard demonstrating executive-quality BI reporting with synthetic data, interactive charts, and period-over-period metric deltas.

The Streamlit KPI Dashboard is an executive-quality business intelligence demo built entirely in Python. It generates realistic synthetic KPI data with NumPy, renders interactive charts and metric cards in Streamlit, and demonstrates how data scientists can ship stakeholder-ready reporting without a separate frontend team. For SEO around Streamlit dashboard, KPI visualization Python, and business intelligence prototyping, this repo is a concise proof point that complements my larger FastAPI + Next.js production systems.

Dashboard capabilities

Synthetic KPI time series with configurable seasonality, trend, and noise parameters
Metric cards with period-over-period delta indicators (up/down/neutral)
Interactive line, bar, and area charts with Streamlit-native widgets
Sidebar filters for date range, segment, and metric category
Dark/light theme compatibility via Streamlit theming
Single-file deployability — ideal for internal demos and portfolio review

Architecture

Component	Technology	Role
Data layer	NumPy, pandas	Synthetic KPI generation and aggregation
UI	Streamlit	Layout, widgets, and chart rendering
Charts	Streamlit native + Plotly optional	Interactive visualization
Config	Python constants / env	Seed, date range, segment definitions

Quick start

git clone https://github.com/cdtalley/streamlitKPIDashboard
cd streamlitKPIDashboard
pip install streamlit numpy pandas plotly
streamlit run dashboard.py

Key Features & Capabilities

Synthetic KPI time series with configurable seasonality and trend
Metric cards with period-over-period delta indicators
Interactive line, bar, and area charts with sidebar filters
Single-file deployability for demos and portfolio review

Tech Stack & Components

PythonStreamlitNumPypandasPlotly

Getting Started

1.Launch dashboard

Requires Streamlit and NumPy.

git clone https://github.com/cdtalley/streamlitKPIDashboard
pip install streamlit numpy pandas plotly
streamlit run dashboard.py

Frequently asked questions

Is the KPI data real?: No — the dashboard uses NumPy-generated synthetic data designed to look realistic for demo and portfolio purposes. Replace the data layer with your own CSV or database connection for production use.
Can I deploy this to Streamlit Cloud?: Yes. Push to GitHub and connect via share.streamlit.io. Ensure requirements.txt lists all dependencies.
How does this compare to the LangChain Enterprise Dashboard?: The KPI dashboard is a focused BI demo. The LangChain Enterprise Dashboard is a full GenAI workbench with multi-agent routing, RAG, and MLOps tooling — see draketalley.ai/blog/langchain-enterprise-ai-workbench.
What Python version is required?: Python 3.9+ with Streamlit 1.28+. Check requirements.txt in the repository for pinned versions.