Bigdata Cookbook

Turn unstructured financial news, filings, and transcripts into investment-ready intelligence. This repository is a library of ready-to-run notebooks and workflows built on Bigdata.com—thematic screeners, sovereign and crypto analysis, credit and risk monitors, narrative miners, daily digests, and agent integrations for research teams, portfolio managers, and strategists.

Each cookbook is self-contained: open the notebook, point it at your universe or theme, and produce scores, dashboards, briefs, and reports you can share with stakeholders.

Features

• Client-ready: Self-contained projects with their own setup guides
• Fast to try: Docker or local install; many notebooks include a browsable HTML preview on GitHub
• Institutional depth: Thematic scoring, risk taxonomies, narrative summaries, and exportable reports
• Broad coverage: Equities, sovereigns, crypto, credit, macro, M&A, and sector themes
• Composable: Use one cookbook on its own or combine outputs across your research stack

Preview on GitHub

Many cookbooks include a static HTML export next to the notebook so you can browse charts and results on GitHub without running cells:

Cookbook	Preview
AI Cost Cutting	Provider vs. adopter map for AI cost-cutting narratives
AI Revenue Generation	Who is selling vs. adopting AI revenue tools
Board Management Monitoring	Leadership and board activity exposure
Credit Ratings Monitoring	Rating actions, outlooks, and timeline views
Daily Digest Central Banks	What central banks are saying, ranked by impact
Daily Digest Crude Oil	Oil-market narrative digest
Election Monitor	Corporate positioning on electoral outcomes
Liquid Cooling Market Watch	Liquid cooling providers, adopters, and ecosystem
Narrative Miners	Theme discovery and narrative ranking
Pricing Power Analysis	Pricing power signals across a company universe
Report Generator AI Threats	AI disruption risk by company
Report Generator Regulatory Issues	Regulatory exposure in tech
Report Generator Tariffs	Tariff risk and mitigation narratives
Rising Bond Spread Risks	Western Europe sovereign spillover from bond spreads
Risk Analyzer	Corporate exposure to a defined risk scenario
Screener for Crypto	Institutional adoption themes across major cryptos
Thematic Screener	Legacy thematic screener (reference)
Tracking Inflation Drivers	Inflation driver taxonomy and narrative scores

Projects

🔍 Thematic Screener CLI

Screen any theme across a company universe—in the terminal, via MCP, or in client notebooks

• Rank companies by exposure to an investment theme or derivative narrative
• Export heatmaps and scored universes for portfolio and sector work
• Example client workflows for commodity and tariff derivative screens

🔍 Thematic Screener

Classic notebook workflow for thematic identification and scoring (legacy reference; prefer Thematic Screener CLI)

• Thematic identification and categorization across multiple sectors
• Automated screening based on thematic criteria
• Theme tracking and evolution analysis
• Investment opportunity identification through thematic lenses

📊 Pricing Power Analysis

Automated Analysis of Pricing Power Narratives and Competitive Positioning

• Assesses competitive positioning across your company universe
• Provides sector-wide comparative analysis
• Tracks temporal evolution of pricing narratives
• Implements confidence scoring system for pricing power signals

🤖 AI Threats Report Generator

Automated Analysis of AI Threats and Opportunities in Technology Companies

• Evaluates AI disruption risks and proactive AI adoption
• Provides standardized scoring for cross-company comparison
• Generates investment intelligence from AI transformation narratives
• Creates structured reports ranking companies by AI resilience

⚖️ Regulatory Issues in Tech Report Generator

Automated Analysis of Regulatory Risks and Company Mitigation Strategies

• Maps sector-wide regulatory issues across technology domains
• Quantifies company-specific regulatory risks
• Extracts mitigation strategies from corporate communications
• Provides structured reporting on regulatory intensity and business impact

🎯 Risk Analyzer

Automated Risk Analysis and Assessment Tool

• Comprehensive risk assessment across multiple risk dimensions
• Quantitative risk modeling with statistical analysis
• Risk visualization and reporting capabilities
• Automated risk scoring and ranking systems

📖 Narrative Miners

Automated Narrative Analysis and Mining Tool

• Narrative extraction and pattern recognition from unstructured data
• Sentiment analysis and narrative sentiment tracking
• Narrative evolution and temporal analysis
• Automated narrative scoring and ranking systems

📈 Sentiment Pulse

Single-Ticker Company Sentiment Dashboard

• Turns one company stock ticker into a complete sentiment dashboard
• Qualitative tearsheet: executive summary, bullish and risk drivers, outlook, ranked evidence
• Quantitative sentiment time series, pressure, and abnormal media attention
• At-a-glance direction gauge (Bullish / Neutral / Bearish)
• Change the ticker and re-run for any single name

🎙️ Earnings Call Tone Analyzer

Score management tone from earnings calls at scale

• Pull the latest earnings transcripts for your coverage list
• LLM-based tone scoring with quarter-over-quarter comparability
• Portfolio-wide tone trends for idea generation and risk monitoring

📰 News Monitor (Edge MRVR)

Fresh, entity-scoped news with relevance, sentiment, and novelty scores

• Monitor breaking stories across a defined company universe
• Structured outputs ready for alerts, dashboards, or downstream research
• Enrich with full document text when you need the underlying article

👥 Board Management Monitoring

Automated Analysis of Board Member and Management Activity Exposure

• Comprehensive person tracking across multiple name variations and contexts
• Company-specific filtering ensuring relevance to monitored organizations
• Multi-mode search precision from strict entity matching to broader coverage
• Temporal analysis showing how coverage patterns evolve over time
• Entity-specific monitoring using bigdata's entity tracking capabilities

🌊 Liquid Cooling Market Watch

Automated Analysis of Liquid Cooling Technology Providers and Adopters

• Dual-role classification distinguishing technology providers from adopters
• Network analysis mapping provider-customer relationships in the cooling ecosystem
• Temporal tracking of adoption patterns and market evolution
• Market positioning analysis with confidence scoring for investment decisions
• Comprehensive ecosystem mapping for infrastructure investment intelligence

🗳️ Election Monitor

Automated Analysis of Corporate Perspectives on Electoral Outcomes

• Positive vs. negative impact assessment distinguishing companies that expect benefits from those anticipating challenges under new elected officials' policies
• Sector-wide political exposure mapping revealing industry patterns in positioning toward electoral results
• Temporal positioning tracking showing how political expectations evolve over time
• Corporate-political topic networks identifying key policy themes and company concerns through relationship analysis

📊 Credit Ratings Monitoring

Automated Detection and Analysis of Credit Rating Events

• Event detection and classification for credit rating updates, outlook changes, and watch list events
• Entity relationship mapping distinguishing between rating agencies and rated entities with validation workflows
• Multi-feature extraction capturing credit ratings, outlooks, watchlist status, debt instruments, and key drivers
• Timeline analysis generating chronological reports showing rating evolution over time
• Interactive visualizations creating HTML reports with charts for rating timeline analysis

📉 Credit Factor Analysis

Find deteriorating credit names, explain the catalysts, and draft a grounded narrative

• Rank a portfolio or sector on credit-news sentiment
• Drill into the names that moved and see event-type drivers
• Pull supporting news and synthesize an analyst-ready credit story

💰 AI Cost Cutting Market Analysis

Automated Analysis of AI Cost Cutting Providers and Users

• Dual-role classification distinguishing companies developing AI cost cutting solutions from those implementing them
• Technology ecosystem mapping revealing relationships between solution providers and corporate users
• Adoption timeline tracking showing how AI cost cutting implementation evolves across different sectors
• Market positioning analysis quantifying each company's role and exposure in the AI cost cutting ecosystem

📈 AI Revenue Generation Market Analysis

Automated Analysis of AI Revenue Generation Providers and Users

• Dual-role classification distinguishing companies developing AI revenue generation solutions from those implementing them
• Technology ecosystem mapping revealing relationships between solution providers and corporate users
• Adoption timeline tracking showing how AI revenue generation implementation evolves across different companies
• Market positioning analysis quantifying each company's role and exposure in the AI revenue generation ecosystem

📊 Tracking Inflation Drivers

Automated Macroeconomic Inflation Analysis Tool

• Automated theme breakdown into specific inflation components and drivers
• Systematic document analysis using embeddings-based search and classification
• Economic categorization that turns narrative signals into structured insights
• Comprehensive reporting with analytical summaries for each inflation driver covering demand-pull, cost-push, wage increases, global factors, and monetary policy impacts

🏦 Daily Digest Central Banks

Automated Central Bank Announcements Monitoring and Analysis Tool

• Lexicon generation of monetary policy and central bank-specific terminology
• Real-time content retrieval via Bigdata API with parallelized keyword searches
• Topic clustering and selection with AI-powered verification and ranking
• Custom report generation with configurable ranking systems for trending topics
• Market impact assessment scoring topics for trendiness, novelty, and magnitude

🛢️ Daily Digest Crude Oil

Automated Crude Oil Market Monitoring and Analysis Tool

• Lexicon generation of crude oil industry-specific terminology and jargon
• Real-time content retrieval via Bigdata API with parallelized keyword searches
• Topic clustering and selection with AI-powered verification and ranking
• Custom report generation with configurable ranking systems for trending topics
• Market impact assessment scoring topics for trendiness, novelty, and magnitude

📋 Large-Scale Portfolio Briefs Generation

Automated Brief Generation for Large Company Portfolios

• Batch processing for hundreds or thousands of companies in configurable batches
• CSV-based input for easy portfolio management
• Customizable topics and research questions tailored to analysis needs
• Progress tracking with status polling and error handling
• Multiple export formats including JSON and Excel for further analysis
• Source attribution with full metadata including URLs, headlines, and publication dates

☀️ Morning Brief

Start the day with a portfolio morning brief across five research lenses

• Earnings and guidance, macro and policy, analyst sentiment, M&A and corporate actions, supply chain and operations
• One command produces shareable Markdown and HTML briefs with sourced evidence
• Built for PM morning meetings, sector pods, and coverage-team standups

🧾 Specialized Report Tariffs

Automated Analysis of Trade Tariff Risks and Corporate Mitigation Strategies

• Generates sector-wide and company-specific risk reports
• Extracts mitigation plans from SEC filings and earnings transcripts
• Produces executive and detailed HTML reports
• Exports structured CSVs for further analysis

📉 Rising Bond Spread Risks

Quantify sovereign spillover risk as Western European bond spreads widen

• Score Western European countries on bond-spillover and contagion narratives
• Compare relative exposure across the region with standardized risk metrics
• Rolling sentiment, volume spikes, and AI-written peak-risk narratives per country
• Interactive country dashboards for committee packs and sovereign research

🪙 Screener for Crypto

Identify cryptocurrencies aligned with institutional adoption before the crowd

• Screen major digital assets against institutional adoption themes (KYC/AML, custody, regulation, enterprise use)
• Rank cryptos by thematic exposure with heatmaps and composite scores
• Purpose-built for crypto wire intelligence and early trend detection
• Interactive visualizations for portfolio and research presentations

🔧 Build Your Own MCP

Connect Bigdata.com research workflows to Cursor, Claude, and other MCP clients

• Expose search and screening as tools your AI assistant can call
• Example grounded dashboards and HTML assets for client-ready deliverables
• A starting point for custom agent and automation workflows

📌 MCP Dashboard Demo

Illustration: MCP-grounded dashboard (frozen snapshot)

• React + Vite demo: typed GROUNDED_DATA in src/dashboard.jsx populated via Bigdata.com MCP (market tearsheet, search, country tearsheets)—no in-browser API
• Shows source-attributed panels (Iran–Gulf example); cookbook copy frozen 2026-03-18; deploy and live refresh live in a separate production repo
• Example GitHub Actions and Fly.io workflows are reference-only under MCP_Dashboard_Demo/docs/reference-workflows/ (not active CI here)

🔬 Research Agent Sync Response

Python Client for Research Agent API with Citation Support

• Simple synchronous interface wrapping the Research Agent streaming API
• Bigdata.com standard citation format with full source metadata
• Inline citation markers [1], [2] with numbered reference lists
• Multiple output formats: plain answer, citations JSON, or combined results
• Follow-up conversation support with chat ID continuation
• Configurable research effort levels (lite/standard) for speed vs. depth tradeoff

🤖 Agent to Bigdata

Modular Framework for Building AI Agents with Bigdata.com Integration

• Multi-source AI agent integrating Bigdata.com Search, Knowledge Graph, and Research Agent APIs
• Internal data integration with SQLite databases and FAISS vector stores
• Hierarchical agent architecture with smart tool routing (internal-first, external escalation)
• LangSmith observability for production monitoring and tracing
• Reusable core module for building custom agent workflows
• Citation support with inline markers and numbered references

🤖 Google ADK with Bigdata and local data

Standalone Google ADK agent with SQLite, local Markdown research files (FAISS + Gemini embeddings), and Bigdata.com MCP

• Multi-source AI agent integrating Bigdata.com Search, Knowledge Graph, and Research Agent APIs
• Internal data integration with SQLite databases and FAISS vector stores
• Citation support with inline markers and numbered references

🧱 Databricks Agent to Bigdata

Financial-intelligence agent on Databricks combining internal lakehouse data with Bigdata.com over MCP

• One Mosaic AI agent over three sources: internal structured (Unity Catalog SQL functions + AI/BI Genie), internal unstructured (Vector Search), and external real-time (Bigdata.com MCP)
• Model Context Protocol integration with automatic tool discovery — governed via Unity AI Gateway MCP Services, or a direct connection
• Built on the latest Databricks agent stack: Mosaic AI Agent Framework, MLflow ChatAgent, LangGraph, Databricks-hosted Claude
• End-to-end: Unity Catalog setup → Vector Search → MCP → deploy to Model Serving with the AI Playground / Review App
• Cited, cross-source answers separating proprietary signal from public market intelligence

❄️ Snowflake Agent to Bigdata

Snowflake Intelligence demo combining live Snowflake data with Bigdata.com MCP

• Cortex Agent (SNOWFLAKE_BIGDATA_AGENT) over portfolio SQL, internal research search, and Bigdata.com MCP tools
• Search financial news and filings, resolve securities, and pull company tearsheets from one chat UI
• End-to-end Snowflake setup guide: External Access Integration, MCP connector, demo data, and agent deployment

🔍 Large Scale Search

High-Performance Portfolio Search Tool

• Entity resolution with CSV caching for ticker-to-entity ID mapping
• Parallel processing with ThreadPoolExecutor for searching hundreds of tickers
• Multi-layered rate limiting (sliding window + concurrency semaphore + auto-retry)
• SQLite storage with indexed queries for fast result retrieval
• Customizable research topics with company name placeholders
• Query interface to filter results by ticker, topic, or custom criteria

📊 Index M&A Activity Report

Automated M&A Analysis and Report Generation Tool

• M&A news search for specified tickers using Bigdata.com API
• AI-powered executive briefs summarizing key M&A developments
• Structured deal analysis tables identifying acquisition targets
• Desk notes per ticker with source attribution
• Automated report generation with deal tables, summaries, and source links

📦 Smart Batching

Run thematic search across thousands of companies efficiently

• Intelligent query planning that groups similar companies and themes
• Large-universe execution with parallel search and robust retries
• Proportional sampling so results stay representative at scale
• Reusable search plans for recurring screens and monitors

🔍 Batch Search API

One batch job to search an entire universe asynchronously

• Submit all queries in a single job and receive one consolidated result file
• Entity-level scores and volumes for ranking and heatmaps
• Optional sector–country views for macro-style screens

📚 Bigdata.com API Examples

Notebook and script examples for key Bigdata.com APIs

• Five notebook examples: Search, Volume, Knowledge Graph, Co-mentions, and an end-to-end workflow example
• Client-ready script library: Sample_Scripts — full folder catalog, quickstart, and step-by-step workflow patterns are in API_Tutorials/Sample_Scripts/README.md
• Standardized auth via BIGDATA_API_KEY loaded from .env
• Progressive path from API fundamentals to workflow-level signal construction
• Designed as a practical onboarding and execution path for teams integrating Bigdata.com APIs

Quick Start

Prerequisites

For Docker Installation

• Docker installed on your system
• Bigdata API access
• OpenAI API key (for advanced features)

For Local Installation

• Python 3.11+ recommended
• uv package manager
• Bigdata.com and OpenAI API keys (see each project's .env.example)

Clone repository

Clone the repository to your local computer. Please follow the below steps:

• Navigate your local computer to the folder where you want to clone the repo and run the following command:

git clone https://github.com/Bigdata-com/bigdata-cookbook.git

Installation

Each project supports both Docker and local installation methods:

• Docker Installation: Each project includes a Dockerfile for containerized deployment
• Local Installation: Traditional installation using Python and uv package manager

Each project has its own detailed README with specific installation and usage instructions for both methods.

Project Structure

bigdata-cookbook/
├── Pricing_Power_Analysis/                          # Pricing power analysis
│   ├── Pricing Power.ipynb
│   ├── Pricing Power.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Report_Generator_AI_Threats/                      # AI risk analysis
│   ├── Report Generator_ AI Disruption Risk.ipynb
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Report_Generator_Regulatory_Issues_in_Tech/        # Regulatory analysis
│   ├── Report Generator_ Regulatory Issues.ipynb
│   ├── Report Generator_ Regulatory Issues.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Risk_Analyzer/                                    # Risk analysis tool
│   ├── Risk_Analyzer.ipynb
│   ├── Risk_Analyzer.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Thematic_Screener_CLI/                            # Thematic screener CLI + MCP (REST)
│   ├── notebooks/
│   ├── src/
│   ├── pyproject.toml
│   └── README.md
├── Thematic_Screener/                                # Deprecated SDK notebook
│   ├── ThematicScreener.ipynb
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Narrative_Miners/                                 # Narrative analysis tool
│   ├── NarrativeMiner.ipynb
│   ├── NarrativeMiner.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Sentiment_Pulse/                                  # Single-ticker sentiment dashboard
│   ├── company_sentiment_dashboard.ipynb
│   ├── requirements.txt
│   └── README.md
├── Earnings_Call_Tone_Analyzer/                      # Earnings call tone scoring CLI
│   ├── pyproject.toml
│   └── README.md
├── News_Monitor_MAS/                                 # Edge MRVR news monitor
│   ├── pyproject.toml
│   └── README.md
├── Board_Management_Monitoring/                      # Board monitoring tool
│   ├── Board_Management_Monitoring.ipynb
│   ├── Board_Management_Monitoring.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Liquid_Cooling_Market_Watch/                      # Liquid cooling analysis
│   ├── Liquid_Cooling_Market_Watch.ipynb
│   ├── Liquid_Cooling_Market_Watch.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Election_Monitor/                                 # Election monitoring tool
│   ├── Trump_Reelection_Impact_Analysis.ipynb
│   ├── Trump_Reelection_Impact_Analysis.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Credit_Ratings_Monitoring/                       # Credit rating event monitoring
│   ├── Credit_Ratings_Monitoring.ipynb
│   ├── Credit_Ratings_Monitoring.html
│   ├── report/
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Credit_Factor_Analysis/                          # Credit-news factor screen + narrative
│   ├── Credit_Factor_Analysis.ipynb
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── AI_Cost_Cutting_Market_Analysis/                # AI cost cutting analysis
│   ├── AI_Cost_Cutting_Market_Analysis.ipynb
│   ├── AI_Cost_Cutting_Market_Analysis.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── AI_Revenue_Generation_Market_Analysis/          # AI revenue generation analysis
│   ├── AI_Revenue_Generation_Market_Analysis.ipynb
│   ├── AI_Revenue_Generation_Market_Analysis.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Tracking_Inflation_Drivers/                     # Inflation analysis tool
│   ├── Tracking_Inflation_Drivers.ipynb
│   ├── Tracking_Inflation_Drivers.html
│   ├── src/
│   ├── requirements.txt
│   └── README.md
├── Daily_Digest_Central_Banks/                      # Central bank monitoring
│   ├── Daily_Digest_Central_Banks.ipynb
│   ├── Daily_Digest_Central_Banks.html
│   ├── src/
│   ├── assets/
│   ├── report/
│   ├── requirements.txt
│   ├── Dockerfile
│   └── README.md
├── Daily_Digest_Crude_Oil/                          # Crude oil market analysis
│   ├── Daily_Digest_Crude_Oil.ipynb
│   ├── Daily_Digest_Crude_Oil.html
│   ├── src/
│   ├── assets/
│   ├── report/
│   ├── requirements.txt
│   ├── Dockerfile
│   └── README.md
├── Briefs_Generation_Large_Scale/                    # Large-scale portfolio briefs generation
│   ├── portfolio_briefs_generation.ipynb
│   ├── static/
│   │   └── data/
│   ├── requirements.txt
│   └── README.md
├── morning_brief_cli/                               # Portfolio morning brief generator
│   ├── pyproject.toml
│   └── README.md
├── Report_Generator_Specialized_Report_Tariffs/      # Tariffs risk report generator
│   ├── Report_Generator_Specialized_Report_Tariffs.ipynb
│   ├── Report_Generator_Specialized_Report_Tariffs.html
│   ├── src/
│   ├── requirements.txt
│   ├── Dockerfile
│   └── README.md
├── Rising_Bond_Spread_Risks/                        # Bond spread spillover analysis
│   ├── Rising_Bond_Spread_Risks.ipynb
│   ├── Rising_Bond_Spread_Risks.html
│   ├── data/western_europe_countries_banks.csv
│   ├── src/
│   ├── requirements.txt
│   ├── Dockerfile
│   ├── .dockerignore
│   └── README.md
├── Screener_for_Crypto/                             # Cryptocurrency thematic screening
│   ├── Screener_for_Crypto.ipynb
│   ├── Screener_for_Crypto.html
│   ├── data/top_15_cryptos.csv
│   ├── src/
│   ├── requirements.txt
│   ├── Dockerfile
│   ├── .dockerignore
│   └── README.md
├── Build_Your_Own_MCP/                              # MCP server integration
│   ├── build_your_mcp.py
│   ├── assets/
│   ├── Dockerfile
│   └── README.md
├── MCP_Dashboard_Demo/                            # MCP-grounded dashboard illustration (frozen snapshot)
│   ├── src/
│   ├── docs/reference-workflows/
│   ├── Dockerfile
│   └── README.md
├── Research_Agent_Sync_Response/                    # Research Agent API client
│   ├── research_client_usage.ipynb
│   ├── research_client.py
│   ├── output/
│   └── README.md
├── Agent_To_Bigdata/                                # AI agent framework with Bigdata.com integration
│   ├── agent_to_research_agent.ipynb
│   ├── agent_to_search.ipynb
│   ├── langgraph_core.py
│   ├── research_client.py
│   ├── requirements.txt
│   ├── static/
│   └── README.md
├── Google_ADK_With_BigData/                         # Google ADK + Bigdata + local FAISS demo
│   └── README.md
├── Databricks_Agent_To_Bigdata/                     # Databricks + Bigdata MCP agent
│   └── README.md
├── Snowflake_Agent_To_Bigdata/                      # Snowflake Intelligence + Bigdata MCP demo
│   └── README.md
├── Search_Large_Scale/                              # Large-scale portfolio search
│   ├── large_search.ipynb
│   ├── output/
│   └── README.md
├── Index_MA_Activity_Report/                        # M&A activity report generation
│   ├── index_ma_report.ipynb
│   ├── config/
│   ├── services/
│   ├── requirements.txt
│   └── README.md
├── Smart_Batching/                                  # Optimized query planning
│   ├── ...
│   └── README.md
├── Batch_Search_API/                                # Batch Search API — one job for thousands of queries
│   ├── Batch_Search_API.ipynb
│   ├── src/
│   ├── data/
│   ├── requirements.txt
│   └── README.md
├── API_Tutorials/                                   # Bigdata.com API examples bundle
│   ├── Search_API/
│   ├── Volume_API/
│   ├── Knowledge_Graph_API/
│   ├── CoMentions_API/
│   ├── Workflow_example/
│   ├── Sample_Scripts/
│   └── README.md
└── README.md                                        # This file

Requirements

Each project lists its own dependencies in requirements.txt or pyproject.toml. Setup details and credentials are in every project README.

Usage

Typical flow across cookbooks:

1. Choose a workflow that matches your question (theme, risk, credit, macro, etc.)
2. Configure your universe, dates, and theme in the notebook
3. Run the pipeline to retrieve, label, and score unstructured content
4. Share Excel, CSV, HTML, or dashboard outputs with your team

Support

• Each project has its own detailed README with specific instructions
• Check the individual project documentation for troubleshooting
• Ensure you have valid Bigdata API credentials before running analyses

License

This project is licensed under the terms specified in the LICENSE file.

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Note: This repository contains financial analysis tools. Please ensure compliance with relevant regulations and use appropriate risk management practices when making investment decisions based on these analyses.