Agent skill · data analytics · datadrivenconstruction
big-data-analysis
Analyze large-scale construction datasets. Process thousands of projects for patterns, benchmarks, and predictive insights.
Why this skill is useful
Provides domain-specific patterns and benchmarks for analyzing construction datasets that the AI wouldn't reliably generate on its own.
What it needs
Requires python3 installed locally. About 5k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
Big Data Analysis Business Case Problem Statement Large-scale data analysis challenges: Processing millions of records Cross-project benchmarking Pattern recognition at scale Memory and performance constraints Solution Scalable big data analysis framework for construction data using efficient data structures and parallel processing patterns. Technical Implementation Quick Start Common Use Cases 1. Find Anomalies 2. Trend Analysis 3. Project Ranking 4. Segment Analysis Resources DDC Book: Chapter 4.4 - Modern Data Technologies Apache Parquet: https://parquet.apache.org/ Website: https://datadrivenconstruction.io
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/big-data-analysis