Big Data Analysis
It precisely processes the vast media data collected in Monitor Wizard and analyzes mention trends and related keywords from multiple angles.
Going beyond simple quantitative statistics, it visualizes issue changes by period and mention trends by media type so you can objectively diagnose where your business stands in the market.
By providing quantified indicators for competitor share comparisons and key-keyword ownership, it supports strategic PR and marketing direction grounded in data.
Systematic Integrated Data Management Based on Medallion Architecture
Using Medallion Architecture, which layers data by quality, it systematically manages more than 1,300 tables and over 600 GB of source data by integrating them from Bronze to Silver layers.
This guarantees source-data immutability while creating high-purity datasets optimized for analysis and AI processing, providing the most reliable foundation for business decision-making.
A Multilingual NLP Pipeline Powered by High-Performance Parallel Processing
By combining a Spark-based distributed processing engine with Kiwipiepy and Elasticsearch, it processes large-scale media data in real time through more than 15 stages of preprocessing.
This completely removes complex noise such as promotional phrases, special symbols, and unnecessary whitespace from news body text, helping teams capture the true issues surrounding their company and clearer market signals hidden in massive information flows.
Precise Core-Keyword Extraction with a Multi-Stage Algorithm
By applying a multi-stage algorithm that combines TF-IDF, entropy scoring, and the Elbow Selection method, it mathematically distinguishes keyword discrimination and document specificity with precision.
Rather than surfacing only frequent words, it scientifically selects the truly meaningful keywords that cut through the essence of an issue, allowing users to understand core market flows and reputation changes at a glance without reading massive numbers of articles one by one.
A High-Performance Analytics Environment Through Incremental Loads and Optimized Formats
By adopting watermark-based incremental loading and the Snappy-compressed Parquet format, it maximizes system-resource efficiency and query speed even in large-scale data environments.
It maintains a stable analytics environment without performance degradation even when more than 200,000 records flow in daily on average, enabling immediate and agile strategy building through low-latency real-time intelligence.