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Exclusive: Anomalo expands data quality insights to unstructured information
- Anomalo Inc. has launched a new Unstructured Data Monitoring tool to monitor unstructured data for enterprises, building on its flagship data quality platform.
- The tool helps in spotting issues within massive unstructured data volumes stored in various locations like text files and images.
- Anomalo's expertise now extends to managing unstructured data in cloud data warehouses and data lakes, ensuring trust in all data types.
- Unstructured data comprises around 80% of records in most companies, making it a significant focus area for data quality and AI.
- The tool, including Anomalo Workflows, automates the identification and correction of quality issues in unstructured data.
- It can analyze up to 100,000 documents in one operation, offering a scalable solution for handling large volumes of unstructured information.
- Anomalo aims to help companies extract insights from unstructured data and convert it into clean datasets for AI model training.
- The tool facilitates analysis of support tickets, call logs, social media comments, and more to derive meaningful insights for businesses.
- Anomalo's tool launch follows a similar move by Monte Carlo Data Inc., signaling a rapid consolidation phase in the AI and data observability markets.
- This advancement in unstructured data monitoring signifies a shift towards enhancing trust and value extraction from unstructured data for enterprises.
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