Unstructured Data Quality Management
Data Governance and Data Quality Management (DQM) are common disciplines applied to structured data within organizations. According to the Data Warehousing Institute, poor quality data costs American businesses 600 billion dollars a year, and is a leading cause of IT project failure.
Quality management initiatives for unstructured data are far less common. However, the effect of poor quality unstructured data can also be profound. In Search Technologies' experience, poor data quality is the leading cause of search project failure or underperformance.
Proven best practices are available to improve data quality and ensure that search applications meet their objectives in terms of functionality and relevance.
Specializing in search and analytics applications across unstructured, semi-structured, and structured data, we have delivered results for over 800 clients worldwide. With over 200 search and big data experts, we bring a range of unstructured data management expertise and technology assets to help clients accelerate success and reduce costs of ownership:
- Aspire content processing for unstructured data
- Connectors for a range of unstructured and structured content sources
- Query processing language for advanced query processing
- Natural language processing
Contact us to learn more about how we can help you manage and discover insights from unstructured data.
1. Data Model Design: A structured approach to researching and planning a search project which ensures a focus on data issues and directly serving user needs
2. A Document Preparation Methodology for Search: A collection of tools, techniques, and processes which prepare data for use in search-based applications