Mine Messy Unstructured Text Data
Using Your Business Language
Turn Raw Text Into Insights You Can Act On
Our patented domain-specific approach complements bug data applications in AI,
Machine Learning, RPA, business intelligence, research, talent matching and
other downstream systems. It drastically reduces the time it takes to curate,
search, filter, match, label, tag and route heterogeneous textual content.
“Algorithms will be more effective in the long run if they are embedded in a tool like DataScava, which provides a comprehensive knowledge framework that includes user-controlled domain-specific ontologies, statistical analysis and rule-based reasoning strategies.”
– Scott Spangler, Chief Data Scientist and IBM Distinguished Engineer
It’s for Data Professionals, Business People and Programmers
Make raw text data more accessible and actionable with user-defined topics that produce precise results you can see, control and measure.
Mine data 24/7 from databases, subscription-based feeds, emails and other sources based on content, intent and your areas of interests.
Get the most out of your unstructured data so you can make better business decisions while keeping the humans in command.
Ease of use and transparency enables collaboration between non-technical and technical people, providing and a rapid path to efficiency.
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7 Ways Text Mining with DataScava is Different
- It uses Domain-Specific Language Processing (DSLP) and Weighted Topic Scoring (WTS).
- Ensures data quality is high to reduce the risk of suggested actions.
- Works top-down through your entire corpus at the file level, not at the sentence level.
- Measures raw text, highlights content in on-topic files and eliminates irrelevant ones.
- Summarizes textual content in a usable, numerical form for routing or to trigger an action.
- It doesn’t infer what you’re looking for, it finds what you ARE looking for.
- Encapsulates your business language, jargon and acronyms in your software.
Surface Relevant Information Faster
Domain-Specific Language Processing and Weighted Topic Scoring work as an alternative or adjunct to Natural Language Processing.
DataScava mines your data around the clock and continually refines its capabilities in a measurable way at the direction of users