The ability to gather data at scale, clean it, standardise it, and enrich it with domain knowledge serves as a crucial differentiation for business information providers. For data curation, enrichment, and transformation into insights and action, it is essential to have subject-matter expertise.
These unstructured data sources are typically where these raw datasets must be gathered, collected, or extracted. Examples of common data sources include directories, product catalogues, internal papers, photos, and videos as well as websites, government registrations, regulatory agencies, and regulatory bodies. Unstructured data can offer considerable competitive benefits and deliver actionable insights if managed successfully, but firms today struggle to manage it.
- Publisher-specific pre-editing frameworks support extensive customization of normalization requirements, bringing together technology expertise and in-depth knowledge in content structure
- Automated house style– and style manual–based rules that deliver accuracy during technical editing
- Extensive reference style repositories for bibliography structuring, from APA and CMS to author’s style.
- Copyediting skill sets across domains, from medical to legal, delivering simple to complex levels of content editing
- Deep subject-level and language skill sets delivering simple to intensive levels of language editing
- Skills in alternative text creation, spanning a wide range of subject specialization and capturing the essence of display elements across all ranges of complexities – from simple images to complex graphs, chemical equations, and mathematical concepts
Work Challenges
Web Extraction Solutions
Current web extraction solutions struggle to keep up with more complex websites and security restrictions such as captcha, making collection sub-optimal.
Relevant data
Extraction of relevant data points from text-based documents is manual and time-consuming.
Data become outdated
Data become outdated quickly, requiring continuous monitoring to check for currency.