Augmented Self-Service Analytics Workflows

A technical publishing team standardizing a large PDF corpus used a dashboard to audit figure captions, replacing manual spreadsheet tracking. The interface provided automated visual distributions of caption lengths and labeling conventions. Prefix data revealed that 950 captions (99.8%) used "figure:", while just 2 (0.2%) used "fig:", instantly isolating outliers for editorial correction. The dashboard also summarized length metrics, showing a mean of 43.3 words and 323.0 characters. Two histogram bar charts detailed these distributions, with word counts peaking in the 20-29 bin and character counts peaking in the 100-199 bin. This approach to augmented data discovery enabled researchers to ensure submission-ready compliance without writing ad-hoc regex scripts.

What it shows:

Visualizing text distributions eliminates the need for manual regex scripting during editorial audits.

A portfolio analyst evaluated a potential stock swap by comparing S&P Global, MSCI, and Danaher using SEC EDGAR data. The dashboard featured metric cards displaying an OP Margin of 55.6% and ROE of 232.7% for the first company, alongside text panels detailing insights like Danaher's $19.9B revenue and MSCI's 25.5% share reduction. A revenue trajectory line chart plotted fiscal years 2009-2018, showing S&P Global fluctuating between $5B and $7B, MSCI near $1B, and Danaher at nearly $20B in 2018. This workflow demonstrates how guided analytics helps extract, clean, and visualize raw XBRL data, overcoming inconsistent tags without relying on expensive third-party data terminals.

What it shows:

Direct extraction and visualization of raw XBRL data enables independent financial analysis.