"Google-like" natural search to deliver instant answers for everyone
Orchestration of AI models to surface no-nonsense insights that are actionable
"YouTube-like" audio-visual storytelling for better data consumption
Clear visibility of data quality as an index that is constantly measured across key dimensions. We assist in enhancing data observability with the intent to enrich the quality of your analytics.
View your data quality index on a scale at attribute, entity and workspace level, and understand it as clearly as an air quality index.
Conduct objective data quality assessments and configure custom rules in a user-friendly way to ensure high quality data for analytics.
Observe data quality across 8 key dimensions in real time, control issues effectively, and fix them promptly for timely accurate insights.
Save time identifying and troubleshooting issues with data quality scores and actionable findings to enrich data on an on-going basis.
Gain visibility of data quality measured across 8 dimensions – clarity, completeness, consistency, integrity, interpretability, timeliness and uniqueness.
Assess quality at granular levels of workspace, entities and attributes, with full visibility of issues and transparency of applied rules, without black box approaches.
Get curated ready-for-analysis data with comprehensive rules and algorithms applied automatically without writing a single line of code.
Use actionable findings and "Fix It" suggestions on data quality to instantly locate specific instances and get a snapshot report on data quality at no extra cost.
Improve analytics workflow by making only the required entities or attributes searchable, reducing data noise, and saving time and effort at data store level.
Keep data reliable and accessible with data quality reports delivered in minutes, instead of multi-year timeframes offered by legacy solutions.
Increase user satisfaction, adoption and ROI of search analytics by avoiding inferior quality attributes and ensuring high precision insights
Build trust in data and improve output of AI models by controlling attributes based on data quality and preventing spurious and questionable artifacts.
Improve productivity and efficiency of business users by empowering them with high quality data and timely actionable insights.