Designed an application that enables users to seamlessly upload headless documents, Excel sheets, or text files, and leverages Robotic Process Automation (RPA) to automatically format data and generate intelligent recommendations.
Designed an application that allows users to easily upload multiple file types and leverages Robotic Process Automation (RPA) to:
Automatically clean and format raw data
Standardize file structures for consistency
Provide intelligent recommendations based on the processed data
The intuitive interface guides users through the upload process and gives real-time feedback, making complex automation accessible to non-technical users.
Significant Time Savings
Automates repetitive data-mapping tasks, reducing processing time by up to 70%.
Enhanced Data Quality and Consistency
Reduces manual errors, ensuring reliable outputs that are ready for downstream systems.
Increased Scalability
Allows teams to handle large datasets and frequent uploads without increasing headcount.
Boosted User Productivity
Frees users from manual formatting so they can focus on analysis and decision-making.
Higher Adoption and Satisfaction
The clean, intuitive interface encourages wider adoption among both technical and non-technical users.
Displaying incomplete or inconsistent data:
One challenge was how to display partial or missing data without confusing users or causing them to make incorrect assumptions. We addressed this with clear placeholders, distinct status icons, and progressive disclosure to reveal details only when needed.
Building trust in automation recommendations:
Users needed to understand why a field was recommended for mapping and still feel in control of the process. To address this, we included transparent explanation tooltips, color-coded statuses (mapped, suggested, unmapped), and simple approve/reject actions to reinforce confidence in the system.
Visual clarity with complex datasets:
Managing large volumes of data required a layout that could accommodate multiple data types while remaining easy to scan. The split-screen approach (configuration on the left, data visualization on the right) allowed users to focus on one context at a time while still seeing how their actions impacted the dataset in real-time.
Left Side: Benefits
• Streamlined uploads: Supports text, Excel, and headless documents with configurable separators and formats.
• Automated mapping: RPA suggests column mappings based on prior data sets.
• Real-time validation: Flags invalid data, unmapped fields, and inconsistencies before processing.
• User-friendly interface: Clear indicators (mapped/unmapped/suggested) and previews reduce user errors.
• Global flexibility: Supports different regional data formats and file structures.
Right Side: Impact (with metrics)
• 70% reduction in processing time by eliminating manual data formatting.
• Near-zero data errors through automated validation and standardized mapping.
• Scalable for large datasets without additional staffing.
• Boosted user adoption among both technical and non-technical users.
• Improved confidence in data integrity, accelerating downstream decision-making.
To further enhance usability, KPI indicators were integrated at the top of the interface. These KPIs surface critical insights—such as unmapped fields, invalid data points, or suggested mappings—helping users quickly identify and resolve issues during the import process.