Digitizing Unstructured Data Enterprise-Wide
A New Approach to Creating Seamless Data Streams across the Enterprise
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Unstructured data including images, handwriting, signatures, and mobile content pose a challenge to capturing and digitizing data. Organizations need analytics-based insights to evolve in today’s markets, but automation is only effective if it can obtain structured, digitized data and most is neither.
Unstructured data is difficult to analyze because it cannot be processed with rules, is in a natural language, has limited/no structure or metadata, and can include nontext-based materials.
This report covers why unstructured data is such a crucial resource to enterprise transformation and how it can be consolidated across different silos with an array of tools for both better management and long-term automation enablement.
It includes:
- The state of play: why is data such a challenge for organizations?
- The current solution universe and how data can be digitized with CMR, RPA and OCR
- A case study that looks at how one of the oldest and largest US-based financial institutions was able to digitize and process 170K+ loan applications during COVID for a 90% accuracy rate
- Insights from Robert Garagiola, Senior Director for Global Enterprise Data with James Hardie
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