Unstructured Data refers to information that does not follow a pre-defined data model or organized format, making it difficult to collect, process, or analyze using traditional tools. It is typically found in formats that are rich in content but lack standardized structures.
Examples of this include:
- Text-based content such as emails, social media posts, or documents
- Multimedia files like audio, video, and images
- Data generated from sensors, logs, or customer interactions
Organizations often must deal with unstructured data to uncover insights, monitor trends, and support more informed decision-making. Because this data type is often high in volume and varied in form, it also requires specialized software and analytical approaches to extract value from it.
Unstructured data plays a critical role in driving innovation, particularly in areas like artificial intelligence, customer experience, and predictive analytics. Its potential lies not in its organization, but in how effectively it can be interpreted and applied across business functions.
Data Driven Decisions for Effective Future Planning
Case Study
Automotive: Cross-incentive consolidation empowers program success
A large vehicle manufacturer were looking to consolidate their dealer Co-Op/MDF, Rebates and SPIFFs incentives and work together to influence dealer channel behavior.
By accumulating incentives into one branded platform, enabled the manufacturer to have clearer visibility of claim submissions, engagement and activity reporting, through the analytics.
Learn how 360insights helps this manufacturer understand how measuring the data provides a better attribution of direct program ROI.