Today’s digital landscape requires companies to synthesize classical information governance strategies with effective and user-friendly technologies to tackle the increased challenges posed by the ever-increasing volume of unstructured data in a more scalable and accurate manner.
To meet this need, organizations are increasingly leveraging advanced text analytics and AI technologies to improve their ability to inventory and classify data effectively.
Here are three information governance use cases illustrating how these technologies are employed and why they are important:
Use Case 1: Health Records
A hospital needs to comply with privacy regulations including HIPAA and similar state laws. Practically, this means that it needs to effectively eliminate terabytes of personal information regarding potential patients, that it no longer needs.
It also means that the hospital must be able to keep and find the right information. Using advanced text analytics and AI, the hospital can scan its vast data repositories to identify and classify sensitive information, such as personally identifiable information (PII) or health records.
This then allows the hospital to develop a comprehensive inventory of sensitive data that is subject to applicable privacy regulations and to properly protect that information.
Use Case 2: E-Discovery and Legal Compliance:
A law firm is defending a major client against a class action proceeding that requires it to search through hundreds of thousands of pages of detailed environmental surveys and other similarly complex documents. Using tools such as text analytics and keyword classification, the law firm can sift through large volumes of this unstructured much more effectively than the old method of simply having junior associates and document review attorneys review the records manually.
This combination of classic information governance strategies that are fueled by AI and other technologies can save clients millions of dollars in legal fees, and while this may not be a short-term goal for the law firm, it must be part of their long-term competitive strategy.
Use Case 3: Content Categorization and Data Retrieval
A large music publisher holds vast volumes of unstructured data, such as documents, images, and videos, which it seeks to make available for both its staff and external users of its various services.
To sift through and categorize this data, the company deploys tools such as advanced text analytics and AI to automatically categorize and tag content based on themes, topics, or sentiment. This allows potential users of its products and systems to locate and retrieve relevant information quickly and effectively and improves customer loyalty. Further, on an internal level, it improves the company’s decision-making processes, improves overall productivity, and reduces worker frustration.
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