Classify
Emotion Analysis
Leveraging Customer Feedback through Text Analysis
Text Analytics for Understanding Market Trends
Data Governance for Compliance and Security
Exploring Customer Segmentation Through Data Analysis
Data Classification Governance
Quality
Text Classification Techniques for Business Use 
Rule-Based Classification Involves using a set of predefined rules to
classify text
...
Emotion Analysis Machine Learning Approach In this approach, algorithms are trained on labeled datasets to
classify text based on the emotions conveyed
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Leveraging Customer Feedback through Text Analysis techniques can be applied: Machine Learning Algorithms: Techniques such as supervised and unsupervised learning can
classify and cluster feedback
...
Text Analytics for Understanding Market Trends Named Entity Recognition (NER) A technique to identify and
classify key entities in text into predefined categories such as names, organizations, locations, etc
...
Data Governance for Compliance and Security Industry Data Security Standard (PCI DSS) A robust data governance framework helps organizations to: Identify and
classify sensitive data
...
Exploring Customer Segmentation Through Data Analysis Decision Trees: A visual representation of decision-making processes that can help
classify customers into segments
...
Data Classification Governance Classification Criteria Defined criteria for
classifying data based on sensitivity, regulatory requirements, and business value
...
Quality Entity Recognition The ability to accurately identify and
classify key entities (e
...
Data Governance Policies for Cloud Environments Implement Data Classification:
Classify data based on its sensitivity and importance to determine appropriate handling procedures
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Techniques 1 Supervised Learning In supervised learning, algorithms learn from labeled data, allowing them to make predictions or
classify new data points
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