Text and Sentiment Analytics for Smarter Business Intelligence Decisions Training Course

Introduction

In the era of digital transformation, text and sentiment analysis has emerged as one of the most powerful techniques for unlocking hidden insights from unstructured data. Organizations are flooded with textual content from customer reviews, social media, surveys, and corporate communications. By applying text mining and sentiment analysis, businesses can measure public perception, identify trends, and gain actionable intelligence that drives competitive advantage.

This training course is designed to equip professionals with the essential skills to analyze large volumes of text and extract meaningful business insights. Participants will learn techniques for natural language processing (NLP), sentiment classification, opinion mining, and the integration of sentiment-driven insights into business intelligence dashboards. By the end of the course, learners will have the expertise to transform raw text into valuable intelligence for strategic decision-making.

Duration: 10 Days

Target Audience

  • Business intelligence professionals and analysts
  • Data scientists and NLP practitioners
  • Marketing and customer experience teams
  • Risk management and compliance officers
  • Professionals seeking to expand BI capabilities with text analytics

10 Objectives

  1. Understand the fundamentals of text and sentiment analysis in BI
  2. Learn the role of natural language processing in extracting insights
  3. Explore text mining methods for business applications
  4. Apply sentiment analysis techniques to real-world datasets
  5. Classify and interpret customer opinions and feedback
  6. Integrate text analytics into BI dashboards and reports
  7. Use modern tools and platforms for sentiment analysis
  8. Recognize challenges in text analytics, including bias and ambiguity
  9. Enhance decision-making with sentiment-driven intelligence
  10. Explore future applications of text analytics in business contexts

15 Course Modules

Module 1: Introduction to Text and Sentiment Analysis

  • Importance in business intelligence
  • Applications across industries
  • Structured vs. unstructured data
  • Key challenges in text analysis
  • Overview of course structure

Module 2: Fundamentals of Natural Language Processing (NLP)

  • Tokenization and lemmatization
  • Stop-word removal
  • Part-of-speech tagging
  • Named entity recognition
  • Text preprocessing pipelines

Module 3: Text Mining Techniques for BI

  • Keyword extraction
  • Topic modeling basics
  • Frequency and co-occurrence analysis
  • Clustering text data
  • Business applications of text mining

Module 4: Introduction to Sentiment Analysis

  • Definition and approaches
  • Rule-based vs. machine learning methods
  • Polarity and subjectivity detection
  • Sentiment lexicons and dictionaries
  • Applications in customer feedback analysis

Module 5: Machine Learning for Sentiment Classification

  • Supervised learning models for sentiment
  • Feature engineering from text
  • Training and evaluating sentiment models
  • Handling imbalanced datasets
  • Case studies of sentiment classification

Module 6: Deep Learning for Text and Sentiment

  • Neural networks for NLP
  • Word embeddings and representation models
  • Recurrent neural networks (RNNs)
  • Transformer-based models (BERT, GPT)
  • Practical examples in BI

Module 7: Opinion Mining and Customer Feedback

  • Extracting customer opinions from reviews
  • Identifying satisfaction and dissatisfaction drivers
  • Sentiment trend analysis
  • Linking opinions to business outcomes
  • Use cases in marketing and product design

Module 8: Social Media Sentiment Analytics

  • Monitoring platforms like Twitter, Facebook, LinkedIn
  • Hashtag and keyword tracking
  • Real-time sentiment monitoring
  • Crisis detection and brand reputation management
  • Social media dashboards

Module 9: Text Analytics for Risk and Compliance

  • Identifying fraudulent activities in text
  • Monitoring compliance reports and documentation
  • Sentiment in financial disclosures
  • Early warning signals from text data
  • Regulatory applications

Module 10: Visualization of Text and Sentiment Data

  • Word clouds and keyword maps
  • Sentiment scoring charts
  • Heatmaps and trend lines
  • Integrating visualizations into BI dashboards
  • Effective storytelling with text data

Module 11: Tools and Platforms for Text Analytics

  • Python libraries (NLTK, spaCy, TextBlob)
  • Sentiment analysis APIs and cloud tools
  • Power BI and Tableau integrations
  • Open-source vs. enterprise solutions
  • Selection of tools for business use

Module 12: Model Evaluation and Validation

  • Accuracy and precision in sentiment analysis
  • Confusion matrix interpretation
  • Cross-validation techniques
  • Avoiding overfitting in text models
  • Best practices for robust analysis

Module 13: Challenges in Text and Sentiment Analysis

  • Ambiguity and sarcasm in text
  • Language and cultural differences
  • Handling noisy or unstructured data
  • Bias in NLP models
  • Ethical concerns in text analytics

Module 14: Integrating Text Analytics into Business Intelligence Systems

  • Workflow integration strategies
  • Combining structured and unstructured data
  • Real-time analytics in BI dashboards
  • Communicating insights to decision-makers
  • Examples of integrated BI solutions

Module 15: Future Trends in Text and Sentiment Analytics

  • AI-driven conversational analytics
  • Real-time multilingual sentiment analysis
  • Integration with voice and speech recognition
  • Predictive sentiment analysis
  • Emerging applications in next-gen BI

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

 

Text And Sentiment Analytics For Smarter Business Intelligence Decisions Training Course in Bosnia and Herzegovina
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