Introduction to Business Analytics Course | IABAC

An "Introduction to Business Analytics" course covers essential concepts and tools to analyze business data, make data-driven decisions, and improve organizational performance. Key topics include data visualization, statistical analysis, and predictive modeling techniques. Ideal for aspiring data analysts.

1. Introduction to Business
Analytics Course
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2. Content
1. Fundamentals of Business Analytics
2. Tools and Techniques
3. Application and Impact
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3. Understanding Business Analytics
Definition and Scope Key Concepts Real-world Examples
Business analytics involves the
use of data, statistical analysis,
and predictive modeling to drive
informed business decisions.
Descriptive, diagnostic, predictive,
and prescriptive analytics form the
core concepts of business
analytics.
Case studies of companies
leveraging business analytics for
strategic decision-making.
Fundamentals of Business Analytics
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4. Importance of Business Analytics
Decision Support
Competitive Advantage
Career OpportunitiesBusiness analytics provides insights for optimizing operations, identifying trends, and mitigating risks. How businesses gain a competitive edge through data-driven strategies and market insights. Exploring the diverse career paths and opportunities in the field of business analytics.
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5. 01 02 03
Ethical and Legal Considerations
Data Privacy and
Security
Regulatory
Compliance
Case Studies
The importance of ethical
data handling and
safeguarding sensitive
information.
Understanding the legal
frameworks and industry
standards governing data
usage and analytics.
Instances of ethical and
legal implications in
business analytics and
their impact.
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6. Data Visualization and Interpretation
Visual Representation Tools like Tableau Interactive Session
Exploring the significance of
visualizing data for effective
communication and analysis.
Introduction to Tableau and its role
in creating interactive and
insightful visualizations.
Engaging activities to demonstrate
the power of data visualization
tools.
Tools and Techniques
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7. Statistical Analysis and Modeling
Statistical Methods
Predictive Modeling
Hands-on PracticeAn overview of statistical techniques used for analyzing and interpreting data patterns. Understanding the process of building predictive models for forecasting and decision support. Interactive exercises using statistical tools and modeling software.
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8. 01 02 03
Data Mining and Machine Learning
Data Extraction
and Exploration
Machine Learning
Algorithms
Use Cases
Techniques for extracting
valuable insights from
large datasets through
data mining.
Introduction to machine
learning and its
applications in business
analytics.
Examples of data mining
and machine learning
applications in real-world
scenarios.
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9. Business Analytics in Industry
Industry Adoption
Examining how various industries
utilize business analytics for
strategic planning and
performance improvement.
Future Trends
Anticipated developments and
innovations in the application of
business analytics across
industries.
Application and Impact
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10. Business Analytics for Decision-making
Strategic Decision Support
Risk Management
Interactive Scenario AnalysisHow business analytics aids in making informed decisions for growth and sustainability. Leveraging analytics to identify and mitigate potential risks in business operations. Engaging students in a decision-making exercise using business analytics insights.
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11. 01 02 03
Career Pathways in Business Analytics
Roles and
Responsibilities
Skill Development Professional
Development
Exploring the diverse
roles such as data
analyst, business
intelligence analyst, and
data scientist.
Key skills and
competencies required for
a successful career in
business analytics.
Opportunities for further
education and certification
in the field of business
analytics.
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12. Thank you
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