Analytics for Competitive Advantage Notes
Subject Overview
The third Business Analytics group elective, covering business analytics fundamentals and its role in competitive advantage, linking analytics with business strategy and organizational challenges, data sourcing/
Subject at a glance
4
Units
27
Topics
4
Credits
4
Infographics
Unit-wise Syllabus
4 units — open any unit for detailed topic-wise notes, diagrams and important exam questions
- Concept
- evolution and scope of business analytics
- big data characteristics and role of IoT
- analytics and competitive advantage
- business analytics models across industries
- customer analytics
- data-driven decision making
Volume
Velocity
Variety
Veracity
Value
Study guide
This unit covers the concept and scope of analytics, big data characteristics, IoT, analytics models across industries, customer analytics and data-driven decisions. Find an example of analytics driving a company's advantage.
- Linking analytics with business strategy
- identifying use cases
- value of business analytics
- organizational challenges and process integration
- building data competencies
- communication of analytics insights
- 1
Business goals
- 2
Identify use cases
- 3
Prioritise by value and feasibility
- 4
Build data competencies
- 5
Embed in processes
- 6
Communicate insights
Study guide
You study linking analytics to strategy, use cases, value, organisational challenges, competencies and communicating insights. Pick a use case and justify its business value.
- Types and sources of data
- big data infrastructure (data warehousing, cloud computing)
- data quality and bias
- descriptive/predictive/prescriptive analytics
- text/speech/image analytics
- machine learning and AI
- data visualization and storytelling
- Prescriptive
What should we do?
- Predictive
What will happen?
- Diagnostic
Why did it happen?
- Descriptive
What happened?
Study guide
You study data sources, big data infrastructure, data quality and bias, descriptive, predictive and prescriptive analytics, text, speech and image analytics and machine learning and AI. Check a data set for bias.
- Developing execution plans
- performance measurement frameworks
- data governance
- privacy and ethical challenges in analytics and AI
- cybersecurity and data risk management
- building a data-driven culture
- future trends in AI and big data
Data quality
Accurate and complete
Privacy
Consent, DPDP Act
Security
Access control, encryption
Ethics
Fairness, bias checks
Culture
Decisions driven by data
Study guide
You study execution plans, performance measurement, governance, privacy and ethics in analytics and AI, cybersecurity, data-driven culture and future trends. Draft a simple data governance policy.
Why Analytics for Competitive Advantage Matters
Analytics strategy skills prepare managers to lead data initiatives, a role in high demand across industries.
How to Prepare for Analytics for Competitive Advantage
- Study analytics case studies from different sectors.
- Practise communicating insight to non-technical audiences.
- Learn data governance basics.
Analytics for Competitive Advantage: Frequently Asked Questions
What are descriptive, predictive and prescriptive analytics?
Descriptive explains what happened, predictive estimates what may happen and prescriptive recommends what to do.