Podcast
Questions and Answers
What type of analytics focuses on analyzing historical performance?
Which question is typically answered by Predictive Analytics?
What is a primary function of Descriptive Analytics?
What type of analytics would be best suited for forecasting smartphone sales for next year?
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Which analytics type utilizes techniques like data aggregation?
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Which statement best describes Prescriptive Analytics?
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What is a core purpose of Predictive Analytics?
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Which analytics are considered the most traditional in the field?
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What is the primary input for a recommendation system?
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Which of the following is an example of content-based filtering?
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What distinguishes collaborative filtering from content-based filtering?
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Which of the following statement about collaborative filtering is true?
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What type of recommendations does the 'Customers who bought this item also bought' section from Amazon.com illustrate?
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What does United Airlines use their 'collect, detect, act' protocol for?
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Which attribute is NOT typically considered in content-based filtering for movies?
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In user-based collaborative filtering, what is primarily utilized to make recommendations?
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What feature does British Airways employ to enhance customer experience?
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Why is content-based filtering considered domain-specific?
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How does EasyJet use artificial intelligence in their operations?
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What partnership has Southwest Airlines pursued to improve safety?
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What type of data does EasyJet analyze to inform future decision-making?
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What measurable impact did the 'collect, detect, act' initiative have on United Airlines?
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What kind of offers does British Airways generate through data analysis?
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What significant data-driven outcome is associated with Southwest Airlines' collaboration with NASA?
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What is the primary basis for user-based collaborative filtering?
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Which movie can be recommended to User1 based on the provided ratings?
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In item-based collaborative filtering, what is the goal when calculating a user's preference for an item they have not rated?
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Which characteristic is shared between users in user-based collaborative filtering?
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What does the P value represent in item-based collaborative filtering?
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What is a common method to calculate the similarity between items in item-based collaborative filtering?
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What can be inferred if User1 and User3 have rated Movie1 and Movie4 similarly?
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What might happen if a user's calculated preference for an item exceeds a certain threshold in item-based collaborative filtering?
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What is the primary purpose of cookies when a user browses a website?
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Which of the following best describes how cookies function?
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In the case of Chow Tai Fook Jewelry, what was the purpose of collecting massive amounts of data?
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What feature distinguishes Explorium, the experimental shopping mall in Shanghai?
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What type of data do cookies primarily store?
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Which aspect of big data analysis is highlighted in the case of Li & Fung in China?
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What can cookies help a website to do when a user returns?
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How do cookies enhance user experience on websites?
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What is a primary factor WeLend uses to determine creditworthiness?
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How quickly can WeLend approve a loan application?
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Which company has implemented big data analytics for customer retention?
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What information does WeLend collect to assess user profiles?
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How does Citibank utilize big data analytics?
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What unique aspect does WeLend consider in addition to credit history?
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What is a benefit of big data for banks like Hang Seng Bank?
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What is the loan delinquency rate reported by WeLend in Hong Kong?
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Study Notes
Course Information
- Course title: GFQR 1026: Big Data in “X”
- Lecture 3: Big Data Analytics in Business (1)
- Course offered by: Department of Computer Science, Hong Kong Baptist University
Lecture 3: Outline
- Business Intelligence
- Types of Big Data Analytics used in Business
- Examples of Big Data Analytics in Business
- Technologies used in Business: Recommendation Systems & Cookies
Business Intelligence (BI)
- Businesses have used business intelligence (BI) tools for decades
- BI covers many applications and technologies to gather, store, analyze, and provide data access
- BI provides historical, current, and predictive views of business operations
- Combine BI with big data
Revenue from Big Data and Business Analytics
- Worldwide revenue from big data and business analytics increased from 2015 to 2022
- In 2018, the revenue was expected to be 166 billion U.S. dollars
Big Data Analytics
- Big data analytics is used in many fields: healthcare, telecom, insurance, government, finance, automobile, education, and retail
- This lecture focuses on big data in business
Types of Big Data Analytics
-
Descriptive Analytics: This is the most traditional type of business analytics which analyzes past performance using historical data to find the reasons for success or failure
- Example: Average weekly sales amount
-
Predictive Analytics: This uses statistical models and forecasting techniques to understand future trends or potential outcomes
- Example: Forecasting smart phone sales in the next year
-
Prescriptive Analytics: This goes beyond predicting future outcomes by suggesting actions to benefit from the predictions. It looks at "why" things will happen, proposes decision options, and considers the impact of each option.
- Example: Google self-driving car
Big Data in Aviation Industry
- Examples of big data in this industry: departure/arrival times of flights, social media activity, in-flight food preferences, and number of passengers
- Usages: aircraft maintenance, inventory management, fleet management, operations management (pilots, crew), staff management
- Benefits: smarter maintenance, improved safety, better service, reduced costs
- Related use cases from different airlines: United Airlines, British Airways, easyJet, Southwest Airlines, and Cathay Pacific are discussed.
- These examples demonstrate how big data helps with tailoring customer experience through personalization, efficiency, and cost reduction.
Big Data in Retail Industry
- Case: Alibaba
- One of Asia's top Big Data users
- Online transactions reached US$ 84.5 billion (HK$ 659 billion) in 2021
- Utilizes big data for personalized recommendations to cross-sell and up-sell products
- Other use cases discuss in detail how big data supports businesses in the retail industry.
- There are example cases to show that big data supports businesses to understand and predict customer behavior.
Big Data in Banking & Finance Industry
- Case: Hang Seng Bank
- Using online applications for loans without requiring income or address verification
- Analyzing customer behavior and creditworthiness via Big Data
- Case: Citibank
- Tracking more than 200 million customer accounts globally
- Identifying and managing fraudulent transactions using Big Data
- Case: WeLend (by WeLab)
- Hong Kong's first online lending platform founded in 2013
- Loans to customers without direct meetings, relying on Big Data for approval and user risk assessment
Big Data in Insurance Industry
- Case: HSBC Insurance
- Uses big data analysis for product innovations, such as the HSBC Term Protector and HSBC Cancer Term Protector
- Understands customer needs and requirements better with big data
- Case: MLC Life Insurance
- Using wearable technology to improve health activity and better provide insurance premiums
- Focuses on product innovation, customer experience, and customer engagement with big data
- Case: ZhongAn Online Casualty and Property Insurance
- China's first internet-only insurer
- Utilizes a one-stop shop for buyers and owners of cars
- Offers discounts and better policies based on driver's behavior.
Big Data used for Hospitality Industry
- Case: Marriott
- Uses unstructured/semi-structured data for demand forecasting, and optimizes room prices
- Case: Starwood Hotels and Resorts
- Optimizing room pricing globally based on local and worldwide factors, events and weather and increase yearly revenue by 5%
Big Data Applications In Business Sectors
- Airline sector: using sensors to improve safety
- Retail sector: using analytics to optimize the business
- Bank and Finance sector: using analytics to differentiate fraudulent interactions and transactions
- Insurance sector: using analytics for risk assessment, fraud detection, marketing, customer experience.
- Hospitality sector: using analytics for optimal pricing and personalized marketing campaigns.
Big Data Around You
- Increasing number of connected devices per person.
- Big data is growing rapidly
- The technologies related to big data are in many areas.
Summary of Lecture 3
- This lecture covers business intelligence, big data analytics types, business examples, recommendation and technologies
Cookies
- Small data files on a user's hard drive
- Cookies record browsing activity.
- Cookies remember and access information for later use (e.g., previous orders, pages visited).
- Helps personalize customer experiences from websites.
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Description
Explore the impact of big data analytics on business intelligence in this quiz. Learn about various types of analytics, technologies, and the growing revenue in this field. Test your understanding of how businesses leverage big data for better decision making.