Practice IB Computer Science (CS) Topic A.4 Further Database Models and Database Analysis with authentic exam-style questions for both SL and HL students. This question bank focuses on the exact syllabus content for A.4 Further Database Models and Database Analysis and mirrors Paper 1, 2, 3 style where relevant.
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EduBooks Ltd. is a global distributor of educational materials and uses a data warehouse to store data on customer preferences, sales trends, and market research. They aim to use this data to improve targeted marketing strategies.
(a) (i) Outline why data warehousing is beneficial for long-term business intelligence.
(a) (ii) Outline one reason why EduBooks would choose to use a data warehouse instead of operational databases for analytics.
(b) Explain the importance of data cleaning in EduBooks' ETL process before loading data into the warehouse.
(c) Compare the techniques of cluster analysis and classification as methods for identifying patterns in EduBooks’ data.
(d) Describe how predictive modeling could be used by EduBooks to forecast popular book genres for next season.
A telecommunication company stores a large amount of data in three databases.
The database segmentation is carried out on the CUSTOMERS database.
Data mining is used to extract knowledge hidden in this large amount of data. Before using data mining processes the existing data should be cleaned up.
Customers committing fraud is a risk to the company.
Evaluate the use of an object-oriented database as opposed to a relational database.
Define a spatial database.
State what is meant by database segmentation.
Explain one benefit of database segmentation to the telecommunication company.
Explain how ETL processes could be used in data preparation.
Distinguish between the use of association and sequential patterns as data mining techniques.
Describe how deviation detection could be used to detect fraud at the telecommunications company.
Customers who decide to leave the telecommunication company for a competitor may result in huge losses for the telecommunications company.
Explain with the use of an example, how predictive modelling could be used to optimize information sent to existing customers.
Assume MONS is a proposed cryptocurrency project that uses blockchain technology. You may refer to general properties of blockchain systems (e.g. hashing, distributed ledgers, consensus) in your answer.
Implementing blockchain technology for the MONS cryptocurrency ensures both security and scalability. How far do you agree with this statement?
Modern pharmaceutical companies increasingly rely on advanced data architectures to manage global supply chains and clinical research. These organizations must choose between different database paradigms, such as relational and object-oriented, to handle diverse data types ranging from simple inventory counts to complex molecular models. To synthesize this information for high-level decision-making, they utilize consolidated data environments like data warehouses.
Outline two benefits of implementing an object-oriented database (OODB) when managing complex biological data structures compared to a traditional relational model.
State two functions of metadata within a large-scale data warehouse.
Outline why data scrubbing (cleaning) is a critical step before loading raw sensor data from the supply chain into a warehouse.
Explain the importance of defining the appropriate level of granularity for logistics data in a pharmaceutical warehouse.
Explain how sequential pattern mining could be used to improve the efficiency of clinical trial phases.
Explain how cluster analysis might be used to categorize international distribution centers.
Once data has been consolidated, predictive modeling can be applied to anticipate drug shortages. This high-level analytics is essential for the company but raises significant ethical and privacy concerns.
Discuss whether the benefits of using predictive data mining in this scenario outweigh the potential risks to data privacy.
SkyStream Media is a global video-on-demand service that maintains a high-volume data warehouse. This system aggregates subscriber viewing habits, content metadata, and engagement metrics from various regional servers to help management optimize content production and personalized marketing strategies.
Define the term metadata in the context of a data warehouse.
Outline why data in a data warehouse is described as subject-oriented.
Describe one challenge SkyStream Media might face during the extraction stage of the ETL process.
Compare cluster analysis and regression analysis as data mining techniques that SkyStream Media could use to understand subscriber behavior.
Describe how the slicing operation in OLAP could be used to analyze the popularity of a specific movie genre.