IB Computer Science: Databases Final
Exam Questions And 100% Correct
Answers.
What do ACID properties do? - Answer ensure that the transaction get executed successfully and its
effect permanently stored in the database.
• If the transaction is rolled back, it must return the database to its last consistent state before the
update.
Describe situations suitable for data warehousing - Answer Strategic Planning
• Strategic planning is a review and planning process that is undertaken to make thoughtful decisions
about an organization's future in order to ensure its success.
By following a strategic planning process, an organizations can improve business outcomes and avoid
taking on unanticipated risks due to lack of foresight.
• One key item the organization would need to plan is data.
• A data warehouse provides data necessary for this
Business Modelling
At its simplest, a business model is a specification describing how an organization fulfills its purpose. All
business processes and policies are part of that model. • A business model answers the following
questions: Who is your customer, what does the customer value, and how do you deliver value at an
appropriate cost?
• Data in a data warehouse largely influence how a business is modeled
Explain the need for ETL processes in data warehousing. - Answer • ETL is ideal when the
data has to be integrated from different source systems
source system have data in different formats
process has to be repeated severally
,Associations - Answer • In association, a pattern is discovered based on a relationship between items in
the same transaction.
• That's is the reason why association technique is also known as relation technique.
• The association technique is used in market basket analysis to identify a set of products that
customers frequently purchase together
Describe situations that benefit from
data mining. - Answer • Database analysis and decision support • Market analysis and management
• target marketing, customer relation management, market basket analysis, cross selling, market
segmentation
• Risk analysis and management
• Forecasting, customer retention, improved underwriting, quality control, competitive analysis
• Fraud detection and management
Difference between clustering and classification - Answer • Supervised learning (classification)
• Supervision: The training data (observations, measurements, etc.) are accompanied by labels
indicating the class of the observations
• New data is classified based on the training set
• Unsupervised learning (clustering)
• The class labels of training data is unknown
• Given a set of measurements, observations, etc. with the aim of establishing the existence of classes
or clusters in the data
Forecasting - Answer • This discovers relationships between independent variables and the predicted
variables from past occurrences, and exploiting them to predict the unknown outcome.
• For instance, the prediction analysis technique can be used in sale to predict profit for the future if we
consider sale is an independent variable, profit could be a dependent variable.
Sequential Patterns - Answer • Sequential patterns analysis seeks to discover or identify similar
patterns, regular events or trends in transaction data over a business period.
, • In sales, with historical transaction data, businesses can identify a set of items that customers buy
together at different times in a year. Then businesses can use this information to recommend customers
buy it with better deals based on their purchasing frequency in the past.
Classifications - Answer • Classification is a classic data mining technique based on machine learning
(computer systems that can learn from data).
• Basically classification is used to classify each item in a set of data into one of predefined set of classes
or groups.
• Classification method makes use of mathematical techniques such as decision trees, linear
programming, neural network and statistics.
• In classification, the software developed can learn how to classify the data items into groups.
Data - Answer Collection of raw facts and figures
Information - Answer This is processed data within a context. Processing may involve sorting, selection,
arithmetic manipulations, interpretation, summarizing
Differences between data and information with examples - Answer Data:
1. Usually meaningless and difficult to understand because of lack of context
2. Usually serves as input to processing systems
3. Almost useless in decision making
4. Example: Statistics, numbers, characters, images
Information:
1. Usually meaningful and easy to understand and interpret since there is context
2. Usually is the output of some processing
3. Useful in decision making
4. Examples: reports, pay slips, bills
Database - Answer a collection of data and information that is organized so that it can easily be
accessed, managed, and updated.
Exam Questions And 100% Correct
Answers.
What do ACID properties do? - Answer ensure that the transaction get executed successfully and its
effect permanently stored in the database.
• If the transaction is rolled back, it must return the database to its last consistent state before the
update.
Describe situations suitable for data warehousing - Answer Strategic Planning
• Strategic planning is a review and planning process that is undertaken to make thoughtful decisions
about an organization's future in order to ensure its success.
By following a strategic planning process, an organizations can improve business outcomes and avoid
taking on unanticipated risks due to lack of foresight.
• One key item the organization would need to plan is data.
• A data warehouse provides data necessary for this
Business Modelling
At its simplest, a business model is a specification describing how an organization fulfills its purpose. All
business processes and policies are part of that model. • A business model answers the following
questions: Who is your customer, what does the customer value, and how do you deliver value at an
appropriate cost?
• Data in a data warehouse largely influence how a business is modeled
Explain the need for ETL processes in data warehousing. - Answer • ETL is ideal when the
data has to be integrated from different source systems
source system have data in different formats
process has to be repeated severally
,Associations - Answer • In association, a pattern is discovered based on a relationship between items in
the same transaction.
• That's is the reason why association technique is also known as relation technique.
• The association technique is used in market basket analysis to identify a set of products that
customers frequently purchase together
Describe situations that benefit from
data mining. - Answer • Database analysis and decision support • Market analysis and management
• target marketing, customer relation management, market basket analysis, cross selling, market
segmentation
• Risk analysis and management
• Forecasting, customer retention, improved underwriting, quality control, competitive analysis
• Fraud detection and management
Difference between clustering and classification - Answer • Supervised learning (classification)
• Supervision: The training data (observations, measurements, etc.) are accompanied by labels
indicating the class of the observations
• New data is classified based on the training set
• Unsupervised learning (clustering)
• The class labels of training data is unknown
• Given a set of measurements, observations, etc. with the aim of establishing the existence of classes
or clusters in the data
Forecasting - Answer • This discovers relationships between independent variables and the predicted
variables from past occurrences, and exploiting them to predict the unknown outcome.
• For instance, the prediction analysis technique can be used in sale to predict profit for the future if we
consider sale is an independent variable, profit could be a dependent variable.
Sequential Patterns - Answer • Sequential patterns analysis seeks to discover or identify similar
patterns, regular events or trends in transaction data over a business period.
, • In sales, with historical transaction data, businesses can identify a set of items that customers buy
together at different times in a year. Then businesses can use this information to recommend customers
buy it with better deals based on their purchasing frequency in the past.
Classifications - Answer • Classification is a classic data mining technique based on machine learning
(computer systems that can learn from data).
• Basically classification is used to classify each item in a set of data into one of predefined set of classes
or groups.
• Classification method makes use of mathematical techniques such as decision trees, linear
programming, neural network and statistics.
• In classification, the software developed can learn how to classify the data items into groups.
Data - Answer Collection of raw facts and figures
Information - Answer This is processed data within a context. Processing may involve sorting, selection,
arithmetic manipulations, interpretation, summarizing
Differences between data and information with examples - Answer Data:
1. Usually meaningless and difficult to understand because of lack of context
2. Usually serves as input to processing systems
3. Almost useless in decision making
4. Example: Statistics, numbers, characters, images
Information:
1. Usually meaningful and easy to understand and interpret since there is context
2. Usually is the output of some processing
3. Useful in decision making
4. Examples: reports, pay slips, bills
Database - Answer a collection of data and information that is organized so that it can easily be
accessed, managed, and updated.
