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Questions and Answers List

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Question	Answer
These techniques are suitable for delivering a solution. But in case of decision-support systems, we do not know what query and operation needs to be executed in future.	System Processes
We have a fixed number of operations to be applied on the operational databases and we have well-defined techniques such as use normalized data, keep table small, etc.	System Processes
True or False: techniques applied on operational databases are not suitable for data warehouses.	TRUE
involves determining when to start data extraction and the consistency check on data; Ensures that the tools, the logic modules, and the programs are executed in correct sequence and at correct time.	Controlling the Process
Data extraction takes data from the source systems. Data load takes the extracted data and loads it into the data warehouse.	Extract and Load Process
True or False: Data needs to be in an inconsistent state when it is extracted, i.e., the data warehouse should represent a single, consistent version of the information to the user.	FALSE
True or False: After extracting the data, it is loaded into a permanent data store where it is cleaned up and made consistent.	FALSE
True or False: Consistency checks are executed only when all the data sources have been loaded into the temporary data store.	TRUE
involves converting the source data into a structure.	Transforming
increases the query performance and decreases the operational cost.	Structuring
It will optimize the hardware performance and simplify the management of data warehouse.	Partition the Data
is required to speed up common queries.; relies on the fact that most common queries will analyze a subset or an aggregation of the detailed data.	Aggregation
involves removing the old data from the system in a format that allow it to be quickly restored whenever required.	Archiving
In order to recover the data in the event of data loss, software failure, or hardware failure, it is necessary to keep regular backups.	Backup and Archive the Data
The information generated in this process is used by the warehouse management process to determine which aggregations to generate.	Query Management Process
is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients computing within the enterprise. Each data warehouse is different, but all are characterized by standard vital components.	Data Warehouse Architecture
simplifies data cleansing and consolidation for operational method coming from multiple source systems, especially for enterprise data warehouses where all relevant data of an enterprise is consolidated.	Staging Area
A place where data is processed before entering the warehouse	Staging Area
is a segment of a data warehouses that can provided information for reporting and analysis on a section, unit, department or operation in the company., sales, payroll, production, etc.	Data Marts
Analytical and transactional processing should be kept apart as much as possible	Separation
Hardware and software architectures should be simple to upgrade the data volume, which has to be managed and processed, and the number of user’s requirements, which have to be met, progressively increase	Scalability
The architecture should be able to perform new operations and technologies without redesigning the whole system.	Extensibility
Monitoring accesses are necessary because of the strategic data stored in the data warehouses.	Security
Data Warehouse management should not be complicated.	Administrability
is not periodically used in practice. Its purpose is to minimize the amount of data stored to reach this goal; it removes data redundancies.	Single-tier Architecture
shows the only layer physically available in Single-tier Architecture	Source Layer
True or False: Cleaning and transforming the loaded data will slowdown the queries.	False
True or False: Controlling the process involves determining when to start data extraction and the consistency check on data.	TRUE
True or False: Data needs to be in an inconsistent state when it is extracted	FALSE
True or False: Structuring the data decreases the query performance and increase the operational cost	FALSE
True or False: There are five major processes that contribute to a data warehouse	FALSE
True or False: Consistency checks are executed only when all the data sources have been loaded into the temporary data store.	TRUE
True or False: Aggregation is not required to speed up common queries.	FALSE
True or False: Data extraction takes data from the source systems. Data load takes the extracted data and loads it into the data warehouse.	TRUE
True or False: After extracting the data, it is loaded into a temporary data store where it is cleaned up and made consistent	TRUE
True or False: Archiving involves removing the old data from the system in a format that allow it to be quickly restored whenever required	TRUE
Properties of data warehouse architectures should be able to perform new operations and technologies without redesigning the whole system.	Extensibility
A method used in data warehousing to refer to a system that is used to process the day-to-day transactions of an organization.	Operational System
True or False: A staging area simplifies data cleansing and consolidation for operational method coming from multiple source systems, especially for enterprise data warehouses where all relevant data of an enterprise is consolidated.	TRUE
True or False: The goals of the summarized information are to speed up query performance.	TRUE
Properties of data warehouse architectures management should not be complicated..	Administrability
Properties of data warehouse architectures that monitors the accesses are necessary because of the strategic data stored in the data warehouses.	Security
True or False: The principal purpose of a data warehouse is to provide information to the business managers for strategic decision-making.	TRUE
True or False: Each data warehouse is the same and all are characterized by standard vital components.	FALSE
True or False: Single-Tier architecture is not periodically used in practice. Its purpose is to minimize the amount of data stored to reach this goal;	TRUE
True or False: A warehouse database is updated from operational systems continuously, usually during office hours	FALSE
True or False: Meta Data summarizes necessary information about data, which can make finding and work with particular instances of data more accessible	TRUE
Properties of data warehouse architectures that analytical and transactional processing should be kept apart as much as possible.	Separation
Properties of data warehouse architectures should be simple to upgrade the data volume, which has to be managed and processed, and the number of user's requirements, which have to be met, progressively increase	Scalability
True or False: Data Warehouse applications are designed to support the user ad-hoc data requirements,	TRUE
True or False: Data Warehouse applications are designed to support the user ad-hoc data requirements,	TRUE
True or False: A data warehouse architecture is a method of defining the overall architecture of data communication processing and presentation that exist for end-clients computing within the enterprise.	TRUE
True or False: A data mart is a segment of a data warehouses that can provided information for reporting and analysis on a section, unit, department or operation in the company	TRUE
A set of data that defines and gives information about other data.	Meta Data
is a system of files in which transactional data is stored, and every file in the system must have a different name.	Flat Files
The mechanism of extracting information from source systems and bringing it into the data warehouse	ETL
ETL	Extraction, Transformation, and Loading
crucial in a data warehouse technique because it is supposed to improve data quality.	Cleansing
primary data cleansing features found in ETL tools	Rectification, Homogenization
the core of the reconciliation phase.	Transformation
Two ways to carry load	Refresh, Update
Data Warehouse data is completely rewritten	Refresh
Only those changes applied to source information are added to the Data Warehouse.	Update
ETL or ELT: High amounts of data	ELT
ETL OR ELT: Data is transferred to it and moved back to DB. High network bandwidth required.	ETL
ETL or ELT: Easily add the calculated column to the existing table.	ELT
ETL or ELT: Low maintenance as data is always available.	ELT
ETL or ELT: It needs high maintenance as you need to select data to load and transform.	ETL
ETL or ELT: Transformations are performed (in the source or) in the target.	ELT
ETL or ELT: Data Remains in the DB except for cross Database loads (e.g., source to object).	ELT