Data Mining Chapter 4 Part 1
Data Mining Mastery Quiz
Test your knowledge of data warehousing and mining concepts through our comprehensive quiz! With 50 carefully crafted questions, this quiz is designed for anyone looking to sharpen their understanding of data repositories and OLAP operations.
- Evaluate your understanding of key data warehouse features.
- Explore a variety of topics including data cleaning, integration, and OLAP operations.
- Perfect for students, educators, and professionals in the field.
...... Refers to a data repository that is maintained separately from an organization’s operational databases.
Database
Data warehouse
Data lake
None of them
The major features of a data warehouse are............
subject-oriented, integrated
time-variant, nonvolatile
Both a and b
None of them
Data warehouses usually require only two operations in data accessing, which are .....
initial loading of data
Access of data
Both a and b
None of them
Systems that perform online transaction and query processing are called...
OLTP
OLAP
DBMS
None of them
systems that can organize and present data in various formats in order to accommodate the diverse needs of different users, are called.....
OLTP
OLAP
DBMS
None of them
Data warehouses often adopt a ..... architecture.
Four-tier
Two-tier
Three-tier
None of them
From bottom to top, the order of the three-tier architecture levels of a data warehouse is.....
warehouse database server, front-end client layer and OLAP server
warehouse database server, OLAP server and front-end client layer
front-end client layer, OLAP server and warehouse database server
None of them
Examples of data Warehouse Models are....
Enterprise Warehouse
Data Mart
Virtual Warehouse
All of them
.......contains a subset of corporate-wide data that is of value to a specific group of users.
Enterprise Warehouse
Data Mart
Virtual Warehouse
None of them
.... Data marts are sourced from data captured from external information providers but ..... Data marts are sourced directly from enterprise data warehouses.
Independent, dependent
Dependent, Independent
Dependent, Dependent
None of them
.....gathers data from multiple, heterogeneous, and external sources.
Data extraction
Data cleaning
Data transformation
None of them
......detects errors in the data and rectifies them when possible.
Data extraction
Data cleaning
Data transformation
None of them
.....which converts data from legacy or host format to warehouse format.
Data extraction
Data cleaning
Data transformation
None of them
.....are the perspectives or entities with respect to which an organization wants to keep records.
Facts
Dimensions
Table
None of them
.....are numeric measures or quantities by which we want to analyze relationships between dimensions.
Facts
Dimensions
Table
None of them
.....are numeric measures or quantities by which we want to analyze relationships between dimensions.
Facts
Dimensions
Table
None of them
The most popular data model for a data warehouse is a multidimensional model, which can exist in the form of ......
Star schema
Snowflake schema
Fact constellation schema
All of them
A concept hierarchy that is a total or partial order among attributes in a database schema is called .....
Schema hierarchy
Partial hierarchy
Total hierarchy
None of them
Measures can be organized into categories, such as....
Distributive
Algebraic
Holistic
All of them
.... Is an OLAP operation that performs aggregation on a data cube, either by climbing up a concept hierarchy for a dimension or by dimension reduction.
Roll up
Drill down
Slice and dice
Pivot
.... Is an OLAP operation that's the reverse of roll-up and It navigates from less detailed data to more detailed data.
Roll up
Drill down
Slice and dice
Pivot
.... Is an OLAP operation that performs a selection on one dimension of the given cube, resulting in a subcube.
Roll up
Drill down
Slice and dice
Pivot
.... Is an OLAP operation that is a visualization operation that rotates the data axes in view to provide an alternative data presentation.
Roll up
Drill down
Slice and dice
Pivot
The construction of data warehouses involves data cleaning, data integration, and data transformation.
True
False
Data warehouses provide online transaction processing (OLTP) tools for the interactive analysis of multidimensional data.
True
False
Data mining functions can be integrated with OLAP operations to enhance interactive mining of knowledge at multiple levels of abstraction
True
False
The major features of a data warehouse are subject-oriented, integrated, time-variant, and nonvolatile.
True
False
Data warehouse doesn't focus on the modeling and analysis of data for decision makers.
True
False
A data warehouse is usually constructed by integrating multiple heterogeneous sources, such as relational databases, flat files, and online transaction records.
True
False
In data warehouses, data are stored to provide information from an historic perspective (e.g., the past 5–10 years).
True
False
A data warehouse does require transaction processing, recovery, and concurrency control mechanisms.
True
False
Data warehousing employs an query-driven approach.
True
False
Query processing in data warehouses does not interfere with the processing at local sources.
True
False
An OLTP system is customer-oriented but an OLAP system is market-oriented.
True
False
An OLAP system manages current data that are too detailed but an OLTP system manages large amounts of historic data.
True
False
An OLTP system usually adopts an application-oriented database design but an OLAP system adopts an subject-oriented database design.
True
False
The access patterns of an OLTP system consist mainly of short, atomic transactions but accesses to OLAP systems are mostly read-only operations.
True
False
An OLAP server is typically implemented using either a ROLAP model or a MOLAP model.
True
False
A virtual warehouse is a set of views over operational databases.
True
False
Metadata are data about data.
True
False
Data warehouses and OLAP tools are based on a one-dimensional data model.
True
False
A data cube allows data to be modeled and viewed in multiple dimensions.
True
False
The cuboid that holds the lowest level of summarization is called the base cuboid.
True
False
The 0-Dimension cuboid, which holds the highest level of summarization, is called the apex cuboid.
True
False
A concept hierarchy defines a sequence of mappings from a set of low-level concepts to higher-level, more general concepts.
True
False
Drill-through is an OLAP operation that executes queries involving more than one fact table.
True
False
drill-across is an OLAP operation that uses relational SQL facilities to drill through the bottom level of a data cube down to its back-end relational tables.
True
False
A statistical database is a database system that is designed to support statistical applications.
True
False
A starnet model is a model that consists of radial lines emanating from a central point, where each line represents a concept hierarchy for a dimension.
True
False
Concept hierarchies can be used to generalize data or to specialize data.
True
False
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