Data Modeling Quiz

Redundancies can compromise the consistency of the database and lead to anomalies.

An update anomaly occurs when changing one piece of data requires multiple changes in different places.

Normalization helps prevent anomalies by reducing redundancies and ensuring data is stored in a structured and consistent manner.

<p>Relational, multidimensional, and semantic</p> Signup and view all the answers

<p>To structure communication between users and developers and as a basis for database design</p> Signup and view all the answers

<p>Redundant information can be stored</p> Signup and view all the answers

<p>Compromise the consistency and can lead to anomalies.</p> Signup and view all the answers

<p>If the department number changes, several tuples must be changed at the same time.</p> Signup and view all the answers

<p>Normalization helps avoid redundancies and inconsistencies.</p> Signup and view all the answers

<p>Star and snowflake schemas allow performance-oriented modeling of multidimensional spaces by structuring data in a way that optimizes query performance.</p> Signup and view all the answers

<p>Physical data models specify how data is physically stored, logical data models describe data on a logical level regardless of storage, and semantic data models depict data on a technology-neutral level.</p> Signup and view all the answers

<p>The entity relationship model (ERM) is used in the conceptual phase of application development to structure communication between users and developers, and as a basis for database design in the implementation phase.</p> Signup and view all the answers

<p>The purpose of normalization is to eliminate redundancies and inconsistencies in data, making it more efficient to manage.</p> Signup and view all the answers

<p>Edgar F. Codd</p> Signup and view all the answers

<p>In 1NF, a table row may only contain one attribute value and the attribute value must be atomic.</p> Signup and view all the answers

<p>The purpose of normalization in database design is to eliminate redundancies and inconsistencies in data, making it more efficient to manage.</p> Signup and view all the answers

<p>The first normal form (1NF) states that a table row may only contain one attribute value and the attribute value must be atomic.</p> Signup and view all the answers

<p>The theory of normal forms was developed by Edgar F. Codd, the inventor of the relational database.</p> Signup and view all the answers

<p>A relation is in the second normal form if it is in the first normal form and all non-key attributes depend functionally on the entire key.</p> Signup and view all the answers

<p>A relation is in the third normal form if the second normal form exists and no functional dependencies exist between non-key attributes.</p> Signup and view all the answers

<p>A new table must be created from those attributes that only depend on a part of the compound primary key.</p> Signup and view all the answers

<p>The focus of the OLAP cube model is usually on business ratios as carriers of quantitative information.</p> Signup and view all the answers

<p>Attributes are the characteristics that describe a dimension, while dimensions are sets of attributes that explain a specific aspect of the data.</p> Signup and view all the answers

<p>The relationship hierarchy facilitates both the aggregation of data and navigation through the data in the OLAP cube model.</p> Signup and view all the answers

<p>spreadsheet-style display</p> Signup and view all the answers

<p>values of X</p> Signup and view all the answers

<p>values of Y</p> Signup and view all the answers

<p>An OLAP cube is a multi-dimensional array of data used for online analytical processing (OLAP), which is a computer-based technique of analyzing data to look for insights.</p> Signup and view all the answers

<p>A cube is a multi-dimensional dataset, while a hypercube refers to a multi-dimensional dataset with more than three dimensions.</p> Signup and view all the answers

<p>A slice is a subset of the data in an OLAP cube that is generated by selecting a specific value for one dimension and only showing the data associated with that value.</p> Signup and view all the answers

<p>A hierarchy is a set of parent-child relationships in which a parent member summarizes its children.</p> Signup and view all the answers

<p>The common operations in OLAP cube analysis include slice and dice, drill down, roll up, and pivot.</p> Signup and view all the answers

<p>The slice operation involves picking a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension.</p> Signup and view all the answers

<p>The roll-up operation involves summarizing the data along a dimension, using an aggregate function or a set of formulas.</p> Signup and view all the answers

<p>The result is a spreadsheet-style display.</p> Signup and view all the answers

<p>Values of X populate row 1.</p> Signup and view all the answers

<p>Values of Y populate column A.</p> Signup and view all the answers

<p>An OLAP cube is a multi-dimensional array of data used for online analytical processing (OLAP). It is a computer-based technique of analyzing data to look for insights.</p> Signup and view all the answers

<p>A cube is a multi-dimensional dataset, while a hypercube refers to a dataset with more than three dimensions.</p> Signup and view all the answers

<p>A slice is a subset of the data generated by selecting a specific value for one dimension and displaying only the data associated with that value.</p> Signup and view all the answers

<p>The purpose of the &quot;slice&quot; operation is to pick a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension.</p> Signup and view all the answers

<p>The purpose of the &quot;dice&quot; operation is to produce a subcube by allowing the analyst to pick specific values of multiple dimensions.</p> Signup and view all the answers

<p>The purpose of the &quot;drill down/up&quot; operation is to allow the user to navigate among levels of data ranging from the most summarized (up) to the most detailed (down).</p> Signup and view all the answers

<p>The purpose of the &quot;roll-up&quot; operation is to involve summarizing the data along a dimension, typically using an aggregate function or a set of formulas.</p> Signup and view all the answers

<p>The result is a spreadsheet-style display.</p> Signup and view all the answers

<p>Values of X populate row $1.</p> Signup and view all the answers

<p>Values of Y populate column $A.</p> Signup and view all the answers

<p>The purpose of OLAP is to analyze data and look for insights.</p> Signup and view all the answers

<p>A cube is a multi-dimensional dataset that represents the data's dimensions.</p> Signup and view all the answers

<p>Measures are represented as numbers in each cell of the cube, while dimensions are derived from dimension tables.</p> Signup and view all the answers

<p>The purpose of the &quot;drill down&quot; operation is to allow the user to navigate among levels of data ranging from the most summarized to the most detailed.</p> Signup and view all the answers

<p>The purpose of the &quot;pivot&quot; operation is to allow an analyst to rotate the cube in space to see its various faces.</p> Signup and view all the answers

<p>In database theory, an OLAP cube is an abstract representation of a projection of an RDBMS relation. Given a relation of order N, consider a projection that subtends X, Y, and Z as the key and W as the residual attribute.</p> Signup and view all the answers

<p>The common operations in OLAP cube analysis include slice and dice, drill down, roll up, and pivot.</p> Signup and view all the answers

<p>to display values of g : ( X, Y ) → W at intersections of X-labeled columns and Y-labeled rows</p> Signup and view all the answers

<p>to populate the row $1</p> Signup and view all the answers

<p>to populate the column $A</p> Signup and view all the answers

<p>OLAP is a technique used for analyzing data to look for insights.</p> Signup and view all the answers

<p>A cube is a multi-dimensional dataset that can be considered a multi-dimensional generalization of a spreadsheet.</p> Signup and view all the answers

<p>Measures represent some measure of the business, such as sales or profits, while dimensions represent the different aspects or categories by which the data is summarized, such as product or time. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables.</p> Signup and view all the answers

<p>The four common operations in OLAP cube analysis are slice and dice, drill down, roll up, and pivot.</p> Signup and view all the answers

<p>The purpose of the slice operation in OLAP cube analysis is to pick a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension.</p> Signup and view all the answers

<p>The purpose of the dice operation in OLAP cube analysis is to produce a subcube by allowing the analyst to pick specific values of multiple dimensions.</p> Signup and view all the answers

<p>The purpose of the drill down operation in OLAP cube analysis is to allow the user to navigate among levels of data ranging from the most summarized to the most detailed.</p> Signup and view all the answers

<p>The purpose of the roll up operation in OLAP cube analysis is to involve summarizing the data along a dimension.</p> Signup and view all the answers

<p>The star schema is the simplest style of data mart schema and is widely used in data warehouses and dimensional data marts.</p> Signup and view all the answers

<p>The star schema consists of one or more fact tables referencing any number of dimension tables.</p> Signup and view all the answers

<p>The star schema is more effective for handling simpler queries and provides a clear and intuitive structure for organizing data in a data warehouse.</p> Signup and view all the answers

<p>Transaction, snapshot, accumulating snapshot</p> Signup and view all the answers

<p>Simpler queries, simplified business reporting logic, query performance gains, fast aggregations, feeding cubes</p> Signup and view all the answers

<p>Time, geography, product, employee, range</p> Signup and view all the answers

<p>To ensure each row can be uniquely identified</p> Signup and view all the answers

<p>The main difference is that the dimension table of the snowflake schema is maintained in the normalized form to reduce redundancy.</p> Signup and view all the answers

<p>The advantages include easy maintenance and storage space savings. However, it may result in slower query response times and higher resource usage.</p> Signup and view all the answers

<p>The decision should consider query performance, schema complexity, and data integrity requirements.</p> Signup and view all the answers