Question: Explain how each of the following types

> Explain the difference between the WHERE and HAVING clause.

> Talk with a database administrator or designer from the organization. What type of metadata does this organization maintain about its databases? Why did the organization choose to keep track of these and not other metadata? What tools are used to maintai

> What can be changed about a table definition using the SQL command ALTER? Can you identify anything about a table definition that cannot be changed using the ALTER command?

> Explain the purpose of the CHECK clause within a CREATE TABLE SQL command.

> Contrast the following terms: a. scalar aggregate; vector aggregate b. DDL; DML c. catalog; schema

> How can an SQL command be structured to allow parallel execution?

> State four rules for choosing indexes for a relational database.

> What is a materialized view, and when would it be used?

> SQL:2006 and SQL:2008 introduced a new key word, MERGE. Explain how using this key word allows one to accomplish updating and merging data into a table using one command rather than two.

> What is an identity column? Explain the benefits of using the identity column capability in SQL.

> What considerations should be kept in mind when using indexing?

> Explain why SQL is called a set-oriented language.

> Investigate whether the organization follows more of a traditional file processing approach or the database approach to organizing data. How many different databases does the organization have? Try to draw a figure, similar to Figure 1-2, to depict some

> Contrast transactional and analytical data management approaches.

> How do you determine the order in which the rows in a response to an SQL query appear? What options do you have when specifying this order?

> In what clause of a SELECT statement is an IN operator used? What follows the IN operator? What other SQL operator can sometimes be used to perform the same operation as the IN operator? Under what circumstances can this other operator be used?

> How is the HAVING clause different from the WHERE clause?

> Match the following terms to the appropriate definitions: - referential integrity constraint - SQL: 2016 - Null value - scalar aggregate - vector aggregate - catalog - schema - host language a. list of values b. description of a database c. missing or no

> If an SQL statement includes a GROUP BY clause, the attributes that can be requested in the SELECT statement will be limited. Explain that limitation.

> What is the evaluation order for the Boolean operators (AND, OR, NOT) in an SQL command? How can a query writer be sure that the operators will work in a specific, desired order?

> What is the difference between COUNT, COUNT DISTINCT, and COUNT(*) in SQL? When will these three commands generate the same and different results?

> How is the order in which attributes appear in a result table determined? How are the column heading labels in a result table changed?

> Explain and provide at least one example of how to qualify the ownership of a table in SQL. What has to occur for one user to be allowed to use a table in a database owned by another user?

> Explain the factors to be considered in deciding whether to create an index for a column in SQL.

> In this chapter, we described four important data models and their properties: enterprise, conceptual, logical, and physical. In the following table, summarize the important properties of these data models by entering a Y (for yes) or an N (for no) in ea

> What are the potential consequences of inappropriate indexing decisions?

> Explain the purpose of indexing in database implementation.

> Explain how referential integrity is established in databases that are SQL:1999 compliant. Explain how the ON UPDATE RESTRICT, ON UPDATE CASCADE, and ON UPDATE SET NULL clauses differ from one another. What happens if the ON DELETE CASCADE clause is set?

> What are the primary data integrity constraints in SQL?

> Define each of the following terms: a. data definition language b. data manipulation language c. referential integrity constraint d. relational DBMS (RDBMS) e. schema

> Demonstrate each of the anomaly types with an example.

> Describe three types of anomalies that can arise in a table and the negative consequences of each.

> What is a schema? Discuss two common methods of expressing a schema.

> List the three components of a relational data model.

> Describe the primary differences between the conceptual and logical data models.

> Consider Figure 1-15. a. What is the purpose of introducing an attribute called Product ID to the Product table? What is its data type? b. If the company wants to keep track of the total outstanding balances of customers, an attribute called â&#128

> Contrast the following terms: a. normal form; normalization b. candidate key; primary key c. partial dependency; transitive dependency d. composite key; recursive foreign key e. determinant; candidate key f. foreign key; primary key g. natural primary ke

> What are the benefits of the use of an enterprise key?

> Why is the natural key preserved whenever a surrogate key is created?

> Describe the difference between how a 1:M unary relationship and an M:N unary relationship are implemented in a relational data model.

> What is an enterprise key, and why is it important?

> Under what conditions must a foreign key not be null?

> What are the properties that a candidate key must satisfy?

> In the context of unary relationships, what is a recursive foreign key?

> Suggest four steps to represent super/subtype relationships.

> Match the following terms to the appropriate definitions: - well-structured relation - anomaly - functional dependency - determinant - composite key - 1NF - 2NF - 3NF - recursive foreign key - transitive dependency a. constraint between two attributes b.

> Martin is encouraged by the progress you have made so far. As promised, he forwards you an email from one of the key members of his staff, Pat Smith (an artist manager). He also provide you with an e-mail from Shannon Howard, a prospective artist who mig

> How do you represent a 1:M unary relationship in a relational data model?

> What are the benefits of enforcing the integrity constraints as part of the database design and implementation process (instead of doing it in application design)?

> List the three steps to remove transitive dependencies.

> Discuss how transitive dependencies in a relation can be removed when it leads to anomalies.

> Outline a shortcut to describe relations in 3NF.

> What do you understand by domain constraint?

> Describe how the following components of an E-R diagram are transformed into relations: a. regular entity type b. relationship (1:M) c. relationship (M:N) d. relationship (supertype/subtype) e. multivalued attribute f. weak entity g. composite attribute

> Does normalization place any constraint on the storage of data in physical form or on its processing performance? Explain.

> Define each of the following terms: a. determinant b. functional dependency c. transitive dependency d. recursive foreign key e. normalization f. composite key g. candidate key h. normal form i. partial functional dependency j. enterprise key k. surrogat

> Martin is encouraged by the progress you have made so far. As promised, he forwards you an email from one of the key members of his staff, Pat Smith (an artist manager). He also provide you with an e-mail from Shannon Howard, a prospective artist who mig

> What types of business rules are normally captured in an EER diagram?

> What is a completeness constraint, and what are the total and partial specialization rules?

> What is attribute inheritance? Why is it important?

> Explain how specialization and generalization assist in the development of supertype/subtype relationships.

> Explain the need for EER modeling.

> Discuss the notations used to represent EER models. Which notation is the most widely used?

> Contrast the following terms: a. supertype; subtype b. generalization; specialization c. disjoint rule; overlap rule d. total specialization rule; partial specialization rule e. PARTY; PARTY ROLE f. entity; entity cluster

> Match the following terms and definitions: - supertype - entity cluster - subtype - specialization - subtype discriminator - attribute inheritance - generalization a. subset of supertype b. creating a supertype for entity types c. subtype gets supertype

> When is a member of a supertype always a member of at least one subtype?

> Why must the minimum cardinality next to SUPPLIES from PURCHASED PART be one yet the minimum cardinality next to SUPPLIES from SUPPLIER may be zero?

> Martin is encouraged by the progress you have made so far. As promised, he forwards you an email from one of the key members of his staff, Pat Smith (an artist manager). He also provide you with an e-mail from Shannon Howard, a prospective artist who mig

> Discuss how it is decided which subtype will be inserted with a new instance of a supertype.

> Does a data modeling project using a packaged data model require less or greater skill than a project not using a packaged data model? Why or why not?

> Purchasing a packaged data model involves mapping. What is mapping? What are the points you need to consider in mapping?

> In what ways is starting a data modeling project with a packaged data model different from starting a data modeling project with a clean sheet of paper?

> How are the attributes assigned in a supertype/subtype hierarchy?

> Give an example of generalization not discussed in the text.

> Define each of the following terms: a. supertype b. subtype c. specialization d. entity cluster e. completeness constraint f. enhanced entity-relationship (EER) model g. supertype/subtype hierarchy h. total specialization rule i. generalization j. disjoi

> What is the need for time stamping in modeling time dependent data?

> State the differences between a term and a fact.

> State six general guidelines for naming data objects in a data model.

> Martin is encouraged by the progress you have made so far. As promised, he forwards you an email from one of the key members of his staff, Pat Smith (an artist manager). He also provide you with an e-mail from Shannon Howard, a prospective artist who mig

> What are the characteristics of good business rules?

> Give four reasons why a business rules approach is advocated as a new paradigm for specifying information systems requirements.

> Give four reasons why many system designers believe that data modeling is important and arguably the most important part of the systems development process.

> Contrast the following terms: a. stored attribute; derived attribute b. minimum cardinality; maximum cardinality c. entity type; relationship type d. strong entity type; weak entity type e. degree; cardinality f. required attribute; optional attribute g.

> Why is time stamping considered an important part of the data modeling process?

> Explain any two characteristics of a good business rule.

> For the Manages relationship in Figure 2-12a, describe one or more situations that would result in different cardinalities on the two ends of this unary relationship. Based on your description for this example, do you think it is always clear simply from

> Match the following terms and definitions. - composite attribute - associative entity - unary relationship - weak entity - attribute - entity - relationship type - cardinality constraint - degree - identifier - entity type - ternary - optional attribute

> Why is data modeling considered more important than process modeling?

> What are the special guidelines for naming relationships?

> Interview a DB analyst or systems administrator in your university or at a local company that has adopted a packaged data model. Discuss how they adopted the model. What was the process of customization or mapping involved? Was the process complex? What

> State a rule that says when to extract an attribute from one entity type and place it in a linked entity type.

> Discuss why the E-R model is a popular modeling tool.

> Provide examples (other than those described in this chapter) of multiple relationships, and explain why these examples best represent this type of relationship. Discuss the role of identifiers in modeling this relationship.

> Give an example (other than those described in this chapter) for each of the following, and justify your answer: a. derived attribute b. multivalued attribute c. atomic attribute d. composite attribute e. composite identifier attribute f. optional attrib

> State the guidelines for naming entity types. Discuss why organizations customize a purchased data model.

> The chapter makes a distinction between a required attribute and an optional attribute. Illustrate a required attribute with a relevant example.

> When should an attribute be linked to an entity via a relationship?

> Discuss the main guidelines for defining relationships.

> Define each of the following terms: a. entity type b. entity-relationship model c. entity instance d. attribute e. relationship type f. strong entity type g. multivalued attribute h. associative entity i. cardinality constraint j. weak entity k. binary r

> Explain some of the advantages of large databases that organizations can benefit from considering how the amount of data processed and stored in databases will increase in the future.