Preface for Database Design – 3rd Edition

Computer Engineering Curricula 2016 (https://www.acm.org/binaries/content/assets/education/ce2016-final-report.pdf)

Chapters

CE-PPP-9 Contemporary issues (Page 88)

Articulate some of the privacy implications related to massive database systems.

Chapter 3

CE-SEC-9 Authentication (Page 91)

Discuss eavesdropping and server database reading and explain how various authentication methods deal with them.

CE-SPE-5 Risk, dependability, safety, and fault tolerance

Describe fault tolerance and dependability requirements of different applications (such as database, aerospace, telecommunications, industrial control, and transaction processing).

CE-SWD-10 Database systems (Page 103)

Explain how use of database systems evolved from programming with simple collections of data files.

Chapter 1

Describe the major components of a modern database system.

Describe the functionality provided by languages such as SQL.

Chapter 9

Give examples of interactions with database systems that are relevant to computer engineering.

Computer Science Curricula 2013 (https://www.acm.org/binaries/content/assets/education/cs2013_web_final.pdf)

Chapters

Information Management (IM) (Page 113)

IM/Database Systems (Pages 113-114)

1. Explain the characteristics that distinguish the database approach from the approach of programming with data files. [Familiarity]

2. Describe the most common designs for core database system components including the query optimizer, query executor, storage manager, access methods, and transaction processor. [Familiarity]

3. Cite the basic goals, functions, and models of database systems. [Familiarity]

4. Describe the components of a database system and give examples of their use. [Familiarity]

5. Identify major DBMS functions and describe their role in a database system. [Familiarity]

6. Explain the concept of data independence and its importance in a database system. [Familiarity]

7. Use a declarative query language to elicit information from a database. [Usage]

8. Describe facilities that databases provide supporting structures and/or stream (sequence) data, e.g., text. [Familiarity]

[Elective]

9. Describe major approaches to storing and processing large volumes of data. [Familiarity]

1. Chapter 1

2.

3. Chapter 2

4. Chapter 11

5. Chapter 11

6. Chapter 3

7. Chapter 9

8.

9.

IM/Relational Databases (Pages 115-116)

1. Prepare a relational schema from a conceptual model developed using the entity- relationship model. [Usage]

2. Explain and demonstrate the concepts of entity integrity constraint and referential integrity constraint (including definition of the concept of a foreign key). [Usage]

3. Demonstrate use of the relational algebra operations from mathematical set theory (union, intersection, difference, and Cartesian product) and the relational algebra operations developed specifically for relational databases (select (restrict), project, join, and division). [Usage]

4. Write queries in the relational algebra. [Usage]

5. Write queries in the tuple relational calculus. [Usage]

6. Determine the functional dependency between two or more attributes that are a subset of a relation. [Assessment]

7. Connect constraints expressed as primary key and foreign key, with functional dependencies. [Usage]

8. Compute the closure of a set of attributes under given functional dependencies. [Usage]

9. Determine whether a set of attributes form a superkey and/or candidate key for a relation with given functional dependencies. [Assessment]

10. Evaluate a proposed decomposition, to say whether it has lossless-join and dependency-preservation. [Assessment]

11. Describe the properties of BCNF, PJNF, 5NF. [Familiarity]

12. Explain the impact of normalization on the efficiency of database operations especially query optimization. [Familiarity]

13. Describe what is a multi-valued dependency and what type of constraints it specifies. [Familiarity]

1. Chapter 4

Chapter 5

2. Chapter 3

Chapter 6

3. Chapter 10

4. Chapter 10

5. Chapter 10

6. Chapter 7

7. Chapter 7

8. Chapter 7

9. Chapter 7

10. Chapter 5

11. Chapter 7

12. Chapter 7

13. Chapter 7

IM/Query Languages (Page 116)

1. Create a relational database schema in SQL that incorporates key, entity integrity, and referential integrity constraints. [Usage]

2. Use SQL to create tables and retrieve (SELECT) information from a database. [Usage]

3. Evaluate a set of query processing strategies and select the optimal strategy. [Assessment]

4. Create a non-procedural query by filling in templates of relations to construct an example of the desired query result. [Usage]

5. Embed object-oriented queries into a stand-alone language such as C++ or Java (e.g., SELECT Col.Method() FROM Object). [Usage]

6. Write a stored procedure that deals with parameters and has some control flow, to provide a given functionality. [Usage]

1. Chapter 9

2. Chapter 9

3.

4. Chapter 12

5. Chapter 12

Chapter 13

6. Chapter 12

Computer Science Curricula 2023³ (https://dl.acm.org/doi/pdf/10.1145/3664191)

Bloom⁴

Chapters

DM-Data: The Role of Data and the Data Life Cycle (Page 115)

CS Core⁵ 1. The Data Life Cycle: Creation-Processing-Review/Reporting Retention/Retrieval Destruction

Illustrative Learning Outcomes

ILO CS Core 1. Identify the five stages of the Data Life Cycle.

Evaluate

DM-Core: Core Database Systems Concepts (Pages 115-116)

Explain

CS Core 1. Purpose and advantages of database systems

Chapter 3

CS Core 2. Components of database systems

Chapter 11

CS Core 3. Design of Core DBMS functions (e.g., query mechanisms, transaction management, buffer management, access methods)

Chapter 11

CS Core 4. Database architecture, data independence, and data abstraction

Chapter 11

CS Core 5. Transaction management

Chapter 11

CS Core 6. Normalization

Chapter 7

CS Core 7. Approaches for managing large volumes of data (e.g., NoSQL database systems, use of MapReduce)

CS Core 8. How to support CRUD-only applications

Chapter 15

CS Core 9. Distributed databases/cloud-based systems

CS Core 10. Structured, Semi-structured, and unstructured data

CS Core 11. Use of a declarative query language

KA Core 12. Systems supporting structured and/or stream content

Illustrative Learning Outcomes

ILO CS Core 1. Identify at least four advantages that using a database system provides.

Chapter 1

ILO CS Core 2. Enumerate the components of a (relational) database system.

Chapter 11

ILO CS Core 3. Follow a query as it is processed by the components of a (relational) database system.

Chapter 11

ILO CS Core 4. Defend the value of data independence.

Chapter 2

ILO CS Core 5. Compose a simple select-project-join query in SQL.

Chapter 9

ILO CS Core 6. Enumerate the four properties of a correct transaction manager.

Chapter 11

ILO CS Core 7. Describe the advantages for eliminating duplicate repeated data.

Chapter 7

ILO CS Core 8. Outline how MapReduce uses parallelism to process data efficiently.

ILO CS Core 9. Evaluate the differences between structured and semi/unstructured databases.

DM-Modeling: Data Modeling (Pages 116-117)

Develop and Explain

CS Core 1. Data modeling

Chapter 4

CS Core 2. Relational data model

Chapter 4

Chapter 5

KA Core 3. Conceptual models (e.g., entity-relationship, UML diagrams)

Chapter 4

Chapter 5

KA Core 4. Semi-structured data models (expressed using DTD, XML, or JSON Schema, for example)⁶

Non-core 5. Spreadsheet models

Chapter 1

Non-core 6. Object-oriented models

Chapter 1

Non-core 6a. GraphQL

Non-core 7. New features in SQL

Chapter 9

Non-core 8. Specialized Data Modeling topics

Non-core 8a. Time series data (aggregation, join)

Non-core 8b. Graph data (link traversal)

Non-core 8c. Techniques for avoiding inefficient raw data access (e.g., “avg daily price”): materialized views and special data structures (e.g., Hyperloglog, bitmap)

Non-core 8d. Geo-Spatial data (e.g., GIS databases)

Illustrative Learning Outcomes

ILO CS Core 1. Describe the components of the relational data model.

Chapter 5

ILO CS Core 2. Model 1:1, 1:n, and n:m relationships using the relational data model.

Chapter 6

ILO KA Core 3. Describe the components of the E-R (or some other non-relational) data model.

Chapter 5

ILO KA Core 4. Model a given environment using a conceptual data model.

Chapter 4

ILO KA Core 5. Model a given environment using the document-based or key-value store-based data model.

DM-Relational: Relational Databases (Pages 117-118)

Explain and Develop

CS Core 1. Entity and referential integrity: Candidate key, superkeys

Chapter 5

Chapter 6

CS Core 2. Relational database design

Chapter 5

KA Core 3. Mapping conceptual schema to a relational schema

Chapter 5

KA Core 4. Physical database design: file and storage structures

Chapter 1

KA Core 5. Introduction to Functional dependency theory.

Chapter 7

KA Core 6. Normalization Theory

Chapter 7

KA Core 6a. Decomposition of a schema; lossless join, and dependency-preservation properties of a decomposition

Chapter 7

KA Core 6b. Normal forms (BCNF)

Chapter 7

KA Core 6c. Denormalization (for efficiency)

Chapter 7

Non-core 7. Functional dependency theory

Chapter 7

Non-core 7a. Closure of a set of attributes

Chapter 7

Non-core 7b. Canonical Cover

Chapter 7

Non-core 8. Normalization theory

Chapter 7

Non-core 8a. Multi-valued dependency (4NF)

Chapter 7

Non-core 8b. Join dependency (PJNF, 5NF)

Chapter 7

Non-core 8c. Representation theory

Illustrative Learning Outcomes

ILO CS Core 1. Describe the defining characteristics behind the relational data model.

Chapter 5

ILO CS Core 2. Comment on the difference between a foreign key and a superkey.

Chapter 5

ILO CS Core 3. Enumerate the different types of integrity constraints.

Chapter 3

Chapter 6

ILO KA Core 4. Compose a relational schema from a conceptual schema which contains 1:1, 1:n, and n:m relationships.

Chapter 6

ILO KA Core 5. Map appropriate file structure to relations and indices.

ILO KA Core 6. Describe how functional dependency theory generalizes the notion of key.

Chapter 7

ILO KA Core 7. Defend a given decomposition as lossless and or dependency preserving.

Chapter 7

ILO KA Core 8. Detect which normal form a given decomposition yields.

Chapter 7

ILO KA Core 9. Comment on reasons for denormalizing a relation.

Chapter 7

DM-Querying: Query Construction (Page 118)

Develop

CS Core 1. SQL Query Formation

Chapter 9

CS Core 1a. Interactive SQL execution

CS Core 1b. Programmatic execution of an SQL query

Chapter 13

KA Core 2. Relational Algebra

Chapter 10

KA Core 3. SQL

Chapter 9

KA Core 3a. Data definition including integrity and other constraint specifications.

Chapter 9

KA Core 3b. Update sublanguage

Non-core 4. Relational Calculus

Chapter 1

Non-core 5. QBE and 4^th-generation environments

Non-core 6. Different ways to invoke non-procedural queries in conventional languages.

Chapter 13

Non-core 7. Introduction to other major query languages (e.g., XPATH, SPARQL)

Non-core 8. Stored procedures

Chapter 13

Illustrative Learning Outcomes

ILO CS Core 1. Compose SQL queries that incorporate select, project, join, union, intersection, set difference, and set division.

Chapter 9

ILO CS Core 2. Determine when a nested SQL query is correlated or not.

ILO CS Core 3. Iterate over data retrieved programmatically from a database via an SQL query

ILO KA Core 4. Define, in SQL, a relation schema, including all integrity constraints and delete/update triggers.

Chapter 9

ILO KA Core 5. Compose an SQL query to update a tuple in a relation.

DM-Processing: Query Processing (Pages 118-119)⁷

Develop

KA Core 1. Page structures

KA Core 2. Index structures

KA Core 2a. B+ trees

KA Core 2b. Hash indices: static and dynamic

KA Core 2c. Index creation in SQL

KA Core 3. File structures

KA Core 3a. Heap files

KA Core 3b. Hash files

KA Core 4. Algorithms for query operators

KA Core 4a. External Sorting

KA Core 4b. Selection

KA Core 4c. Projection⁸; with and without duplication elimination

KA Core 4d. Natural Joins: Nested loop, Sort-merge, Hash join

KA Core 4e. Analysis of algorithm efficiency

KA Core 5. Query transformations

KA Core 6. Query optimization

KA Core 6a. Access paths

KA Core 6b. Query plan construction

KA Core 6c. Selectivity estimation

KA Core 6d. Index-only plans

KA Core 7. Parallel Query Processing (e.g., parallel scan, parallel join, parallel aggregation)

KA Core 8. Database tuning/performance

KA Core 8a. Index selection

KA Core 8b. Impact of indices on query performance

KA Core 8c. Denormalization⁹

Illustrative Learning Outcomes

ILO KA Core 1. Describe the purpose and organization of both B+ tree and hash index structures.

ILO KA Core 2. Compose an SQL command to create an index¹⁰ (any kind).

ILO KA Core 3. Specify the steps for the various query operator algorithms: external sorting, projection with duplicate elimination, sort-merge join, hash-join, block nested-loop join.

ILO KA Core 4. Derive the run-time¹¹ (in I/O requests) for each of the above algorithms.

ILO KA Core 5. Transform a query in relational algebra¹² to its equivalent appropriate for a left-deep, pipelined execution.

ILO KA Core 6. Compute selectivity estimates for a given selection and/or join operation.

ILO KA Core 7. Describe how to modify an index structure to facilitate an index-only operation for a given relation.

ILO KA Core 8. For a given scenario decide on which indices to support for the efficient execution of a set of queries.

ILO KA Core 9. Describe how DBMSs leverage parallelism to speed up query processing by dividing the work across multiple processors or nodes

DM-Internals: DBMS Internals (Pages 119-120)

Explain

KA Core 1. DB Buffer Management.

Chapter 11

KA Core 2. Transaction Management

Chapter 11

KA Core 2a. Isolation Levels

Chapter 11

KA Core 2b. ACID

Chapter 11

KA Core 2c. Serializability

Chapter 11

KA Core 2d. Distributed Transactions

Chapter 11

KA Core 3. Concurrency Control

Chapter 11

KA Core 3a. 2-Phase Locking

Chapter 11

KA Core 3b. Deadlocks handling strategies

Chapter 11

KA Core 3c. Quorum-based consistency models

KA Core 4. Recovery Manager

Chapter 11

KA Core 4a. Relation with Buffer Manager

Chapter 11

Non-core 5. Concurrency Control

Chapter 11

Non-core 5a. Optimistic concurrency control

Chapter 11

Non-core 5b. Timestamp concurrency control

Chapter 11

Non-core 6. Recovery Manager

Chapter 11

Non-core 6a. Write-Ahead logging

Chapter 11

Non-core 6b. ARIES recovery system (Analysis, REDO, UNDO)

Illustrative Learning Outcomes

KA Core 1. Describe how a DBMS manages its Buffer Pool.

Chapter 11

KA Core 2. Describe the four properties for a correct transaction manager.

Chapter 11

KA Core 3. Outline the principle of serializability.

DM-NoSQL: NoSQL Systems (Pages 120-121)

Explain

KA Core 1. Why NoSQL? (e.g., Impedance mismatch between Application [CRUD] and RDBMS)

Chapter 4

Chapter 8

Chapter 15

KA Core 2. Key-Value and Document data model

Chapter 8

Non-core 3. Storage systems (e.g., Key-Value systems, Data Lakes)

Chapter 8

Non-core 4. Distribution Models (Update and Read, Quorum consistency, CAP theorem)

Non-core 5. Graph Databases

Chapter 8

Non-core 6. Consistency Models (Update and Read, Quorum consistency, CAP theorem)

Non-core 7. Processing model (e.g., Map-Reduce, multi-stage map-reduce, incremental map-reduce)

Non-core 8. Case Studies: Cloud storage systems (e.g., S3); Graph databases; “When not to use NoSQL”

Illustrative Learning Outcomes

ILO KA Core 1. Develop a use case for the use of NoSQL over RDBMS

Chapter 4

Chapter 8

ILO KA Core 2. Describe the defining characteristics behind Key-Value and Document-based data models

Chapter 8

DM-Security: Data Security and Privacy (Page 121)¹³

Explain

CS Core 1. Differences between data security and data privacy.

CS Core 2. Protecting data and database systems from attacks, including injection attacks such as SQL injection

Chapter 13

CS Core 3. Personally identifying information (PII) and its protection.

CS Core 4. Ethical considerations in ensuring the security and privacy of data.¹⁴

KA Core 5. Need for, and different approaches to securing data at rest, in transit, and during processing.¹⁵

KA Core 6. Database auditing and its role in digital forensics.

KA Core 7. Data inferencing and preventing attacks.

KA Core 8. Laws and regulations governing data security and data privacy

Non-core 9. Typical risk factors and prevention measures for ensuring data integrity

Non-core 10. Ransomware and prevention of data loss and destruction.

Illustrative Learning Outcomes

KA Core 1. Describe the differences in the goals for data security and data privacy.

KA Core 2. Identify and mitigate risks associated with different approaches to protecting data.

KA Core 3. Describe legal and ethical considerations of end-to-end data security and privacy.

KA Core 4. Develop a database auditing system given risk considerations.

KA Core 5. Apply several data exploration approaches to understanding unfamiliar datasets.

DM-Analytics: Data Analytics (Page 121-122)

Explain

KA Core 1. Exploratory data techniques (motivation, representation, descriptive statistics, visualizations)

KA Core 2. Data science lifecycle: business understanding, data understanding, data preparation, modeling, evaluation, deployment, and user acceptance

KA Core 3. Data mining and machine learning algorithms: e.g., classification, clustering, association, regression

KA Core 4. Data acquisition and governance.

KA Core 5. Data security and privacy considerations

KA Core 6. Data fairness and bias

KA Core 7. Data visualization techniques and their use in data analytics

KA Core 8. Entity Resolution

Illustrative Learning Outcomes

KA Core 1. Describe several data exploration approaches, including visualization, to understanding unfamiliar datasets.

KA Core 2. Apply several data exploration approaches to understanding unfamiliar datasets.

KA Core 3. Describe basic machine learning/data mining algorithms and when they are appropriate for use.

KA Core 4. Apply several machine learning/data mining algorithms.

KA Core 5. Describe legal and ethical considerations in acquiring, using, and modifying datasets.

KA Core 6. Describe issues of fairness and bias in data collection and usage.

DM-Distributed: Distributed Databases/Cloud Computing (Page 122)

Non-core 1. Distributed DBMS

Non-core 1a. Distributed data storage

Non-core 1b. Distributed query processing

Non-core 1c. Distributed transaction model

Non-core 1d. Homogeneous and heterogeneous solutions

Non-core 1e. Client-server distributed databases

Non-core 2. Parallel DBMS

Non-core 2a. Parallel DBMS architectures: shared memory, shared disk, shared nothing

Non-core 2b. Speedup and scale-up, e.g., use of the MapReduce processing model

Non-core 2c. Data replication and weak consistency models

DM-Unstructured: Semi-structured and Unstructured Databases (Pages 122-123)

Non-core 1. Vectorized unstructured data (text, video, audio, etc.) and vector storage

Non-core1a. TF-IDF Vectorized with ngram

Non-core 1b. Word2Vec

Non-core 1c. Array database or array data type handling

Non-core 2. Semi-structured databases (e.g., JSON)

Non-core 2a. Storage

Non-core 2ai. Encoding and compression of nested data types

Non-core 2b. Indexing

Non-core 2bi. Btree, skip index, Bloom filter

Non-core 2bii. Inverted index and bitmap compression

Non-core 2biii. Space filling curve indexing for semi-structured geo-data

Non-core 2c. Query processing for OLTP and OLAP use cases

Non-core 2ci. Insert, Select, update, and delete tradeoffs

DM-SEP: Society, Ethics, and the Profession (Page 123)

Explain

KA Core 1. Enumerate three social and three legal issues related to large data collections.

KA Core 2. Describe the value of data privacy.

KA Core 3. Identify the competing stakeholders with respect to data ownership.

KA Core 4. Enumerate three negative unintended consequences from a given (well known) data-centric application (e.g., Facebook, LastPass, Ashley Madison)

KA Core 5. Describe the meaning of data provenance and lineage.

KA Core 6. Identify how a database might contribute to data security as well as how it may introduce insecurities.

Cybersecurity Curricula 2017 (https://www.acm.org/binaries/content/assets/education/curricula-recommendations/csec2017.pdf)

Cybersecurity encompasses many areas such as database management. (Page 17)

There are no specific learning outcomes. The best list comes from the National Security Agency.

4.1 Knowledge Area: Data Security

This focuses on the protection of data at rest, during processing, and in transit.

CSEC2017 does have topics that address database security.

4.7 Knowledge Area: Organizational Security (Page 59)

This focuses on protecting organizations from cybersecurity threats and managing risk.

CSEC2017 does have topics that address this knowledge area:

• Risk: One topic is about identifying the information assets in an organization.
• Systems Administration
• Database system administration
• System hardening commonly used systems such as database systems.

Computing Competencies for Undergraduate Data Science Curricula (https://www.acm.org/binaries/content/assets/education/curricula-recommendations/dstf_ccdsc2021.pdf)¹⁶

Chapters

Data Mining (DM) (Page 74)

This involves the processing, analysis, and presentation of data in order to gain valuable information.

DM-Information Retrieval – T2 (Pages 80-81)

This is about identifying and retrieving information from a large data set. Some of the data may be in a database.

Students need to have knowledge of

• The techniques for creating and searching relational databases systems.
• Various relational, non-relational, and other database formats.

Chapter 9

Chapter 8

Skills

Create and use a relational database structure using SQL.

Chapter 9

Data Integrity (DPSIA/DI) (page 89)

This is about the completeness, accuracy, and consistency of data. One part of the data life cycle is storing and retrieving.

DPSIA/DI Logical Integrity – T1 (Page 89)

Students need to have knowledge of

• Types of integrity constraints in database systems
• Entity integrity, referential integrity, domain integrity, user-defined integrity

Chapter 3

Chapter 6

Programming, Data Structures, and Algorithms (PDA) (Page 111)

This is about the tools for data collection and analysis.

One competency is the need to write appropriate database queries.

PDA-Programming (Page 112-113)

Skills

Manipulate data from selected sources (e.g., databases, spreadsheets, text documents, XML) utilizing appropriate techniques (e.g., database queries, API calls, regular expressions).

Chapter 9

Chapter 12

Chapter 13

Software Development and Maintenance (SDM) (Page 119)

There is a statement that this area draws from CS2012 knowledge area on software engineering.

SDM-Software Design and Development (page 119)

Students need to have T1 level of knowledge of

• Integration with Information Management/Database systems

Chapter 12

Chapter 13

Skills (Page 120)

Describe how to integrate or interact with Information Management/Database Systems.

Chapter 12

Chapter 13

IS 2020: A Competency Model for Undergraduate Programs in Information Systems (https://www.acm.org/binaries/content/assets/education/curricula-recommendations/is2020.pdf)

Chapters

A3.2 Data / Information Competency Realm (Page 101)

A3.2.1 Competency Area – Data / Information Management (Page 101)

• Query the relational model (Page 102)

Chapter 9

• Design relational databases (Page 103)

Chapter 4

Chapter 5

• Programming database systems using functions and triggers (Page 103)

Chapter 12

• Secure a database (Page 103)

Chapter 12

• Compare tradeoffs of different concurrency modes (Page 103)

Chapter 8

• Develop non-relational models (Page 104)

Information Technology Curricula 2017 (IT2017) (https://www.acm.org/binaries/content/assets/education/curricula-recommendations/it2017.pdf)

Chapters

ITE-IMA Domain: Information Management (Page 56) for all listed competencies.)

Competencies

A. Express how the growth of the internet and demands for information have changed data handling and transactional and analytical processing, and led to the creation of special purpose databases. (Requirements)

Chapter 1

B. Design and implement a physical model based on appropriate organization rules for a given scenario including the impact of normalization and indexes. (Requirements and development)

Chapter 9

C. Create working SQL statements for simple and intermediate queries to create and modify data and database objects to store, manipulate and analyze enterprise data. (Testing and performance)

Chapter 9

D. Analyze ways data fragmentation¹⁷, replication, and allocation affect database performance in an enterprise environment. (Integration and evaluation)

E. Perform major database administration tasks such as create and manage database users, roles and privileges, backup, and restore database objects to ensure organizational efficiency, continuity, and information security. (Testing and performance)

Roles were mentioned in Chapter 11, but the usage part was not done.

Chapter 12

Subdomains (Page 92)

L1: A minimal degree of engagement.

L2: A medium degree of engagement.

L3: A large degree of engagement.

ITE-IMA-01 Perspectives and impact [L1] (Page 92 for this section.)

a. Describe how data storage and retrieval has changed over time.

Chapter 1

b. Justify the advantages of a database approach compared to traditional file processing.

Chapter 1

c. Describe how the growth of the internet and demands for information for users outside the organization (customers and suppliers) impact data handling and processing.

Chapter 1

d. Tell a brief history of database models and their evolution.

Chapter 1

ITE-IMA-02 Data-information concepts [L2] (Page 92 for this section.)

a. Describe the role of data, information, and databases in organizations.

Chapter 2

b. Compare and use key terms such as: information, data, database, database management system, metadata, and data mining.

Chapter 2

c. Illustrate data quality, accuracy, and timeliness, and explain how their absence will impact organizations.

Chapter 6

d. Describe mechanisms for data collection and their implications (automated data collection, input forms, sources).

e. Describe basic issues of data retention, including the need for retention, physical storage, backup, and security.

ITE-IMA-03 Data modeling [L3] (Page 92 for this section.)

a. Design Entity Relationship diagrams based on appropriate organizational rules for a given scenario.

Chapter 5

Chapter 6

b. Describe the relationship between a logical model and a physical model.

Chapter 4

c. Evaluate importance of database constraints.

Chapter 3

d. Design a physical model for the best performance including impact of normalization and indexes¹⁸.

e. Compare and contrast the differences and similarities between the relational and the dimensional data modeling (OLTP vs. OLAP)

ITE-IMA-04 Database query languages [L3] (Page 92 for this section.)

a. Create, modify, and query database objects using the Structured Query Language (SQL).

Chapter 9

b. Perform filtering and sorting data using various clauses including where, order by, between, like, group by, and having.

Chapter 9

c. Use joins to select data across multiple tables.

Chapter 9

d. Use embedded SQL queries.

Chapter 12

e. Perform calculations in a query using calculated fields and aggregate functions.

Chapter 9

f. Create updatable and non-updatable views

Chapter 12

ITE-IMA-05 Data organization architecture [L3] (Page 92 for this section.)

a. Demonstrate select, project, union, intersection, set difference, and natural join relational operations using simple example relations provided.

Chapter 9

b. Contrast and compare relational databases concepts and non-relational databases including object-oriented, XML, NewSQL and NoSQL databases.

Chapter 8

c. Express the relationship between functional dependencies and keys, and give examples.

Chapter 7

d. Evaluate data integrity and provide examples of entity and referential integrity.

Chapter 3

Chapter 6

e. Analyze how data fragmentation, replication and allocation affect database performance.

ITE-IMA-06 Special-purpose databases [L1] (Page 92 for this section.)

a. Describe major concepts of object oriented, XML, NewSQL, and NoSQL databases.

Chapter 8

b. Demonstrate an understanding of online analytical processing and data warehouse systems.

c. Describe methods of data mining and what insights may be gained by these methods.

ITE-IMA-07 Managing the database environment [L2] (Page 92 for this section.)

a. Contrast and compare data administration and database administration.

b. Describe tasks commonly performed by database administrators.

c. Create and manage database users, roles, and privileges¹⁹.

d. Consider the concept of database security and backup and recovery.

Chapter 3

e. Evaluate the importance of metadata in database environment.

Chapter 3

Software Engineering 2014 (https://www.acm.org/binaries/content/assets/education/se2014.pdf )

From page 27, the cognitive skill level for each topic is specified as follows:

• Knowledge (k): Remembering previously learned material. Test observation and recall of information; that is, “bring to mind the appropriate information” (such as dates, events, places, knowledge of major ideas, and mastery of subject matter).

• Comprehension (c): Understanding information and the meaning of material presented. For example, being able to translate knowledge to a new context, interpret facts, compare, contrast, order, group, infer causes, predict consequences, and so forth.

• Application (a): Using learned material in new and concrete situations. For example, using information, methods, concepts, and theories to solve problems requiring the skills or knowledge presented.

The exact details are not provided.

Chapters

Computing Essentials (Page 28)

This includes the computer science foundations that support software product design and construction.

CMP.cf.10 Database fundamentals Comprehension coverage. And is essential part of the core. (Page 29)

Chapter 2

Software Design (Page 32)

DES.dd.2 Database design At the application level. And is an essential part of the core.

Data Administration (DBA)

The intent of the Data Administration Knowledge Unit is to provide students with methods to protect the confidentiality, integrity, and availability of data throughout the data life cycle.

Chapters

Outcomes

To complete this KU, students should be able to:

1. Draw and describe a data and information lifecycle, identifying specific and general security issues at all stages.

2. Define and evaluate data and information quality, accessibility, and utility.

3. Examine how the origination, change, distribution, storage, and deletion of information is managed and secured.

4. Compare and contrast data and information ownership, stewardship, management, possession, and governance.

5. Outline the role of data and information classification in security.

1

2

3

4

5

Database Management Systems (DMS)

The intent of the Database Management Systems Knowledge Unit is to provide students with the skills to utilize database management system to solve specific problems

Chapters

Outcomes

To complete this KU, students should be able to:

1. Compare and contrast database types including relational, hierarchical, distributed, and other models.

2. Describe the role of a database, a DBMS, and a database server within a complex system supporting multiple applications.

3. Apply SQL to create and administer databases and to manipulate the data they contain.

4. Describe DBMS access controls, privilege levels, and security principles and apply them to a simple database.

5. Outline common structures for storing data in a database management system.

6. Design and deploy a simple database for a specified application.

1. Chapter 2

2. Chapter 2

3. Chapter 9

4. Chapter 12

5

6. This is the running project.

Databases (DAT)

The intent of the Databases Knowledge Unit is to teach students how database systems are used, managed, and issues associated with protecting the associated data assets

Chapters

Outcomes

To complete this KU, students should be able to:

1. Describe the role of a database, a database management system (DBMS), and a database server within a complex system supporting one or more applications.

2. Outline different models for databases and cases where they may be used.

3. Identify and describe common security concerns in databases and database management systems

1. Chapter 2

2. Chapter 2

3.