Paper 7

DATA MANAGEMENT INFORMATION SYSTEMS

This paper is intended to equip the candidate with the knowledge, skills and attitude that will enable him/her to oversee and control data management information systems and provide technical details to manage and implement organisational databases.

On completion, a candidate should be able to

Design and implements Database Management Systems
Develop entity-relationship diagrams, relational schemas, and data dictionaries for a database using a given set of business rules
Analyse Data Management Systems
Investigate new technologies that are transforming businesses in data management information systems
Determine the necessary application in an Enterprise Setup

Content

1
Introduction to Data Management Information Systems
1. 1.1
  Overview of data management and information systems
2. 1.2
  Data, Information, Knowledge and Wisdom (DIKW) pyramid
3. 1.3
  Functions of MIS
4. 1.4
  Database systems applications
5. 1.5
  Type of databases
6. 1.6
  DBMS architecture
7. 1.7
  Components of a DBMS
8. 1.8
  Facilities of a DBMS
2
Introduction to Management Information Systems
1. 2.1
  Elements of information systems
2. 2.2
  Characteristics of valuable information
3. 2.3
  Types of Information Systems
4. 2.4
  Business process and functions
5. 2.5
  Concepts and types of information systems
6. 2.6
  Elements of Information systems
7. 2.7
  Categories of information system
3
Data Management
1. 3.1
  Introduction to Data Management
2. 3.2
  Hierarchy of data and data types
3. 3.3
  Data organization techniques
4. 3.4
  Software Process models
4
Database Design and Entity-Relationship Model
1. 4.1
  Overview of database design process
2. 4.2
  Entity-Relationship (E-R) model
3. 4.3
  E-R diagrams
4. 4.4
  Relationships: One-to-one; one-to-many; many-to-many relationships (17)
5. 4.5
  E-R design issues
6. 4.6
  Weak entity sets
7. 4.7
  Unified Modelling Language(UML)
8. 4.8
  Case Study Implementation
5
Relational Database Design
1. 5.1
  Set operations
2. 5.2
  Aggregate functions
3. 5.3
  Features of a good relational design
4. 5.4
  Atomic design and first normal form
5. 5.5
  Decomposition using functional dependence
6. 5.6
  Functional decomposition theory
7. 5.7
  Algorithms for decomposition
8. 5.8
  Case study implementation
6
Structured Query Language (SQL)
1. 6.1
  Overview of SQL
2. 6.2
  Basic structure of SQL queries
3. 6.3
  Null values
4. 6.4
  Nested sub-queries
5. 6.5
  SQL data types and Schema
6. 6.6
  Integrity constraints
7. 6.7
  Data Definition Language
8. 6.8
  Data Manipulation Language
9. 6.9
  Joins
10. 6.10
  Authentication in SQL
11. 6.11
  Case study implementation
7
Database Storage and Querying
1. 7.1
  Storage and file structure
2. 7.2
  Indexing and hashing
3. 7.3
  Query processing
4. 7.4
  Query optimization
5. 7.5
  Case study implementation
8
Transaction Processing
1. 8.1
  Transactions and atomicity, consistency, isolation, durability (ACID) Properties
2. 8.2
  Transaction types and states
3. 8.3
  Concurrent access, control and recovery
4. 8.4
  Serializability and concurrency control
5. 8.5
  Concurrency control and locking techniques
6. 8.6
  Locking algorithms
7. 8.7
  Recovery systems
9
Data Integration
1. 9.1
  Data integration approaches
2. 9.2
  Overview of the data warehouse
3. 9.3
  Data modelling for warehouses (18)
4. 9.4
  Building a data warehouse
5. 9.5
  Types and functions of data warehouses
6. 9.6
  Challenges in implementing and managing data warehouses
7. 9.7
  Overview of data mining
8. 9.8
  Classification and clustering
9. 9.9
  Tools, techniques and applications of data mining
10. 9.10
  Virtual data integration
11. 9.11
  Case studies in Data Integration e.g. A Case Study on Model Driven Data
12. 9.12
  Integration for Data Centric Software Development
10
Object-based databases and Extensible Mark-up Language (XML)
1. 10.1
  Overview and complex types
2. 10.2
  Object–relational database management system (ORDBMS)
3. 10.3
  Structured types and inheritance in SQL
4. 10.4
  Overview, Structure of XML data
5. 10.5
  XML document schema
6. 10.6
  Querying and transformation
7. 10.7
  Application programming interface (API) to XML
8. 10.8
  XML data storage and XML Applications
11
Online Transactions Processing (OLTP), Online Analytical Processing (OLAP) and Data Warehousing
1. 11.1
  Overview of OLTP, OLAP and Data Warehouse
2. 11.2
  OLTP and OLAP difference
3. 11.3
  The role of OLAP in business intelligence
4. 11.4
  Overview of servers and data warehouse
5. 11.5
  Data warehouse characteristics and architecture
6. 11.6
  Multidimensional data model
7. 11.7
  Schemas of Multidimensional data models
8. 11.8
  Data Warehouse implementation
12
Data Mining for Business Intelligence
1. 12.1
  Overview of data mining concept
2. 12.2
  Knowledge Discovery in Databases (KDD) Process
3. 12.3
  Cross Industry Standard Process for Data Mining (CRISP-DM)
4. 12.4
  Key performance indicators (KPI) dashboards
5. 12.5
  Data Visualization
6. 12.6
  Case Study e.g. Implementing Business Intelligence System – A Case Study
13
Business processes, Innovations and process re-engineering
1. 13.1
  Overview of business process steps
2. 13.2
  Business processes documentation and management
3. 13.3
  Business process improvement
4. 13.4
  Business Process Management and International Organization for Standardization (ISO) Standards Alignment
5. 13.5
  Factors leading to innovations
6. 13.6
  Overview Business re-engineering and steps
7. 13.7
  Business Continuity Plan (BCP), objectives and phases (19)
14
Emerging issues in Data Management Information Systems
1. 14.1
  Databases that bridge SQL/NoSQL
2. 14.2
  Databases in the cloud/Platform as a Service
3. 14.3
  Automated management
4. 14.4
  Automated management
5. 14.5
  In-memory databases
6. 14.6
  Big Data
7. 14.7
  Business intelligence: