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CIT143Sciences2 Unitsintermediate

Introduction To Data Organisation And Management

This course introduces the fundamental principles of data organization and management. It explores the nature of data, information, and knowledge, and their interrelationships within information systems. Students will learn about data planning, policy making, definition, structuring, and quality control. The course also covers data storage, retrieval, analysis, and summarization techniques, equipping students with the skills to design and implement effective data management strategies in various contexts.

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120h
Study Time
13
Weeks
9h
Per Week
basic
Math Level
Course Keywords
Data OrganizationData ManagementInformation SystemsData QualityDatabase

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
➕
Math Level
Basic Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Data Concepts

2

Information Systems

3

Data Organization

4

Data Management

5

Data Quality Control

6

Database Systems

Total Topics6 topics

Requirements

Knowledge and skills recommended for success

Computer Fundamentals

💡 Don't have all requirements? Don't worry! Many students successfully complete this course with basic preparation and dedication.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assessments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Computer Based Test

Career Opportunities

Explore the career paths this course opens up for you

Data Analyst

Apply your skills in this growing field

Database Administrator

Apply your skills in this growing field

Information Manager

Apply your skills in this growing field

Records Manager

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

GovernmentHealthcareFinanceEducationTechnology

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Data, information and knowledge

2h

Unit 1: Data, information and knowledge

2 study hours
  • •Define data, information, and knowledge. Explore their relationships.
  • •Differentiate between data and precepts.
Week
2

Module 1: Data, information and knowledge

2h

Unit 2: Data, information and knowledge management

2 study hours
  • •Explain the purposes of data management.
  • •Describe data management activities in the context of the data life cycle.
  • •Explain the relationship between data management, information management and knowledge management.
Week
3

Module 1: Data, information and knowledge

2h

Unit 3: Information systems for data management

2 study hours
  • •Describe the goals, key features and processes of information systems.
  • •Explain how the goals of information systems are interwoven with those of data and information management.
  • •Explain the data management activities involved in the input-process-storage-output communication processes of information systems.
Week
4

Module 1: Data, information and knowledge

2h

Unit 4: Languages for data organization

2 study hours
  • •Explain the nature and importance of natural and special languages for social communication and data creation.
  • •Describe how the symbols, rules and usages of a language determine what and how data can be created for expressing information.
Week
5

Module 1: Data, information and knowledge

2h

Unit 5: Data representation in the computer

2 study hours
  • •Explain the binary number system, and how to add binary numbers.
  • •How computers use signals representing binary digits or bits to represent alphabetic, numeric and other characters.
  • •How images and pictures are captured and represented by computers.
  • •How sound and voice are captured and represented by computers.
Week
6

Module 2: Data planning and policy making

2h

Unit 6: Data planning and policy making

2 study hours
  • •Explain the role of data planning in the process of data management.
  • •Describe aims of information resources management.
  • •Discuss the importance of data and information policies in data management.
  • •Describe the types of information that data policy manuals usually contain.
Week
7

Module 2: Data planning and policy making

2h

Unit 7: Data definition and structure

2 study hours
  • •Describe the differences between structured and unstructured data.
  • •Explain how data are pre-defined before being created or collected.
  • •Explain the different ways in which data can be subdivided into separately meaningful portions for ease of understanding and manipulation.
Week
8

Module 2: Data planning and policy making

2h

Unit 8: Data arrangement, grouping and modeling

2 study hours
  • •Arrange data using different orders of sorting.
  • •Describe a data model, and its purposes.
  • •Explain the hierarchical and network modes of arranging data.
  • •Arrange data using different sorting modes.
  • •Arrange data in either the hierarchical or network modes.
Week
9

Module 2: Data planning and policy making

2h

Unit 9: Data capture, acquisition and collection

2 study hours
  • •Distinguish between primary and secondary data.
  • •Describe the differences between data creation, collection and acquisition.
  • •Explain the importance of the different tasks involved in data collection.
  • •Describe and give examples of data collection instruments.
  • •Explain data capture and the devices for data capture.
Week
10

Module 3: Data quality control

2h

Unit 10: Data quality control - fundamental concepts

2 study hours
  • •Explain the importance of data quality control.
  • •Distinguish between the accuracy, validity and reliability of data.
  • •Distinguish between the accuracy and reliability of data collection instruments.
  • •Explain the importance of instruments and procedures in data quality control.
Week
11

Module 3: Data quality control

2h

Unit 11: Data quality control - context and strategies

2 study hours
  • •Explain the tasks involved in planning for data quality control.
  • •Explain the different data quality control contexts and strategies.
  • •Explain the methods that can be used for data quality control in laboratories research.
  • •Contrast human and computerized approaches to data quality control.
Week
12

Module 3: Data quality control

2h

Unit 12: Data storage media and organization

2 study hours
  • •Explain the importance of data storage, and the relationships between data storage and retrieval.
  • •Explain the types of media that can be used to store data.
  • •Describe how data are organized and stored in different types of paper documents.
  • •Explain how data are organized and stored on computer media such as hard disks, diskettes and compact disks.
Week
13

Module 3: Data quality control

4h

Unit 13: Data storage in computer databases

2 study hours
  • •Explain the importance of database management to an organization or information system.
  • •Explain the concepts of database, data tables, records and fields, as well as database forms, views and reports.

Unit 14: Creating and using databases: Common tasks

2 study hours
  • •Describe the common tasks in creating and using databases.
  • •Explain the database table concepts of field name, field type and field width, primary key field, etc.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Create a glossary of key terms from Units 1-5 to solidify understanding of fundamental concepts.

2

Practice designing data tables and defining field properties as covered in Units 7-8.

3

Review different data summarization methods from Unit 18 and apply them to sample datasets.

4

Focus on understanding the data management cycle from Unit 2 and its application in different contexts.

5

Study the different data quality control strategies from Units 10-11 and their importance in ensuring data integrity.

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