Learning outcome
1.1

1.1 Information strategy
1.2

1.2 Advice and guidance
1.3

1.3 Business strategy and planning
1.4

1.4 Technical strategy and planning
2.1

2.1 Business change implementation
2.2

2.2 Business change management
2.3

2.3 Relationship management
2.4

2.4 Skills management
3.1

3.1 Systems development
3.2

3.2 Human factors
3.3

3.3 Installation and integration
4.1

4.1 Service strategy
4.2

4.2 Service design
4.3

4.3 Service transition
4.4

4.4 Service operation
5.1

5.1 Supply management
5.2

5.2 Quality and conformance
6.1

6.1 Sales and marketing
6.2

6.2 Client support
A1

Plan effective big data storage and processing for specific business applications.
A2

Use appropriate tools to analyse, process and visualize data for big data management and analytics.
A3

Present big data management scenarios using oral and written communication skills and include ethical considerations.
K1

Describe defining characteristics, categories, examples and challenges of big data.
K2

Illustrate key storage data, data types and documents for big data management.
K3

Explain basic theories and techniques that underpin big data management such  as  management issues, strategies, interface models, infrastructures and related frameworks.
S1

Demonstrate skills in managing data using related analytical tools.
S2

Manage data using analytical tools.
S3

Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.
Learning outcome
1.1

<p>ICT Professional Knowledge</p>

1.2

<p>ICT Problem Solving</p>

2.1

<p>Technology Resources</p>

2.2

<p>Technology Building</p>

2.3

<p>ICT Management</p>

A1

Plan effective big data storage and processing for specific business applications.
A2

Use appropriate tools to analyse, process and visualize data for big data management and analytics.
A3

Present big data management scenarios using oral and written communication skills and include ethical considerations.
K1

Describe defining characteristics, categories, examples and challenges of big data.
K2

Illustrate key storage data, data types and documents for big data management.
K3

Explain basic theories and techniques that underpin big data management such  as  management issues, strategies, interface models, infrastructures and related frameworks.
S1

Demonstrate skills in managing data using related analytical tools.
S2

Manage data using analytical tools.
S3

Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.
Learning outcome
1.1

Strategy and planning
1.2

Security and privacy
1.3

Governance, risk and compliance
1.4

Advice and guidance
2.5

Change implementation
2.6

Change analysis
2.7

Change planning
3.8

Systems development
3.9

Data and analytics
3.10

User experience
3.11

Content management
3.12

Computational science
4.13

Technology management
4.14

Service management
4.15

Security services
5.16

People management
5.17

Skills management
6.18

Stakeholder management
6.19

Sales and marketing
A1

Plan effective big data storage and processing for specific business applications.
A2

Use appropriate tools to analyse, process and visualize data for big data management and analytics.
A3

Present big data management scenarios using oral and written communication skills and include ethical considerations.
K1

Describe defining characteristics, categories, examples and challenges of big data.
K2

Illustrate key storage data, data types and documents for big data management.
K3

Explain basic theories and techniques that underpin big data management such  as  management issues, strategies, interface models, infrastructures and related frameworks.
S1

Demonstrate skills in managing data using related analytical tools.
S2

Manage data using analytical tools.
S3

Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.
Learning outcome
1.1

ICT Fundamentals

1.2

ICT Infrastructure

1.3

Information & Data Science and Engineering

1.4

Computational Science and Engineering

1.5

Application Systems

1.6

Cyber Security

1.7

ICT Projects

1.8

ICT Management and Governance

2.1

Professional ICT Ethics
2.2

Impacts of ICT

2.3

Working Individually and in ICT development teams

2.4

Professional Communication

2.5

The Professional ICT Practitioner

A1

Plan effective big data storage and processing for specific business applications.
A2

Use appropriate tools to analyse, process and visualize data for big data management and analytics.
A3

Present big data management scenarios using oral and written communication skills and include ethical considerations.
K1

Describe defining characteristics, categories, examples and challenges of big data.
K2

Illustrate key storage data, data types and documents for big data management.
K3

Explain basic theories and techniques that underpin big data management such  as  management issues, strategies, interface models, infrastructures and related frameworks.
S1

Demonstrate skills in managing data using related analytical tools.
S2

Manage data using analytical tools.
S3

Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.
Learning outcome
1.1

<p>1.1 Modelling methods and processes.</p>

2.1

<p>2.1 Ethics</p>

2.2

<p>2.2 Professionalism</p>

2.3

<p>2.3 Teamwork concepts and issues</p>

2.4

<p>2.4 Communication</p>

2.5

<p>2.5 Societal issues</p>

2.6

<p>2.6 History and status of discipline</p>

3.1

<p>3.1 Programming</p>

3.2

<p>3.2 Human-computer interaction</p>

3.3

3.3 Systems development
3.4

<p>3.4 Systems acquisition</p>

4.1

<p>4.1 Hardware and software fundamentals</p>

4.2

<p>4.2 Data and information management</p>

4.3

<p>4.3 Networking</p>

5.1

<p>5.1 Service management</p>

6.1

<p>6.1 ICT Governance</p>

6.2

<p>6.2 ICT Project management</p>

A1

Plan effective big data storage and processing for specific business applications.
A2

Use appropriate tools to analyse, process and visualize data for big data management and analytics.
A3

Present big data management scenarios using oral and written communication skills and include ethical considerations.
K1

Describe defining characteristics, categories, examples and challenges of big data.
K2

Illustrate key storage data, data types and documents for big data management.
K3

Explain basic theories and techniques that underpin big data management such  as  management issues, strategies, interface models, infrastructures and related frameworks.
S1

Demonstrate skills in managing data using related analytical tools.
S2

Manage data using analytical tools.
S3

Analyse and compare programming interface models for managing big data, such as Hadoop and MapReduce.