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Evidence Guide: ICTICT812 - Develop a business intelligence framework

Student: __________________________________________________

Signature: _________________________________________________

Tips for gathering evidence to demonstrate your skills

The important thing to remember when gathering evidence is that the more evidence the better - that is, the more evidence you gather to demonstrate your skills, the more confident an assessor can be that you have learned the skills not just at one point in time, but are continuing to apply and develop those skills (as opposed to just learning for the test!). Furthermore, one piece of evidence that you collect will not usualy demonstrate all the required criteria for a unit of competency, whereas multiple overlapping pieces of evidence will usually do the trick!

From the Wiki University

 

ICTICT812 - Develop a business intelligence framework

What evidence can you provide to prove your understanding of each of the following citeria?

Elicit the business intelligence requirements

  1. Articulate the benefits of business intelligence
  2. Select the appropriate system development methodology, through the analysis of a range of options
  3. Critically evaluate the impact of business intelligence on the enterprise
  4. Select the appropriate business model for a data repository
  5. Adopt a metadata standard for the enterprise
  6. Establish the appropriate data analysis techniques
Articulate the benefits of business intelligence

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Select the appropriate system development methodology, through the analysis of a range of options

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Critically evaluate the impact of business intelligence on the enterprise

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Select the appropriate business model for a data repository

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Adopt a metadata standard for the enterprise

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Establish the appropriate data analysis techniques

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Direct the business intelligence data manipulation

  1. Identify the data sources and scope
  2. Evaluate and endorse the selected data-manipulation methods
  3. Critically review, and commit to, the feasibility of the architecture design
  4. Develop the acceptance criteria
  5. Endorse the selected data-modelling techniques and processes
  6. Endorse a load balancing algorithm for optimum processing
  7. Sign off the design specifications
Identify the data sources and scope

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Evaluate and endorse the selected data-manipulation methods

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Critically review, and commit to, the feasibility of the architecture design

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Develop the acceptance criteria

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Endorse the selected data-modelling techniques and processes

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Endorse a load balancing algorithm for optimum processing

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Sign off the design specifications

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Endorse the business intelligence solution architecture

  1. Ensure that the data-warehousing management techniques and processes are according to the specifications
  2. Lead the scoping of logical data models
  3. Supervise the selection of middleware tools
  4. Critically review, and commit to, a searchable data repository solution
Ensure that the data-warehousing management techniques and processes are according to the specifications

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Lead the scoping of logical data models

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Supervise the selection of middleware tools

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Critically review, and commit to, a searchable data repository solution

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Finalise the testing and accept the framework

  1. Finalise the physical data model
  2. Complete testing of the overall model
  3. Test the security
  4. Test the integrity
  5. Perform a user-acceptance test
Finalise the physical data model

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Complete testing of the overall model

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Test the security

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Test the integrity

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Perform a user-acceptance test

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Assessed

Teacher: ___________________________________ Date: _________

Signature: ________________________________________________

Comments:

 

 

 

 

 

 

 

 

Instructions to Assessors

Evidence Guide

ELEMENT

PERFORMANCE CRITERIA

Elements describe the essential outcomes.

Performance criteria describe the performance needed to demonstrate achievement of the element.

1. Elicit the business intelligence requirements

1.1 Articulate the benefits of business intelligence

1.2 Select the appropriate system development methodology, through the analysis of a range of options

1.3 Critically evaluate the impact of business intelligence on the enterprise

1.4 Select the appropriate business model for a data repository

1.5 Adopt a metadata standard for the enterprise

1.6 Establish the appropriate data analysis techniques

2. Direct the business intelligence data manipulation

2.1 Identify the data sources and scope

2.2 Evaluate and endorse the selected data-manipulation methods

2.3 Critically review, and commit to, the feasibility of the architecture design

2.4 Develop the acceptance criteria

2.5 Endorse the selected data-modelling techniques and processes

2.6 Endorse a load balancing algorithm for optimum processing

2.7 Sign off the design specifications

3. Endorse the business intelligence solution architecture

3.1 Ensure that the data-warehousing management techniques and processes are according to the specifications

3.2 Lead the scoping of logical data models

3.3 Supervise the selection of middleware tools

3.4 Critically review, and commit to, a searchable data repository solution

4. Finalise the testing and accept the framework

4.1 Finalise the physical data model

4.2 Complete testing of the overall model

4.3 Test the security

4.4 Test the integrity

4.5 Perform a user-acceptance test

Required Skills and Knowledge

ELEMENT

PERFORMANCE CRITERIA

Elements describe the essential outcomes.

Performance criteria describe the performance needed to demonstrate achievement of the element.

1. Elicit the business intelligence requirements

1.1 Articulate the benefits of business intelligence

1.2 Select the appropriate system development methodology, through the analysis of a range of options

1.3 Critically evaluate the impact of business intelligence on the enterprise

1.4 Select the appropriate business model for a data repository

1.5 Adopt a metadata standard for the enterprise

1.6 Establish the appropriate data analysis techniques

2. Direct the business intelligence data manipulation

2.1 Identify the data sources and scope

2.2 Evaluate and endorse the selected data-manipulation methods

2.3 Critically review, and commit to, the feasibility of the architecture design

2.4 Develop the acceptance criteria

2.5 Endorse the selected data-modelling techniques and processes

2.6 Endorse a load balancing algorithm for optimum processing

2.7 Sign off the design specifications

3. Endorse the business intelligence solution architecture

3.1 Ensure that the data-warehousing management techniques and processes are according to the specifications

3.2 Lead the scoping of logical data models

3.3 Supervise the selection of middleware tools

3.4 Critically review, and commit to, a searchable data repository solution

4. Finalise the testing and accept the framework

4.1 Finalise the physical data model

4.2 Complete testing of the overall model

4.3 Test the security

4.4 Test the integrity

4.5 Perform a user-acceptance test

Evidence of the ability to:

research and critically analyse the business intelligence requirements

review, analyse and direct, business intelligence data manipulation

review, critically analyse and endorse, the proposed business intelligence solution architecture

initiate and contrast the tests required for the intelligence framework, for final acceptance.

Note: If a specific volume or frequency is not stated, then evidence must be provided at least once.

To complete the unit requirements safely and effectively, the individual must:

evaluate the application of system development methodologies and other technical considerations including:

managing and using metadata

data modelling

data warehousing/back-end software alternatives

business analytics

business intelligence tools

analyse the organisational policies and procedures, as they apply to the business intelligence frameworks

discuss behaviour theories as they apply to business intelligence, including:

responsibility and achievement

affiliation management

motivation

appraise and evaluate, the business intelligence (BI) procedures

interpret the workplace and industry environmental conditions, as they apply to business intelligence.