ICAICT712A
Develop a business intelligence framework

This unit describes the performance outcomes, skills and knowledge to manage business intelligence, including data mining and analysis.

Application

Senior managers in medium to large organisations apply analytical and strategic business knowledge to direct the strategic planning to meet current and future business needs.


Prerequisites

Not applicable.


Elements and Performance Criteria

1. Elicit business intelligence requirements

1.1 Articulate the benefits of business intelligence

1.2 Select appropriate system development methodology from a range of options

1.3 Evaluate impact of business intelligence on the enterprise

1.4 Select appropriate business model for data repository

1.5 Adopt a metadata standard for the enterprise

1.6 Establish appropriate data analysis techniques

2. Direct business intelligence data manipulation

2.1 Identify data sources and scope

2.2 Endorse selected data-manipulation methods

2.3 Review and commit to feasibility of architecture design

2.4 Develop acceptance criteria

2.5 Endorse selected data-modelling techniques and processes

2.6 Endorse a load balancing algorithm for optimum processing

2.7 Sign off design specifications

3. Endorse business intelligence solution architecture

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

3.2 Lead scoping of logical data models

3.3 Supervise selection of middleware tools

3.4 Review and commit to searchable data repository solution

4. Finalise testing and accept framework

4.1 Finalise physical data model

4.2 Complete testing overall model

4.3 Test security

4.4 Test integrity

4.5 Perform user-acceptance test

Required Skills

Required skills

analytical skills to evaluate information

literacy skills to:

conduct oral presentations to a group

demonstrate leadership in a group

prepare and overview reports

conflict-management skills to deal with grievances, disputes or disagreements

information technology skills to analyse and oversee research

initiative and enterprise skills to identify improvements to quality

planning and organisational skills to plan, prioritise and organise own work

problem-solving skills to resolve issues in the workplace

research skills to validate data and information.

Required knowledge

equity and diversity principles as they apply to the project

OHS requirements

organisational policy and procedures as they apply to the project

overview knowledge of behaviour theories:

responsibility, achievement as in Herzberg’s two factor

affiliation management after McClelland

motivation after Vroom

personal safety issues

public sector legislation, codes of practice and other formal agreements that directly impact on business operations

technical knowledge of business intelligence procedures

workplace and industry environment as it applies to project.

Evidence Required

The evidence guide provides advice on assessment and must be read in conjunction with the performance criteria, required skills and knowledge, range statement and the Assessment Guidelines for the Training Package.

Overview of assessment

Critical aspects for assessment and evidence required to demonstrate competency in this unit

Evidence of the ability to:

determine the human factors that need to be analysed when managing people and groups

conduct business meetings applying effective communication techniques

determine essential requirements of a product, applying quality management principles

monitor and implement training for staff

resolve problems and conflicts in a business environment

support human resource management program.

Context of and specific resources for assessment

Assessment must ensure access to:

a business intelligence focus

relevant enterprise documentation, including HR and quality management policies.

Where applicable, physical resources should include equipment modified for people with special needs.

Method of assessment

A range of assessment methods should be used to assess practical skills and knowledge. The following examples are appropriate for this unit:

direct observation of the candidate running a productive business meeting and using effective interview techniques

verbal or written questioning to assess the candidate’s required knowledge of:

business intelligence

data warehousing

data modelling

business domain

review of quality reports prepared by the candidate on the development of the business intelligence framework

evidence of candidate’s consultations with staff and management.

Guidance information for assessment

Holistic assessment with other units relevant to the industry sector, workplace and job role is recommended, where appropriate.

Assessment processes and techniques must be culturally appropriate, and suitable to the communication skill level, language, literacy and numeracy capacity of the candidate and the work being performed.

Indigenous people and other people from a non-English speaking background may need additional support.

In cases where practical assessment is used it should be combined with targeted questioning to assess required knowledge.


Range Statement

The range statement relates to the unit of competency as a whole. It allows for different work environments and situations that may affect performance. Bold italicised wording, if used in the performance criteria, is detailed below. Essential operating conditions that may be present with training and assessment (depending on the work situation, needs of the candidate, accessibility of the item, and local industry and regional contexts) may also be included.

Business intelligence may include:

analytics

benchmarking

business performance management

data mining

online analytical processing

predictive analytics

reporting

text mining.

System development methodology may include:

agile unified process (AUP)

prop-typing

rational unified process (RUP)

spiral

systems development life cycle (SDLC)

waterfall.

Metadata standard may include:

common warehouse meta-model (CWM)

data documentation initiative (DDI)

digital object identifier (DOI)

Dublin core

eGovernment Metadata Standard (E-GMS)

ISO 23081

ISO/IEC 11179

multimedia content description interface (MPEG-7)

online information exchange (ONIX).

Data-modelling techniques may include:

Bachman diagrams

Barker's notation

Chen's notation

data vault modelling (DVM)

Extended Backus-Naur form

IDEF1X

object role modelling (ORM)

object-relational mapping

relational model.

Load balancing algorithm may include:

biasing algorithm

round-robin algorithm.

Middleware may include:

application servers

web servers.

Data repository may include:

component-repository management

digital repository

information repository

repository open-service interface definition

software repository.


Sectors

General ICT


Employability Skills

This unit contains employability skills.


Licensing Information

No licensing, legislative, regulatory or certification requirements apply to this unit at the time of endorsement but users should confirm requirements with the relevant federal, state or territory authority.