BCS Professional Certificate in Data Analysis

Duration: 
2 days
Codes: 
BCS,PCDA

Overview

This course is intended to enable business analysts to define data requirements with detailed understanding of what is required and a rigorous approach.

The course will provide business analysts with knowledge and understanding of data analysis activities and techniques designed to elicit and analyse data requirements and inherent business rules and how to define the structure of the data to meet business needs.

Key areas of the course include:

  • Building and understanding two types of data models - Entity Relationship Diagrams and Class Models
  • Normalisation of data and why this is a useful approach
  • Validation of data requirements
  • Examination on the afternoon of day 2

Please do note that the course timetable is designed to include coverage of new content up to around mid-afternoon on day 2. Delegates should be prepared to spend around 1 -2 hours in the evening on homework and revision activities. This may include activities set by the instructor as appropriate.

Target Audience:

This certification is relevant for anyone wishing to gain an understanding of data analysis and techniques that maybe be applied when analysing business data. It is likely to be of benefit to business analysts, systems analysts and technical architects and solution architects. Project managers working on data-oriented projects may also find it a useful certification Note that if you are intending to work towards the BCS Advanced Diploma in Business Analysis then you must already have the International Diploma in Business Analysis.

Audience

  • This certification is relevant for anyone wishing to gain an understanding of data analysis and techniques that maybe be applied when analysing business data. It is likely to be of benefit to business analysts, systems analysts and technical architects and solution architects. Project managers working on data-oriented projects may also find it a useful certification
  • Note that if you are intending to work towards the BCS Advanced Diploma in Business Analysis then you must already have the International Diploma in Business Analysis.

Skills Gained

  • Define data analysis as a tool for a business analyst
  • Explain the purpose of data analysis and modelling
  • Identify the components of different data modelling techniques
  • Interpret a data model
  • State business rules within data analysis artefacts
  • Define the process and rules used to derive third normal form
  • Evaluate data sets against normalisation rules

Prerequisites

Prerequisites for Data Analysis

This 2-day specialist course leads to the BCS Professional Certificate in Data Analysis.

An understanding of projects would be useful but is not essential.

Prerequisites for including this course as part of the Advanced Diploma in Business Analysis:

If you are planning to work towards obtaining the Advanced Diploma then you must already hold the BCS International Diploma in Business Analysis and provide further evidential criteria, see below for details.

How do you obtain the Advanced Diploma?

Anyone who holds the BCS International Diploma in Business Analysis can begin working towards the BCS Advanced Diploma. There are three elements to be achieved in order to be awarded the Advanced Diploma:

  • Gain certifications in four subject areas across three skill domains
  • Provide evidence of a minimum of five years' experience in business analysis
  • Provide evidence of engaging with the BA community.

Exam Requirements

Course Outline

  • Concepts and Principles of Data Analysis and Modelling
  • Definitions of terms – data, data analysis, data model
  • Rationale for analysing and modelling data
  • Techniques used in data analysis:
  • Entity relationship modelling
  • Analysis class modelling
  • Normalisation Approaches to data analysis and modelling:
  • Derived from business needs: 'top-down'
  • Derived from data sources: ' bottom-up Application of data analysis artefacts:
  • Business modelling
  • System modelling (existing and required)
  • Impact analysis

Communication and training

  • Entity Relationship Modelling
  • Content of an entity relationship model
  • Identification of entities and attributes
  • Entity types and entity occurrences
  • Attribute types and attribute occurrences
  • Simple and compound keys
  • Relationships:
  • Cardinality (1:1, 1:M, M:M)
  • Optionality
  • Exclusivity
  • Recursion

Naming relationships

Super-types and sub-types

  • Rationalising Data
  • Normalisation process and rules:
  • Unnormalised (UNF)
  • First normal form (FNF)
  • Second normal form (SNF)

Third normal form (TNF)

Definition of the TNF tests

Rationalisation of TNF results from multiple data sources

Development of the TNF model

  • Analysis Class Modelling
  • Objects and classes
  • Structure of a class: name, attributes, operations
  • Associates and multiplicity
  • Naming associations
  • Generalisation
  • Validation Techniques
  • Cross-referencing matrices: CRUD matrix
  • Data navigation paths

Thinking about Onsite?

If you need training for 3 or more people, you should ask us about onsite training. Putting aside the obvious location benefit, content can be customised to better meet your business objectives and more can be covered than in a public classroom. It's a cost effective option.

Submit an enquiry from any page on this site, and let us know you are interested in the requirements box, or simply mention it when we contact you.

Upcoming Dates

  • GREEN This class is Guaranteed To Run.
  • SPVC - Self-Paced Virtual Class.
  • Click a Date to Enroll.
Course Location Days Cost Date
Onsite
Onsite2 1000 £1000 2019-01-18
London
London2 1000 £1000 2019-02-18
London
London2 1000 £1000 2019-02-18