BCS Professional Certificate in Data Analysis Eğitimi

Prerequisites for Data Analysis

• It is recommended that delegates should have completed, or have knowledge to the level of, the BCS International Business Analysis Diploma or the BCS Solutions Development Diploma, before attempting this course
• 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:

This course is one of the 4 BCS professional certificates offered by QA which can be combined and lead to 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.

Bu sertifikasyon, iş verilerini analiz ederken uygulanabilecek veri analizi ve tekniklerini anlamak isteyenler ile ilgilidir. İş analistleri, sistem analistleri, teknik mimarlar ve çözüm mimarları için faydalı olması muhtemeldir. Veri odaklı projeler üzerinde çalışan proje yöneticileri de bunu faydalı bir sertifikasyon olarak görebilirler.

BCS İş Analizinde İleri Düzey Diploma alanında daha fazla çalışmayı amaçlıyorsanız İş Analizi Uluslararası Diploması’na sahip olmalısınız.

Data analysis for business analysts

• The context of data and importance to the organisation
• Application of data analysis
• Data analysis and business analysis

Principles of data analysis

• The rationale for modelling data
• Techniques for data analysis : Entity relationship modelling, Class diagrams, Data normalisation

Modelling data

• Grouping data through entities and classes
• Values of data (attributes)
• Relationships/associations between data items
• Business rules governing data relationships (multiplicity etc.)

Normalisation of data

• Rules for reaching third normal form
• Drawing models using third normal form
• Identifying keys

Validating the data model

• Cross referencing
• CRUD
• Data navigation paths

• 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