BCS Professional Certificate in Data Analysis

Concepts, Principles, Practices, Techniques and Tools for Analysing and Modelling Data. Select Course Date and Time Based on Your Convenience!

GBP
250

Instructor-led, Online

Duration: 16 Hours

Course Code: TXV-BCS-DA3

Skill Level: Intermediate

BCS Professional Certificate in Data Analysis

Overview

In the digital age of rapidly changing technologies and megatrends, data is regarded as the new goldmine of organisations and rightly so. Over the past few decades, businesses have been investing effort, time and money in collecting, storing and curating different types of data. However to truly harness the power of data, IT teams should not only define and implement policies and procedures to manage data, but also transform and analyse the data so that actionable insights are drawn, leading to efficient decision-making and successful outcomes. Take the TEXAVI Course on BCS Professional Certificate in Data Analysis, enhance your data skills, raise your profile and super-charge your career potential!

Who can attend?

Anybody with or without work experience

IT professionals (eg., Developers, testers) considering a move to BA role

Non-IT people who want to learn IT skills thinking of a career switch

Graduates and university students who aspire to get into IT industry

Students who have just passed their B. Tec, A-Levels or college studies

COURSE OUTLINE

Module 1: Introduction to Data Analysis

Module 2: Methods and Techniques in Data analysis

Module 3: Overview on Data Modelling

Module 4: Approaches in Data Modelling

Module 5: Entity Relationship Modelling

Module 6: Rationalising Data Using Normalisation

Module 7: Modelling Analysis Classes and Objects

Module 8: Data Validation Techniques

What will you learn?

By the end of this course, you will be able to:

Define data and explain the importance of data

Define data analysis and data modelling

State the rationale for analysing and modelling data

Highlight the techniques used in data analysis

Explain the approaches to data analysis and modelling

Describe top-down data modelling approaches

Describe bottom-up data modelling approaches

Specify the applications of business modelling

Discuss the steps involved in business modelling

Highlight the guiding principles of system modelling

Specify the applications of system modelling

Describe the different perspectives in system modelling

Discuss the types of system modelling and their uses

Functional modelling

Systems architecture

Business process modelling

Enterprise modelling

Define impact analysis and explain its applications

Elaborate on the methods of impact analysis

Traceability impact analysis

Dependency impact analysis

Experimental impact analysis

Explain the steps to conduct impact analysis

Discuss the importance of communication in data analysis

Explain the techniques involved in effective communication

Storytelling

Data visualisation

Critical thinking

Prevent data for impact

Clarity and concision

Discuss the importance of training in data analysis

Describe the applications of training in data analysis

Define entity-relationship model

Explain the content of an entity-relationship model

Describe how to identify entities and attributes

Explain the entity types and entity occurrences

Elaborate on the attribute types and attribute occurrences

Highlight the differences between simple and compound keys

Describe the different notations in ER model

Chen notation

Crow/Crow’s foot notation

Arrow notation

UML notation

State the definitions and purposes of different types of ERD models

Conceptual data model

Logical data model

Physical data model

Explain the steps involved in creating an ERD model

Specify the different attributes types and explain their uses

Simple attributes

Composite attributes

Single-valued attributes

Multi-valued attributes

Derived attributes

Key attributes

Stored attributes

Complex attributes

Define an entity occurrence and describe the different types

Explain how entities are classified as super-types and sub-types

Explain the cardinality (1:1, 1:M, M:M) in relationships among entities

Describe optionality in relationships among entities

Elaborate on exclusivity of relationships among entities

Explain the recursive relationship among entities

State the best practices in naming the relationships

Define normalisation process and expand on the rules

State the purpose, advantages and disadvantages of data redundancy

Explain the different types of data anomalies

State the definition, rules and applications for first normal form (FNF)

State the definition, rules and applications for second normal form (SNF)

State the definition, rules and applications for third normal form (TNF)

Define the third normal form (TNF) tests

Explain rationalisation of TNF results from multiple data sources

Describe the steps involved in the development of TNF model

Define classes and objects in the context of data models

Highlight the different types of objects

Boundary object

Entity object

Control object

Define boundary classes and objects and explain how to find them

Define entity classes and objects and explain how to find them

Define control classes and objects and explain how to find them

Describe the structure of a class- name, attributes, operations

State the definition of associations and how to name them

Specify definition of multiplicity and its link to association

Explain the process of naming associations

Define generalisation and describe steps in implementing generalisation

Specify the purpose of data validation and state data validation techniques

Define cross-referencing matrices and give some examples

Explain the role, purpose and structure of CRUD matrix

What do you need?

There are no pre-requisites for this course. There is no need for any prior experience, working knowledge or awareness of software development or projects experience. The course is suitable for experienced professionals working in the industry or academia, aspirants and early stage professionals, as well as students in universities and colleges. Professionals and aspirants from technology, business, operations or sales are all welcome to explore and understand the agile methodologies alongside their concepts and principles.

WHAT'S INCLUDED?

24×7 access to TEXAVI’s high quality course content

Practical insights from real life IT projects

Course completion certificate

Case studies, examples and illustrations

Interactive quizzes and challenges

Job aids, resources and tools

Access to TEXAVI’s collaborative digital platform

Why Texavi?

TEXAVI is a proven leader in delivering non-coding IT learning, worldwide

We are not just trainers, but practising IT professionals with 25+ years of work exp

Our courses get you job-ready with practical and real-time insights

Qualify for certificates upon completion and complete our assessments

Pave way for industry-recognised certifications

Access to treasure of Texavi’s high-quality, content-rich resources and materials

Get discount voucher to our popular courses on Udemy

24×7 access to Texavi’s interactive platform with personalised content

Sample Course Video

TEXAVI Tests

Test Your Knowledge

Take the Texavi Tests and challenge yourself, simply click the below links and start the interactive quiz…

Trainer Profile

Your trainer for this course is Pardha Saradhi Mantravadi. Pardha is a seasoned and well-qualified trainer, coach, mentor, influencer and thought leader. He has rich and varied IT-industry experience of 25 years, working in working in different roles as a Business Analysis professional with blue-chip organisations viz., HSBC, Deutsche Bank, Dyson, Asda, Cambridge University Press, Roche, King’s College London , Royal Society of Chemistry etc. Pardha delivers his training sessions by blending the concepts and principles with practical insights from real-life projects and programs…click here to view the complete trainer profile

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