Diploma in Data Analysis Concepts Level 4

Diploma in Data Analysis Concepts - Level 4
The Diploma serves as the second module required for the Level 4 Data Analyst apprenticeship program and encompasses a wide range of relevant concepts, approaches, and techniques for Data Analysts.

Course Description

The Diploma serves as the second module required for the Level 4 Data Analyst apprenticeship program and encompasses a wide range of relevant concepts, approaches, and techniques for Data Analysts. In order to successfully complete the program, learners must demonstrate their comprehension and mastery of these topics.

Additionally, the Diploma is also available as a standalone program for individuals who wish to expand their knowledge and understanding of data analysis approaches and solutions.

Course Specifications

Course Content

Learners are expected to exhibit comprehension and mastery of Data Analysis and its fundamental architecture, principles, and techniques. The following key areas are integral to achieving this goal:

  1. Investigating various data types, including open/public data, administrative data, and research data.
  2. Comprehending the data lifecycle.
  3. Differentiating between structured and unstructured data.
  4. Recognising the significance of defining customer requirements clearly for data analysis.
  5. Understanding the potential quality issues that can arise with data and how to avoid and/or resolve them.
  6. Grasping the steps involved in performing regular data analysis tasks.
  7. Comprehending the range of data protection and legal issues.
  8. Exploring the basic principles of data structures.
  9. Studying the database system design, implementation, and maintenance.
  10. Comprehending the organisation’s data architecture.
  11. Acknowledging the importance of domain context for data analytics.
  • What is the course format and duration?
    Prospective candidates can pursue this diploma by enrolling on this BCS/NCFE accredited training course. The estimated total time required to complete the qualification is 600 hours.
  • What are the days and times of the course?
    Evenings only – 5:30 pm – 8:30pm, or
    Distance Learning only – times to be agreed on enrolment
  • Open Curriculum
    The Diploma is applicable to two types of learners: those who are registered for a Level 4 Data Analyst apprenticeship program and those who wish to acquire a comprehensive understanding of big data analytics up to Level 4 standards.
  • What qualifications will I get?
    – Level 4 Diploma in Data Analyst Concepts
  • Which Units will I be learning?
    The programme is modular and consists of a selection and mixture of units referred to as Knowledge, Skills and Behaviours (KSBs).
    The syllabus includes the identification of a percentage and K level for each top-level area. The percentage represents the exam coverage of that specific area, while the K level indicates the maximum level of knowledge that may be tested for that area.

All Knowledge (K), Skills (S) and Behaviours (B) units are mandatory for this qualifications, thus:

  • Unit 1 – Types of Data (10%, K2) 
  • Unit 2 – The Data Lifecycle (5%, K2)
  • Unit 3 – Structured and Unstructured Data (10%, K2)
  • Unit 4 – Requirements for Data Analysis (15%, K2)
  • Unit 5 – Quality Issues for Data Analysis (10%, K2)
  • Unit 6 – Data Analysis Tasks (15%, K3)
  • Unit 7 – Compliance and Audit Considerations (5%, K2)
  • Unit 8 – Data Structures (10%, K3)
  • Unit 9 – Database Design, Implementation, and Maintenance (10%, K3)
  • Unit 10 – Data Architecture (5%, K2)
  • Unit 11 – The Domain Context for Data Analytics (5%, K2)

Title: Business Analysis
Author: Cadle, J et al.
Publisher: BCS, The Chartered Institute for IT; 3rd edition
Publication Date: 22 Sept. 2014
ISBN-10: 178017277X
ISBN-13: 978-1780172774

Title: Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
Author: Han, J & Kamber, M
Publisher: Morgan Kaufmann; 3 edition
Publication Date: 25 July 2011
ISBN-10: 9380931913
ISBN-13:
978-9380931913

Title: Data Science for Business: What you need to know about data mining and data-analytic thinking
Author: Provost, F. & Fawcett, T.
Publisher: O’Reilly Media; 1 edition
Publication Date: 19 August 2013 
ISBN-10: 1449361323
ISBN-13: 978-1449361327

For apprenticeship learners, the selection criteria will be determined by the employer but will likely require 5 GCSEs, including English, mathematics, and a science or technology subject, along with relevant qualifications or experience, or an IT skills-based aptitude test. Prior to the endpoint assessment, apprentices must have achieved Level 2 English and Maths if not already attained.

For other learners, it is recommended that they have completed 5 GCSEs, including English, mathematics, and a science or technology subject, along with relevant qualifications or experience, or an IT skills-based aptitude test.

The examination is a one-hour multiple-choice test consisting of 40 questions, and it is closed book, meaning that no materials can be taken into the examination room. The passing grade is 26/40 (65%).

Upon successful completion of the course, candidates are awarded a Diploma in Data Analyst and may progress by direct-entry to the Higher Diploma course. Apprentices (and other candidates as the case may be) maybe absorbed by their employer and/or exit to other employment and do well vocationally.

All students are required to pay the following fees:

  • The full apprenticeship programme fee is: £15,000 for 2 years
  • Other independent candidates via Online/remote Learning fee is: £299 per module
  • Distance Learning fee: £399
  • FREE

    For further enquiries on any of the courses, please make contact on:

    Tel: +44(0)7414 253 997; +234(0)706 252 4962
    Email: admissions@mcbit.org

“I am Thanya, an engineering student at University of Greenwich,  I had the chance to meet and work with Patrick Justus since November thanks to the SPARK mentoring scheme. He has been a great mentor in this period and helped me with my career development and life skills development.”

Thanya K. Don

“I owe it to Patrick to set me on a career path and get me where I am today. Without Patrick’s influence, who knows where I might have been today.”

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