5. 251201004-KM-05, Data, Databases and Data Scraping, NQF Level 4, Credits 4
5.1 Purpose of the Knowledge Module
The main focus of the learning in this knowledge module is to build an understanding of data and databases
and giving meaning to data through data processing, analysis and visualisation
The learning will enable learners to demonstrate an understanding of:
KM-05-KT01 : Data and data processing 15%
KM-05-KT02 : Databases, data storage and access to data 20%
KM-05-KT03 : Structured query language (SQL) 10%
KM-05-KT04 : Data scraping 15%
KM-05-KT05 : Software for analysing and visualising data 25%
KM-05-KT06 : Data security 15%
5.2 Guidelines for Topics
5.2.1 KM-05-KT01 : Data and data processing 15%
Topic elements to be covered include:
KT0101 Value of data
KT0102 Data analysis for RPA: Importance of analysis
KT0103 Data sourcing:
Data sources
Data types
Reliable data
Automated data collection
KT0104 Refining data:
Missing data
Data misalignments
Separating useful data from the rest
KT0105 Flaws in data:
Commission
Omission
Perspective
Bias
Frame of reference
KT0106 Limits of data acquisition
KT0107 Data:
Setting up data
Data interactions
Assigned to different fields
Internal Assessment Criteria and Weight
IAC0101 Data and data processing principles are understood and explained
(Weight 15%)

5.2.2 KM-05-KT02 : Databases, data storage and access to data 20%
Topic elements to be covered include:
251201004 – Occupational Certificate: Robotic Processing Automation (RPA) Developer Page 21 of 108
KT0201 Database:
definition, components, function, types, characteristics of good databases, structure and
challenges
KT0202 Data:
storage, characteristics of quality data
KT0203 Data:
collection warehousing, mining and managing concepts
KT0204 Relational database design
KT0205 Database design tools
KT0206 Create, design and modify relational database
KT0207 Import and export data
KT0208 Design and create queries
KT0209 Data driven solutions
Internal Assessment Criteria and Weight
IAC0201 Database concepts, principles and characteristics are described
IAC0202 Data concepts, principles and characteristics are described
IAC0203 Database design concepts, principles and tools are described
IAC0204 Access to data is described
(Weight 20%)

5.2.3 KM-05-KT03 : Structured query language (SQL) 10%
Topic elements to be covered include:
KT0301 SQL programming language
KT0302 SQL code constructs to perform database transactions
KT0303 Storing, retrieving, managing or manipulating the data inside a relational database
management system (RDBMS)
Internal Assessment Criteria and Weight
IAC0301 The application of SQL is explained
(Weight 10%)

5.2.4 KM-05-KT04 : Data scraping 15%
Topic elements to be covered include:
KT0401 Concept and definition
KT0402 Purpose of data scraping
KT0403 Data scraping tools
KT0404 Legal issues
KT0405 Web scraping procedure:
Find the URL to scrape
Inspecting the page
Find the data you want to extract
Write the code
Run the code and extract the data
Store the data in the required format
251201004 – Occupational Certificate: Robotic Processing Automation (RPA) Developer Page 22 of 108
KT0406 Libraries used for web scraping
Internal Assessment Criteria and Weight
IAC0401 The principles and purpose of data scraping are explained
(Weight 15%)

5.2.5 KM-05-KT05 : Software for analysing and visualising data 25%
Topic elements to be covered include:
KT0501 Reporting
KT0502 Tables
KT0503 Pivot tables and pivot charts
KT0504 Dashboards
KT0505 Hierarchies and time data
KT0506 The data model
KT0507 Importing data from files
KT0508 Importing data from databases
KT0509 Importing data from reports
KT0510 Creating and formatting measures
KT0511 Visualizing data
Internal Assessment Criteria and Weight
IAC0501 The importance of analysing and visualising data is reasoned
(Weight 25%)

5.2.6 KM-05-KT06 : Data security 15%
Topic elements to be covered include:
KT0601 Definition
KT0602 Purpose of protecting data
KT0603 Process for protecting data
KT0604 Unauthorised access
KT0605 Data corruption
KT0606 Data security solutions
Internal Assessment Criteria and Weight
IAC0601 The importance of data security is reasoned
(Weight 15%)

5.3 Provider Programme Accreditation Criteria
Physical Requirements:
The provider must have lesson plans and structured learning material or provide learners with
access to structured learning material that addresses all the topics in all the knowledge modules as
well as the applied knowledge in the practical skills.
QCTO/ MICT SETA requirements
Human Resource Requirements:
Lecturer/learner ratio of 1:20 (Maximum)
Qualification of lecturer (SME):
o NQF 6 in industry recognised qualifications with 1 year’s experience in the IT industry
o RPA vendor certification
Assessors and moderators: accredited by the MICT SETA
Legal Requirements:
Legal (product) licences to use the software for learning and training
OHS compliance certificate
Ethical clearance (where necessary)
5.4 Exemptions
No exemptions, but the module can be achieved in full through a normal RPL process