NQF5 Robotics Processing Automation Developer (RPA) – 251201004-KM-05, Data, Databases and Data Scraping

SECTION 3: CURRICULUM COMPONENT SPECIFICATIONS – SECTION 3A: KNOWLEDGE MODULE SPECIFICATIONS

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