Implementing a Windows based data warehouse
CITY & GUILDS LIMITED
Vocational
This topic covers implementing a Windows-based data warehouse, including hardware requirements, ETL processes, and cloud solutions. It also includes using SQL Server tools like SSIS, DQS, and Master Data Services.
10
Learning Outcomes
29
Assessment Guidance
29
Key Skills
10
Key Terms
45
Assessment Criteria
Assessment criteria
City & Guilds Level 3 Diploma in ICT Systems Support
City & Guilds Level 2 Award in ICT Systems and Principles
City & Guilds Level 2 Diploma in ICT Professional Competence
City & Guilds Level 2 Certificate in ICT Systems Support
City & Guilds Level 4 Diploma For ICT Professionals (Systems and Principles)
City & Guilds Level 3 Diploma in ICT Professional Competence
City & Guilds Level 2 Diploma in ICT Systems Support
City & Guilds Level 3 Diploma in ICT Systems and Principles for IT Professionals
City & Guilds Level 3 Certificate in ICT Systems and Principles
City & Guilds Level 2 Diploma in ICT Systems and Principles for IT Professionals
Topic Overview
The City & Guilds Level 2 Diploma in ICT Systems Support is a vocational qualification designed to equip students with the practical skills and knowledge needed to provide effective technical support in an IT environment. This diploma covers a broad range of topics, including computer hardware, software installation, networking fundamentals, and customer service skills. It is ideal for students who wish to pursue a career as an IT support technician, helpdesk analyst, or network administrator, providing a solid foundation for further study or entry-level employment.
Throughout the course, you will learn how to diagnose and resolve common hardware and software issues, set up and maintain computer networks, and communicate effectively with users. The qualification emphasizes hands-on, real-world scenarios, ensuring that you can apply your learning immediately in a workplace setting. By the end of the diploma, you will be confident in supporting end-users, managing IT assets, and understanding the principles of cybersecurity and data protection.
This diploma fits into the wider subject of Computer Science by bridging the gap between theoretical concepts and practical application. While computer science focuses on algorithms, programming, and system design, ICT systems support is about the day-to-day operation and maintenance of those systems. It is a critical role in any organization, as efficient IT support minimizes downtime and maximizes productivity. Mastery of this diploma will also prepare you for advanced qualifications such as the City & Guilds Level 3 Diploma in ICT Systems Support or CompTIA A+ certification.
Key Concepts
Core ideas you must understand for this topic
- →Hardware components: Understanding the function and installation of CPUs, RAM, hard drives, power supplies, and motherboards, as well as peripheral devices like printers and scanners.
- →Operating systems: Installing, configuring, and troubleshooting Windows and Linux operating systems, including managing user accounts, file systems, and system updates.
- →Networking fundamentals: Knowledge of IP addressing, subnetting, DNS, DHCP, and the OSI model, along with setting up wired and wireless networks using routers and switches.
- →Customer service skills: Effective communication, active listening, and problem-solving techniques when dealing with end-users, including logging incidents and managing expectations.
- →Health and safety: Applying electrostatic discharge (ESD) precautions, safe lifting techniques, and understanding electrical safety when working with computer equipment.
Learning Objectives
What you need to know and understand
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
Assessment Criteria
Key criteria assessors look for in your portfolio
- Determine hardware requirements for a data warehouse.
- Implement an ETL solution using SSIS.
- Create an incremental ETL process.
- Use cloud data warehousing solutions appropriately.
- Apply Data Quality Services and Master Data Services.
- Identify hardware and software requirements for a data warehouse.
- Create an ETL solution using SSIS.
- Implement incremental ETL and data quality processes.
- Use cloud data warehousing and master data services.
- Assess hardware and software requirements for a data warehouse.
- Design and implement an ETL solution using SSIS.
- Implement incremental ETL processes for efficiency.
- Use Data Quality Services to cleanse and match data.
- Identifies hardware and software requirements for a data warehouse.
- Implements an ETL solution to extract, transform, and load data.
- Sets up incremental ETL processes for efficient data updates.
- Configures cloud data warehousing solutions appropriately.
- Uses Data Quality Services and Master Data Services effectively.
- Assess hardware requirements for a data warehouse implementation.
- Create an ETL solution using SQL Server Integration Services (SSIS).
- Implement an incremental ETL process to handle changing data.
- Use cloud data warehousing solutions like Azure Synapse.
- Apply Data Quality Services (DQS) and Master Data Services for data governance.
- Understand hardware requirements for a data warehouse.
- Implement a data warehouse and create an ETL solution.
- Implement an incremental ETL process.
- Use cloud data warehousing solutions.
- Use Data Quality Services and Master Data Services.
- Identifies hardware requirements for a data warehouse.
- Implements an ETL solution using SSIS.
- Creates an incremental ETL process.
- Uses Data Quality Services to cleanse data.
- Configures Master Data Services for data governance.
- Award credit for demonstrating a clear understanding of hardware sizing, including CPU, memory, storage (IOPS), and network considerations for a data warehouse workload.
- Award credit for successfully designing and deploying an SSIS package that performs extraction from a source, applies transformations (e.g., lookups, derivations), and loads into a dimensional model.
- Award credit for implementing an incremental ETL strategy using change data capture or timestamp-based delta detection and explaining how it optimizes performance.
- Identifies hardware requirements for a data warehouse.
- Implements an ETL solution using SSIS.
- Creates an incremental ETL process.
- Uses cloud data warehousing solutions appropriately.
- Applies Data Quality Services and Master Data Services.
- Understand data warehouse hardware requirements.
- Implement an ETL solution using SSIS.
- Use cloud data warehousing and Data Quality Services.
- Apply Master Data Services and manage SSIS packages.
Assessment Guidance
Guidance for achieving higher grades
- 💡Familiarise yourself with SSIS control flow and data flow.
- 💡Understand the difference between full and incremental loads.
- 💡Practice using DQS to cleanse data.
- 💡Practice using SQL Server Data Tools.
- 💡Understand star schema design.
- 💡Test ETL packages with sample data.
- 💡Practice building SSIS packages with different control flow tasks.
- 💡Understand the difference between staging and dimension tables.
- 💡Use DQS knowledge base for data standardisation.
- 💡Practice using SQL Server Integration Services (SSIS) for ETL.
- 💡Understand the difference between full and incremental loads.
- 💡Learn about cloud platforms like Azure for data warehousing.
- 💡Familiarise yourself with SSIS control flow and data flow components.
- 💡Understand the difference between staging and dimensional tables.
- 💡Practice setting up DQS knowledge bases and MDS models.
- 💡Practice creating SSIS packages with error handling.
- 💡Know the difference between on-premises and cloud solutions.
- 💡Understand the role of DQS in data cleansing.
- 💡Practice building SSIS packages step by step.
- 💡Understand the difference between full and incremental loads.
- 💡Familiarise yourself with cloud data warehouse services like Azure SQL DW.
- 💡In the practical assessment, document your ETL logic clearly with annotations in SSIS; explain why you chose specific transformations rather than just implementing them.
- 💡For the Business Intelligence section, link your data warehouse design to tangible business questions, demonstrating how dimensions and facts answer real organisational needs.
- 💡Understand the star schema and snowflake schema.
- 💡Practice creating SSIS packages with error handling.
- 💡Know the difference between on-premises and cloud solutions.
- 💡Practice building SSIS packages step by step.
- 💡Understand the role of each service in the data warehouse.
- 💡Test ETL processes with sample data.
- 💡When answering questions about troubleshooting, always follow a logical step-by-step process: identify the problem, establish a theory of probable cause, test the theory, implement a solution, verify full system functionality, and document findings. This structured approach is highly valued in exams.
- 💡For networking questions, be sure to memorize the OSI model layers and their functions. A common exam task is to match protocols or devices to the correct layer. Use mnemonics like 'Please Do Not Throw Sausage Pizza Away' to remember the order.
- 💡In customer service scenarios, always demonstrate empathy and professionalism. Use phrases like 'I understand how frustrating this must be' and explain technical issues in plain language. Examiners look for evidence of good communication skills.
Common Mistakes
Common errors to avoid in your coursework
- Underestimating storage and memory requirements.
- Poorly designed ETL processes causing data inconsistencies.
- Neglecting data quality checks.
- Confusing ETL with ELT.
- Neglecting data quality checks.
- Poor understanding of dimensional modelling.
- Ignoring data profiling before ETL design.
- Overlooking error handling in SSIS packages.
- Failing to test incremental loads with sample data.
- Incorrectly configuring ETL packages leading to data loss.
- Overlooking data quality issues during transformation.
- Failing to optimise cloud storage costs.
- Confusing ETL with ELT and their appropriate use cases.
- Neglecting data quality checks in the ETL pipeline.
- Overlooking incremental load logic, leading to full refreshes.
- Confusing ETL with ELT processes.
- Neglecting data quality checks in ETL.
- Overlooking incremental load strategies.
- Confusing ETL with ELT processes.
- Neglecting data quality checks in ETL.
- Overlooking incremental load logic.
- Students often confuse incremental load with full load, failing to implement proper watermark mechanisms or incorrectly handling updates and deletes, leading to data inconsistency.
- A frequent oversight is neglecting to configure Data Quality Services (DQS) knowledge bases before integration, resulting in poor data cleansing outcomes and downstream errors in reporting.
- Confuses ETL with ELT processes.
- Neglects data cleansing before loading.
- Fails to document SSIS package logic.
- Overlooking data quality issues in ETL.
- Misconfiguring cloud storage permissions.
- Failing to document data lineage.
- Misconception: 'All computer problems are caused by viruses.' Correction: While malware can cause issues, many problems stem from hardware failures, driver conflicts, or user error. Always run diagnostic tests before assuming a virus is the cause.
- Misconception: 'More RAM always makes a computer faster.' Correction: Adding RAM improves performance only if the system is currently running out of memory. If the CPU or storage is the bottleneck, extra RAM won't help. Use Task Manager to check memory usage first.
- Misconception: 'Static electricity isn't a big deal when handling components.' Correction: Electrostatic discharge can permanently damage sensitive electronics. Always use an anti-static wrist strap or mat, and touch a grounded metal object before handling components.
Frequently Asked Questions
Common questions students ask about this topic
Pass / Merit / Distinction Evidence Checklist
How your portfolio evidence is graded for CITY & GUILDS LIMITED Implementing a Windows based data warehouse
Every vocational unit is marked against named criteria rather than an exam percentage. Your tutor's brief lists the exact codes for this unit — here is what each band is asking you to do.
Pass (P)
Demonstrate baseline knowledge, accurate terminology, and core practical application.
Merit (M)
Provide detailed analysis, structured explanations, and clear workplace reasoning.
Distinction (D)
Deliver thorough evaluation, original problem solving, and fully justified recommendations.
Before You Start
Prior knowledge that will help with this topic
- •Basic computer literacy: Familiarity with using a computer, navigating the internet, and common software applications like word processors and spreadsheets.
- •Mathematics: Understanding of binary, decimal, and hexadecimal number systems, as well as basic arithmetic for calculating IP addresses and storage capacities.
- •Communication skills: Ability to read and write clearly in English, as you will need to document issues and interact with users.
Coursework AI Review
Paste your assignment brief and check your draft against its P/M/D criteria
Key Terminology
Essential terms to know
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
- Understand the requirements for data warehouse hardware, Be able to implement a data warehouse, Be abale to create an Extract, Transform and Load (ETL) Solution, Be able to implement an incremental ETL process, Be able to use a cloud data warehousing solution, Be able to use Data QualityServices (DQS), Be able to use Master Data Services, Be able to use SSIS packages, Understand Business Intelligence
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