What is the Data–Information–Knowledge model?
It describes how raw data becomes meaningful insight: data are raw facts; information is data in context; knowledge is information interpreted and applied through experience.
What are the stages of the Data Lifecycle?
Capture → store → use → share → archive → dispose. Each stage ensures data quality, security, and compliance.
Explain the Data Value Chain.
Data → analysis → curation → storage → usage → value creation. Each step adds structure, meaning, and business value.
Describe the Digital Transformation Framework.
It has six dimensions: strategy, organization, culture, technology, customer, and people. Together they align digital initiatives with business goals.
What are the key dimensions of Data Quality?
Accuracy, completeness, consistency, timeliness, and uniqueness — the foundation of reliable analytics and decision-making.
Explain the difference between Schema-on-Write and Schema-on-Read.
Schema-on-Write defines structure before storing data (data warehouses); Schema-on-Read applies structure when accessing data (data lakes).
Compare Data Warehouse, Data Lake, and Data Lakehouse.
Warehouse = structured data for reporting; Lake = raw data for flexibility; Lakehouse = combines both with governance and analytics performance.
Explain the Big Data 5V Model.
Big Data is characterized by volume, velocity, variety, veracity, and value — describing its scale, speed, diversity, reliability, and usefulness.
Describe the relationship between ERP, ETL, and BI systems.
ERP captures operational data; ETL extracts, transforms, and loads it into a central store; BI analyzes and visualizes it for decision-making.
What is the Digitalization Hierarchy?
Digitization converts analog to digital; Digitalization automates processes; Digital Transformation reshapes strategy and culture through technology.
Explain the link between Data Governance and IT Governance.
Data governance manages data quality, availability, and protection; IT governance aligns technology investments with strategic business goals.
Describe the components of a Smart System.
Smart systems combine physical elements, intelligence (software/algorithms), and connectivity — enabling them to sense, analyze, and act autonomously.
Explain the concept of the Internet of Things (IoT).
A network of connected devices that collect, exchange, and process data to enable automation and insight across systems.
Outline the Strategic Business Objectives of Information Systems.
Operational excellence, innovation in products/services, customer and supplier intimacy, improved decision-making, competitive advantage, and survival.
Describe the Data Governance Framework.
Defines policies, roles, responsibilities, and controls to ensure data quality, security, compliance, and value alignment.
Explain the Business Intelligence Model.
BI collects and transforms organizational data into dashboards, reports, and analytics that support operational and strategic decisions.
Describe the Digital Transformation Challenges Model.
Key barriers are data volume, financial cost, resistance to change, and lack of digital skills — spanning technical, cultural, and organizational levels.
Explain the Blockchain Model.
A distributed ledger where each transaction is stored in cryptographically secured, immutable blocks — ensuring transparency and trust.
Describe the Edge Computing Model.
Processes data close to the source device to minimize latency and bandwidth use — essential for real-time and autonomous applications.
Summarize the Cloud Computing Service Model.
Provides on-demand shared IT resources over the internet, typically via IaaS, PaaS, or SaaS models for scalability and flexibility.
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data and information manageemnt52
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Set 4 Management & Information Systems24
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Set 5 – Strategy & Digital Transformation19
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Set 6 – Finance & Reporting18
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Set 7 – Ethics & Value-Based Engineering (VBE)21
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Set 8 – Data Science & Modern Technologies21
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Set 9 - Smart Systems & Emerging Technology Integration19
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Set 10 – Finance & Reporting20
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Set 3 Data20
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Set 1 – IT Governance & Control17
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Business Process Management (BPM) & Process Mining30
