Question 1

What is data quality?

Accepted Answer

Data quality is the degree to which data is accurate, complete, valid, consistent, timely and unique, making it fit for its intended use. Poor data quality can cost organisations between 10% and 30% of revenue. Strong data quality management involves profiling, cleansing, contracting and ongoing monitoring.

Question 2

What is data governance?

Accepted Answer

Data governance is the framework of policies, processes, roles and standards that define how data is managed, used and protected across an organisation. It encompasses data ownership, stewardship, data dictionaries and compliance with standards such as DAMA DMBoK.

Question 3

What is data lineage?

Accepted Answer

Data lineage is a comprehensive, end-to-end view of the flow, transformation and consumption of data within an organisation, essential for auditability, regulatory compliance and understanding the impact of data changes.

Question 4

What is Master Data Management (MDM)?

Accepted Answer

Master Data Management (MDM) is a structured approach to creating and maintaining a single, authoritative golden record for critical data entities such as citizens, patients, customers or assets, resolving duplication and inconsistency across an organisation.

Question 5

What is metadata?

Accepted Answer

Metadata is descriptive information that describes the structure, content, meaning or usage of other data. It is central to effective data governance, enabling discoverability, consistent definitions and data quality management.

Question 6

What is a data warehouse?

Accepted Answer

A data warehouse is a specialised database that consolidates historical data from multiple source systems to support strategic decision-making and analytical reporting, providing a single reliable source of truth for analytics.

Question 7

What is ETL (Extract, Transform, Load)?

Accepted Answer

ETL is a data integration approach where data is transformed prior to being loaded into the target system. It is a foundational pattern for data warehousing and migration that ensures data is cleansed and conformed before landing in the target environment.

Question 8

What is ELT (Extract, Load, Transform)?

Accepted Answer

ELT is a data integration approach in which raw data is loaded into the target system first, then transformed within it using the target system's own processing power. It is commonly used with cloud-native platforms such as Snowflake or BigQuery.

Question 9

What is GDPR?

Accepted Answer

GDPR (General Data Protection Regulation) is a key EU data protection and privacy regulation governing the processing of personal data. UK GDPR mirrors the EU legislation with some differences. Compliance areas include data masking, lineage mapping, DPIAs and subject access requests.

Question 10

What is a Data Protection Impact Assessment (DPIA)?

Accepted Answer

A DPIA is a structured risk assessment conducted to support compliance with UK GDPR, particularly before data migration or when storing, processing and using sensitive personal data.

Question 11

What is PII (Personally Identifiable Information)?

Accepted Answer

Personally Identifiable Information (PII) is sensitive data that identifies or defines an individual, including names, addresses and medical records, that must be protected under regulations such as UK GDPR and the Data Protection Act.

Question 12

What is a data contract?

Accepted Answer

A data contract is a formal agreement between data producers and consumers specifying mutual obligations with regards to data acquisition, storage, processing and usage, typically including standardised schema, automated checks and feedback processes.

Question 13

What is data masking?

Accepted Answer

Data masking and redaction are techniques that obfuscate Personally Identifiable Information (PII) or sensitive data to keep data functional while enabling compliant, controlled sharing, particularly in development, test and analytics environments.

Question 14

What is data profiling?

Accepted Answer

Data profiling is a set of analytical techniques for exploring data to identify potential quality issues such as inconsistent formatting, out-of-range values, duplicate records and missing data. It is typically conducted at the outset of migration and data quality engagements.

Question 15

What is synthetic data?

Accepted Answer

Synthetic data is data created through rule-based simulations or Generative AI to closely mimic real-world data without exposing personally identifiable information, enabling safe testing and collaboration while maintaining GDPR compliance.

Question 16

What is a data clean room?

Accepted Answer

A data clean room is an environment that enables privacy-preserving data collaboration between organisations, allowing secure data sharing and joint analysis without exposing sensitive records.

Question 17

What is artificial intelligence (AI)?

Accepted Answer

Artificial intelligence (AI) is the broad field of computer science focused on building systems that simulate human intelligence, encompassing reasoning, problem-solving, language understanding and decision-making. It applies statistical modelling, deep learning and machine learning methods to answer complex questions or automate tasks.

Question 18

What is machine learning (ML)?

Accepted Answer

Machine learning is a subset of AI in which systems learn patterns from data and improve their performance over time without being explicitly programmed. It includes techniques such as regression, classification and clustering, used for applications including churn prediction and anomaly detection.

Question 19

What is generative AI?

Accepted Answer

Generative AI is a subset of deep learning in which models are trained to produce new content such as text, images, audio, code or video that resembles the patterns found in their training data. It is powered by architectures such as large language models (LLMs) and diffusion models.

Question 20

What are Large Language Models (LLMs)?

Accepted Answer

Large Language Models (LLMs) are advanced generative AI models used to generate text-based synthetic data, code and content. They can be integrated into services to enable natural language interaction and analysis of unstructured data.

Question 21

What is MLOps?

Accepted Answer

MLOps is the application of DevOps principles to the machine learning lifecycle, automating and streamlining data preparation, model training, deployment, monitoring and maintenance to help organisations move ML models reliably from experimentation to production.

Question 22

What is deep learning?

Accepted Answer

Deep learning is a subset of machine learning that uses multi-layered neural networks to learn patterns from large amounts of data. It powers technologies such as image recognition, natural language processing and speech recognition.

Question 23

What is a data engineer?

Accepted Answer

A data engineer is a technical role responsible for designing, building and maintaining data pipelines and infrastructure that enable reliable data ingestion, transformation and storage, ensuring data is accessible and ready for analytics.

Question 24

What is a data scientist?

Accepted Answer

A data scientist is a specialist who applies statistical methods, machine learning and advanced analytics to extract insights, build predictive models and solve complex data problems, helping organisations move from descriptive reporting to forecasting and optimisation.

Question 25

What is a data architect?

Accepted Answer

A data architect is a role responsible for designing the overall structure of data systems, including data models, integration patterns and platform architecture, ensuring platforms align with organisational strategy and support long-term growth.

Question 26

What is a data analyst?

Accepted Answer

A data analyst is a role focused on exploring, analysing and visualising data to generate insights that support business decision-making through dashboards, reports and exploratory analysis.

Question 27

What is a data steward?

Accepted Answer

A data steward is the person responsible for maintaining data definitions on behalf of a data owner, ensuring standards, accuracy and consistency across an organisation. The role is a core component of data governance frameworks.

Question 28

What is a data owner?

Accepted Answer

A data owner is the person or organisation with authority over a data definition, deciding what data should be held and how it should be defined. Formalising data ownership is a key component of data governance frameworks.

Question 29

What is Snowflake?

Accepted Answer

Snowflake is a cloud-based data platform that unifies data warehousing, data lakes, data engineering and data sharing into a single managed service, enabling organisations to store and analyse large volumes of data without managing infrastructure.

Question 30

What is SQL (Structured Query Language)?

Accepted Answer

SQL is the standard database language defined in ISO/IEC 9075, containing constructs for data definition, querying and manipulation. It is the primary language used by relational database management systems.

Question 31

What is a relational database?

Accepted Answer

A relational database stores information in tables made up of rows and columns, with relationships enforced through primary and foreign keys. SQL is the standard language for querying relational databases.

Question 32

What is a star schema?

Accepted Answer

A star schema is a widely used schema modelling framework for data warehouses, organising data into a central fact table surrounded by dimension tables to optimise query performance and reduce costs.

Question 33

What is a data vault?

Accepted Answer

A data vault is a proven schema modelling framework for long-term historical data storage that provides a flexible and auditable approach to data warehouse design.

Question 34

What is normalisation in database design?

Accepted Answer

Normalisation is the process of structuring a relational database to reduce duplication and improve data integrity by organising attributes and relations according to progressively stricter normal forms: 1NF, 2NF and 3NF.

Question 35

What is RBAC (Role-Based Access Control)?

Accepted Answer

Role-Based Access Control (RBAC) is a security approach that assigns data access permissions based on user roles, applying the principle of least privilege to minimise exposure of sensitive information.

Question 36

What is OLAP (Online Analytical Processing)?

Accepted Answer

OLAP is a category of database system designed for complex analytical queries across large volumes of historical data, optimised for retrieval and aggregation. Examples include Snowflake, BigQuery, Redshift and SAS.

Question 37

What is version control in data engineering?

Accepted Answer

Version control is the practice of tracking and managing changes to files over time, enabling collaboration, audit trails and the ability to roll back to earlier versions. In data engineering it covers schema, pipeline and data versioning, not just code.

Question 38

What is DevOps?

Accepted Answer

DevOps is a set of practices, tools and cultural principles that automates and integrates software development and IT operations to enable faster, more reliable delivery of data and technology solutions.

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