MSc Data Analytics Overview 2024-2025

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Questions and Answers

What is the primary goal of Data Architecture in an enterprise?

To conduct market analysis

To design and maintain master blueprints for data needs (correct)

To analyze business processes

To implement security protocols

Which statement best describes data modeling?

A tool for data storage optimization

A method to represent data requirements in a precise form (correct)

A process to establish data backup protocols

A strategy for data encryption

Which of the following is NOT one of the common data modeling schemes?

Dimensional

Relational

Hierarchical (correct)

NoSQL

What does Enterprise Architecture provide to an organization?

A visual blueprint illustrating key interrelationships Signup and view all the answers

Which of the following components is part of the data architecture framework?

Data Lineage Signup and view all the answers

Among the following options, which best describes 'data lineage'?

A detailed documentation of data movement Signup and view all the answers

Which term is used to describe the fundamental organization of a system?

Data Architecture Signup and view all the answers

Which data modeling scheme is characterized by the use of objects in data representation?

Object-Oriented Modeling Signup and view all the answers

What is the primary goal of Data Storage and Operations?

To design and support data to maximize its value throughout its lifecycle Signup and view all the answers

Which of the following refers to any collection of stored data?

Database Signup and view all the answers

What does CAP theory address in distributed architecture?

Consistency, Availability, Partition tolerance Signup and view all the answers

What is a key component of Data Security?

Proper authentication, authorization, access, and auditing of data Signup and view all the answers

How is Data Integration best described?

It consolidates data into consistent forms. Signup and view all the answers

What is Data Interoperability?

The ability for multiple systems to communicate Signup and view all the answers

Which major regulation is mentioned as an example of data security requirements?

General Data Protection Regulation (GDPR) Signup and view all the answers

Which of the following is NOT a focus area of Data Security?

Data visualization Signup and view all the answers

What is the relationship between information, knowledge, and wisdom according to the provided definitions?

Knowledge is transformed information, and wisdom is knowledge that has been applied. Signup and view all the answers

What is the primary goal of Reference and Master Data management?

To ensure accurate and timely use of critical shared data across systems Signup and view all the answers

Which statement best describes data as an asset?

Data is recognized as an enterprise asset that holds value over time. Signup and view all the answers

What does Data Quality management primarily focus on?

Implementing techniques to assess and improve data fitness for organizational use Signup and view all the answers

How is information primarily defined in relation to knowledge and understanding?

As something that changes beliefs or knowledge. Signup and view all the answers

Which of the following best describes the role of Metadata in data management?

It includes activities that enable access to integrated definitions and information critical to understanding data Signup and view all the answers

What differentiates data from physical assets?

Data can be used simultaneously by multiple individuals. Signup and view all the answers

What is an essential aspect of Data Warehousing and Business Intelligence?

Control processes to manage decision support data for knowledge workers Signup and view all the answers

Which of the following statements accurately represents the nature of data?

Data is easy to replicate and transport, but not to regenerate if lost. Signup and view all the answers

In data management, what is primarily involved in the ongoing reconciliation process?

Ensuring consistent use of the most accurate version of shared data Signup and view all the answers

What term can be used interchangeably with information as per the provided definitions?

Data. Signup and view all the answers

What describes the way data can function within an organization?

Data can be valuable for different stakeholders with varying needs. Signup and view all the answers

What effect does information have according to its definitions?

It changes someone's beliefs, knowledge, or expectations. Signup and view all the answers

What is the primary function of Data Governance in data management?

It provides direction and oversight by establishing decision rights over data. Signup and view all the answers

Which of the following best describes the role of Data Architecture?

It defines the blueprint for managing data assets aligned with organizational strategy. Signup and view all the answers

What is the main purpose of Data Modeling and Design?

To analyze and communicate data requirements through a data model. Signup and view all the answers

Which process involves maximizing the value of stored data throughout its lifecycle?

Data Storage and Operations Signup and view all the answers

What is a key concern of Data Security?

Maintaining data privacy and preventing breaches. Signup and view all the answers

Which area includes the movement and consolidation of data within various data environments?

Data Integration and Interoperability Signup and view all the answers

Document and Content Management primarily deals with what aspect of data?

The planning and control of unstructured data, especially documents. Signup and view all the answers

Which statement about data entities and security rules is true?

Some major data entities may not be identified in data models but are in data architecture. Signup and view all the answers

Which job title focuses specifically on machine learning and artificial intelligence applications?

AI Product Manager Signup and view all the answers

What role is primarily responsible for overseeing data-related strategies within an organization?

Chief Strategy & Analytics Officer Signup and view all the answers

Which of the following titles best describes someone who specializes in analyzing and providing insights from geospatial data?

GIS Analyst Signup and view all the answers

Which role would typically be involved in managing a large-scale data architecture?

Data Architect Signup and view all the answers

What job title refers to someone who oversees comprehensive analytics across the organization?

Director of Analytics Signup and view all the answers

Which position is dedicated to conducting research specifically in statistical modeling and analytics?

Statistician Signup and view all the answers

Which title is likely involved in designing and overseeing marketing analytics strategies?

Director of Marketing Analytics Signup and view all the answers

What role typically manages risk analysis for an organization?

Director of Risk Analytics and Policy Signup and view all the answers

Which role is primarily responsible for ensuring the security of information within data systems?

Information Security Analyst Signup and view all the answers

Which job title describes an individual who designs systems for processing large data sets?

Big Data Architect Signup and view all the answers

Study Notes

Data Management Overview

The course is MSc Data analytics for business, 2024-2025, Bordeaux, offered by KEDGE Business School.
Instructor is Dr. Milad Poursoltan.
The course content includes introduction to data and data management, data modeling & relational databases, Structured Query Language (SQL), MariaDB and MySQL software, emerging techniques and methods.

Assessment

8 sessions.
Written exam - 50% (individual).
Practical exam - 40% (group of two).
Presentation - 10% (group of three).

Class Activities

Students will collect data about classmates in 30 minutes, and are not allowed to share the data with each other. (first name, field of study, fav job in data science and knowledge of database/data management).
Students will form groups of four and discuss solutions for challenges in data collection/quality (data collection protocols, defining data quality standards, etc.). Time limit 20 minutes.
Students will undertake data analysis activities over a 10-minute period.
Course participants will collect info about classmates (first name, field of study, fav job in data science and knowledge of database/data management), in 30 minutes.

Data and Data Management

Data represents facts about the world, but these facts are not always straightforward.
Data can be considered 'raw material' for information, while information can be seen as data in a defined context.
Information can be seen as a synonym for data or a synonym for facts, and as something new or as something that changes beliefs, knowledge or expectations.
Wisdom is knowledge put into action.

Data Architecture

Introduced as the "fundamental organization of a system".
Enterprise Architecture: visual blueprint of the organization, showing key data/process/applications/technology interrelationships.
Data Architecture: identification of enterprise data needs, and design/maintenance of master blueprints to meet these needs.

Data Life Cycle

The process involves collection, processing, storage and securing, using and sharing, and archiving, reusing and destroying data.

Data Management

Data Management: the process of collecting, organizing, and accessing data to boost productivity/efficiency/decision making.

Data Management Challenges

Data differs from other assets.
Data valuation remains a challenge.
Maintaining data quality is a critical concern.
Ethical considerations in data handling are key.

Data Management Frameworks

DMBOK (Data Management Body of Knowledge): Strategic alignment model.
DCAM (Data Management Capability Assessment Model).
The Data Management Association (DAMA).

Data Management Framework

Components of a framework include data architecture, data modeling & design, data quality, data storage and operations, data security, data integration and interoperability, document & content management, metadata, data warehousing & business intelligence, and reference & master data.

Data Governance

Data Governance is the authority/control framework over data assets.
The goal is having data managed properly based on best practices and policies (Ladley, 2012).
Data governance (DG) activities include controlling, and monitoring activities to ensure that data is managed properly.

Data Management Functions and Initiatives

Policies
Roles and Responsibilities
Controls
Guidelines
Decision Rights
Metrics
Processes
Rules
Accountabilities
Standards
Issue Management

Data Architecture: Data Lineage

Demonstrated through examples of tabular relationships linking major entities such as Product, Product Part, Manufacturing Plant. These relationships show what data is used to create a specific data element.

Data Modeling and Design

A data model is a representation of data requirements.
Some common data modeling schemes are Relational, Dimensional, Object-Oriented, Fact-Based, Time-Based, and NoSQL schemes.

Data Storage and Operations

Database: Collection of stored data of varied structure/content. Some large databases relate to instances and schemas.
Database Architecture Types: Centralized, and Distributed (not federated).
Basic requirements for distributed architecture (CAP theory): Consistency, Availability, Partition Tolerance.
Scaling techniques: Horizontal, Vertical.

Data Security

Data security policies & procedures will provide proper "authentication, authorization, access and auditing of assets". Key concerns include stakeholder concerns, government regulations, security aspects, and ensuring necessary business access.

Data Integration and Interoperability

Data Integration and Interoperability describes processes related to movement & consolidation of data within & between data stores. Common technologies include ETL and ELT processes.

Document and Content Management

Document & Content Management controls capture, storage, access, and use of data outside of established (relational) databases.

Reference and Master Data

Reference data characterizes/classifies other data relevant to an organization.
Master Data is data about entities that create context for business transactions, such as employees, customers, products, locations, and financial information.

Data Warehousing & Business Intelligence

Data Warehouse stores raw data using ETL, and/or ELT processes for analytical processing.
Data Warehousing and Business Intelligence encompass all activities that enable decision making from data, using BI techniques, such as reporting & analysis. The goal is to enable knowledge workers to gain value.

Metadata Management

Metadata is descriptive 'data about data'. Business intelligence, metadata has multiple kinds and should be managed as 'data'. Metadata is categorized into descriptive, structural and administrative types.

Data Quality

Data quality refers to the degree to which data meets requirements, and is managed through the data lifecycle.
Six key dimensions of data quality: Completeness, Uniqueness, Timeliness, Validity, Accuracy, and Consistency.

Group Exercises

Group exercise N.2 focuses on data governance concepts and on the ability to analyze related problems in various scenarios. Students should consider interaction between the knowledge areas.
Objectives: practical understanding of data governance concepts and the ability to analyze related problems in various scenarios.

Knowledge Areas

Knowledge areas involved include Data Governance, Data Architecture, Data Modeling & Design, Data Storage and Operations, Data Security, Data Integration and Interoperability, Document and Content Management, Reference and Master Data, Data Warehousing and Business Intelligence, and Metadata Management and Data Quality.

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Description

This quiz covers the key concepts of data management as part of the MSc Data Analytics course at KEDGE Business School. Topics include data modeling, relational databases, and hands-on experience with SQL, MariaDB, and MySQL. Prepare to test your understanding of the foundational elements of data analytics in a business context.