(5) Database

Five components of an information system

1. Hardware: physical computing equipment

2. Software: programs and applications

3. Data: raw facts and figures

4. People: users, administrators, and analysts

5. Process: procedures and rules for operating the system

Definition of data

Raw, unorganized facts, numbers, or symbols without context or intent

Definition of information

Data given context, meaning, and specific organization

Definition of knowledge

Information aggregated and analyzed to make decisions, set policies, and spark innovation

Definition of wisdom

Combination of knowledge and experience that improves long-term decision-making

Quantitative data

Used for statistical analysis, performance evaluation and identifying trends

• Core focus: measurable metrics, KPIs, system metrics

• System metrics: CPU usage, database query times, page load speeds

• User metrics: number of daily active users, bounce rates, conversion rates

• Collection methods: system logs, automated performance monitors, quantitative surveys

Qualitative data

Answers the questions ‘why’ and ‘how’; focuses on the human element of technology, helping researchers understand user experiences, frustrations, and the context behind system usage

• Core focus: attitudes, opinions, motivations, and usability experience

• Collection methods: focus groups, in-depth user interviews, and open-ended survey responses

Concept of mixed-methods data approach

Combining quantitative and qualitative data to form a complete operational picture

Definition of database

An unorganized collection of digital information stored in a computer system to generate knowledge for decision-making purposes

Three main reasons to use a database over spreadsheets

1. Control of redundant data: prevents duplicate records across multiple spreadsheets from becoming inconsistent when updates occur (e.g. name changes)

2. Avoid violation of data integrity: ensures business rules are strictly enforced across files (e.g., preventing grade releases prior to tuition payment verification)

3. Overcome human memory limitations: removes reliance on human memory to locate and search massive volumes of stored data

Tables, records, and field in a relational database hierarchy

• Table (relation/entity/concept/object): a two-dimensional grid of rows and columns storing related information

• Record (instance/row): a single entity row within a table

• Field (attribute/column): a specific category or attribute in a record

Definition of primary key (PK)

A unique identifier field in a table assigned to each record that cannot change

Definition of foreign key (FK)

A field in one table that references and connects to the primary key of another table, establishing a relationship between them

Four sequential steps to the database design process

1. Understand the goal: determine how the database will be used

2. Identify data needed: list all required data inputs to achieve the goal

3. Identify relationships: determine how different data elements relate to one another

4. Identify tables and fields: organize data into structured tables, establish primary keys, and define columns

Definition of database normalization

The practice of organizing fields and tables in a relational database

Two primary goals of database normalization

1. Reduce duplicated data (eliminate redundancy)

2. Ensure data integrity across tables using foreign keys

Common database data types

• Text: non-numerical data less than 256 characters

• Number: numeric data

• Boolean (yes/no; true/false): 0 for no or false; 1 for yes or true (only 2 possible options)

• Date/time: a number data type that can be interpreted as a number/time

• Currency: monetary data

• Paragraph text: stores text longer than 256 characters

• Object: data that can’t be typed, such as a picture or music file

Two functions of data types in database design

1. Dictate permissible operations: defines what operations can be run on a field (e.g., mathematical calculations can only be performed on number or currency data types)

2. Specify storage limits: allocates required storage space per field and guides designers to keep space allocations minimal and efficient

Definition of Database Management System (DBMS)

Software used to store, organize, retrieve, and manipulate structured data safely and efficiently, turning raw data into actionable business insights

Commercial DBMS examples

• Microsoft Access

• DB2

• Oracle Database

• Microsoft SQL Server

• MySQL

Real-world uses of DBMS

• Banking: tracking account balance totals and wire transfers

• E-commerce: searching product catalogs and triggering inventory restocks

• Daily apps: powering backend services for ridesharing, streaming, and gaming

Logical view in a DBMS

How end users and business personnel perceive, view, and conceptualize data

Physical view in a DBMS

How data is actually structured, formatted, and physically organized on storage media inside the computer system

How a relational DBMS works

1. SELECT: creates a subset of rows/records from a table that satisfy stated criteria

2. JOIN: combines relational tables together using shared foreign/primary keys to supply more information

3. PROJECT: creates a subset of columns/fields from a table, letting users build new tables containing only specified attributes

Definition of Big Data

Massively large, unstructured, and semi-structured datasets that conventional relational data processing technologies lack the power to process or analyze

Value of Big Data

Larger datasets reveal hidden business patterns, consumer behaviour trends, and environmental models

4Vs framework of Big Data

1. Volume: the massive size or scale of collected data

2. Variety: the diverse forms and formats of incoming data (structured, semi-structured, unstructured)

3. Velocity: the speed and frequency at which new data is generated and streamed in

4. Veracity: the trustworthiness, accuracy, and quality of the collected data

Definition of non-relational (NoSQL) databases

Database systems designed to store and query data outisde traditional tabular row-and-column structures

Key characteristics of non-relational (NoSQL) databases

• Highly scalable across multiple servers and distributed data centers

• Flexible data models that do not require extensive structuring

• Manages and processes unstructured/semi-structured data (e.g., social media posts, graphic files

Definition of cloud relational database

Structured database hosted on cloud computing infrastructure that manages hardware setup, scaling, and backups, charging based on usage

• Target: appeals to small/medium businesses

Definition of distributed database

A single logical database whose physical data is partitioned and distributed across multiple physical nodes, locations, or servers connected over a network

Definition of modern database

An advanced data storage system to handle high volumes of diverse data with high speed and cloud scalability

Definition of blockchain

A distributed database of transcactions across a network of computers; a digital record book that stores information in a very secury way

Characteristics of blockchains

• Each block of info is connected to the previous one, forming a chain

• Operates on a network without a central authority

• Maintains a growing list of records called blocks

• Once recorded, blocks cannot be changed

• Reduces the cost of processing transactions and enhances security

Industries/applications of blockchains

• Digital money

• Supply chain tracking

• Digital identity

• Real estate records

Workflow of a blockchain transaction

1. X sends funds/assets to Y

2. Transcation is configured into a block

3. Transaction is broadcasted across the network, which validates it

4. Block is then added to the chain which records the entire history into the ledger

5. Y accepts funds/assets from X

Definition of cryptocurrency

Any form of currency that exists digitally or virtually and uses cryptography to secure transactions; a digital payment system that doesn’t rely on banks to verify transactions as it is a p2p system that can enable anyone, anywhere, to send and receive payments

Characteristics of cryptocurrency

• Lacks a central regulating or issuing authority

• Stored in secure digital wallets and divisible into smaller decimal units

Definition of fungibility

Units are mutually interchangeable and equal in value

• Example: 1 bitcoin always equals 1 bitcoin, just as 1QAR always equals 1QAR

Definition of non-fungible tokens (NFTs)

A unique digital item that acts as a verifiable certificate of ownership for a specific item or piece of content; stored securely on a blockchain, they prove authenticity and cannot be replicated, substituted, or divided like standard cryptocurrencies

Definition of business intelligence (BI) in IS

Refers to the technologies, applications, and practices used to collect, integrate, analyze, and present data

• Core purpose: transform raw data into actionable insights that drive strategic and operational decision-making

Four primary BI tools for Big Data

1. Data visualization

2. Data warehouses

3. Data mining

4. Knowledge management

Definition of data visualization

Transforming processed data into intuitive visual formats, such as interactive charts, maps, graphs, and scorecards, via dashboards; it translates complex datasets into easily understood insights, allowing the user to spot patterns and trends at a single glance

• Supports quickly summarizing data in a way that is more intuitive and can lead to easy decision-making

Definition of data warehouse

A central storage system designed to collect, integrate, and manage large amounts of current and historical data from different sources so companies can run reports and analyze data

• Allows data to be copied and stored for analysis, and the data needs to be refreshed as the data changes

Characteristics of data warehouses

• Consists of extracting data from one or more of the organization’s databases

• Data is time-stamped when extracted and allows comparisons between different time periods

• Data is standarized

• Data marts: smaller subsets of data warehouses for specific business problems

Benefits of data warehouse

• Focuses orgs to better understand the data

• Centralized view of data to identify inconsistencies

• Once inconsistencies are resolved, higher-quality data is used to make better business decisions

• Data can be analyzed over multiple time periods

• Tools are available to combine data and gain more insight into business operations

Definition of data mining

An automated process of analyzing large datasets to discover patterns, trends, and relationships; commonly used for customer purchasing analysis and predictive analytics in retail; turns raw data into actionable insights for decision-making

Key aspects in data mining

1. Business intelligence: uses mined data and analyzes it for information to increase competitive advantage

2. Business analytics: uses internal company data to improve business processes

3. Privacy concerns: easier to combine dissimilar sources of information, and when aggregated, provides details about an individual; data brokers can sell this information

Definition of knowledge management

The systematic process of identifying, capturing, storing, and sharing an organization’s collective expertise and information; leverages tech to transform individual know-how into accessible digital assets, enabling employees to find the right information exactly when they need

• Relies on people, processes, and technology (the three dimensions of IS) to build a culture of continuous learning

Three core dimensions KM relies on

1. People: building a collaborative organizational learning culture

2. Processes: methods for capturing, filtering, and distributing knowledge

3. Technology: digital IS infrastructure hosting knowledge management platforms