7.7: Summary

7.1. Data and Databases

Quantitative data is numeric, the result of a measurement, count, or some other mathematical calculation.

Qualitative data is descriptive.

Data are raw bits with no context.

Information is data with context or meaning.

The consumption of information produces knowledge.

Wisdom comes when we combine knowledge and experience. 

The most used data type are:

1. Flat File
2. Structured Data
3. Unstructured Data
4. Semi-structured Data

7.2. Before Databases

Before the Database approach, the file-based system was in place in some of the organizations around the world.

The file-based system disadvantages are:

1. Data redundancy
2. Data integrity
3. Data security
4. Data concurrency access

7.3. Relational Model

The relational data model describes the world as “a collection of inter-related relations (or tables).” It was created by E.F. Codd in the 1970’s.

A database is composed of multiple tables and each table holds the data.

Tables are composed by records and fields.

The degree is defined as the number of attributes in a table.

A data warehouse aggregates data from various sources into a central data store optimized for querying and analysis.

There are three main types of data warehouses:

• Enterprise data warehouse (EDW)
• Operational data store (ODS)
• Data mart

Some benefits of Data Warehouses are:

• Improved data quality
• Support for AI and machine learning
• Enhanced decision support
• Time-Variant

Some Data Warehouses drawbacks are:

• Complexity
• Time-Consuming
• Cost
• Changing Requirements

Data  mining is the use of machine learning and statistical analysis to uncover patterns and other valuable information from large data  sets.

Some Data Mining benefits are:

• Discover hidden insights and trends
• Save budget
• Solve multiple challenges

Some Data Mining drawbacks are:

• Complexity and risk
• Cost
• Uncertainty

Data brokers combine publicly accessible data with information obtained, to create vast warehouses of data about people and companies that they can then sell.

Business intelligence (BI) is a set of technological processes for collecting, managing and analyzing organizational data to yield insights that inform business strategies and operations.

Benefits of BI:

• Clearer reporting
• Consolidated data
• Creates new efficiencies
• Deeper data insights
• Faster decision making
• Increase customer satisfaction
• Increase employee satisfaction

Challenges of BI:

• Contradictory conclusions 
• Skills shortfall 
• Up-front costs 

Business analytics (BA) refers to the statistical methods and computing technologies for processing, mining and visualizing data to uncover patterns, relationships and insights that enable better business decision-making.

Benefits of BA:

• Faster and better-informed decisions
• Single-window view of information
• Enhanced customer service

Knowledge management is the process of formalizing the capture, indexing, and storing of the company’s knowledge in order to benefit from the experiences and insights that the company has captured during its existence.

There are 5 main types of knowledge management tools: 

• Knowledge bases (KB)
• Learning management systems (LMS) 
• Document management software (DMS)
• Content management systems (CMS)
• Customer relationship management systems (CRM)

7.4. Databases and security

It is the confidentiality, integrity, and availability (CIA) of the data in a database that need to be protected.

The information stored in databases can be hard to replace, whether the loss results from

• physical threats such as a fire or a significant power outage
• human error that results in errors in the processing of information or unintended deletion of data, or from erroneous input
• corporate espionage, theft, or malicious activity.

A data breach is any security incident in which unauthorized parties access sensitive or confidential information, including personal and corporate data.

Data breaches are caused by:

• Innocent mistakes
• Malicious insiders
• Hackers

Most intentional data breaches follow the same basic pattern:

1. Research
2. Attack
3. Compromise data

Which could be some consequences of Data Breaches?

• Financial losses
• Reputational Damages
• Legal and Compliance Consequences
• Operational Disruption
• Long Term Fallout

A cyber or cybersecurity threat is a malicious act that seeks to damage data, steal data, or disrupt digital life in general.

The most common cybersecurity threats are:

• Malware attacks
• Social engineering attacks
• Denial-of-Service attacks (DoS)
• Man-in-the-middle attacks (MitM)
• Supply chain attacks
• Injection attacks
• Internet of Things (IoT) attacks
• Advanced persistent threats (APTs)
• Zero-day exploits
• Password attacks

A vulnerability is a weakness that can be exploited by cyber criminals to gain unauthorized access to a computer system.

Data can be vulnerable under these circumstances:

• Data at rest 
• Data in motion 
• Poor architecture 
• Vendor bugs 
• Unlocked database 

A cybersecurity risk is the probability that a threat will exploit a vulnerability, resulting in financial loss, operational disruption, or reputational damage.

Risk Assessment is the process of identifying risks to organizational operations (including mission, functions, image, reputation), organizational assets, individuals, other organizations, and the Nation, resulting from the operation of an information system.

The most common classification of the core risk levels is:

• Low Risk
• Moderate / Medium Risk
• High Risk
• Critical / Severe Risk

Steps to perform a Cybersecurity Risk Assessment:

1. Define objectives and scope
2. Prioritize IT assets
3. Identify threats and vulnerabilities
4. Determine risk levels and prioritize risks
5. Address risks with security measures
6. Implement secure coding practices
7. Conduct continuous monitoring and document risks

 Remember some measures you can take to better protect your PII:

• Keep your passwords to yourself
• Use strong passwords
• Use different passwords for different accounts
• Check your credit reports annually
• Google yourself
• Remember that people can be a very weak link in security
• Control physical access to your devices
• Remember to logout of a website when you are finished using it
• Remember to lock your computer with a password when you are finished using it

7.5. Database concepts

Expanding our previous definition, we have that a database is a organized collection of related information used to support the activities of a particular organization.

A database has the following properties:

• It is a representation of some aspect of the real world or a collection of data elements (facts) representing real-world information.
• A database is logical, coherent and internally consistent.
• A database is designed, built and populated with data for a specific purpose.
• Each data item is stored in a field.
• A combination of fields makes up a table.
• Many tables are contained in a database.

A Database Management System (DBMS) is a software technology that manages the information in your database. 

A database can be linked to:

• A website that is capturing registered users
• A client-tracking application for social service organizations
• A medical record system for a health care facility
• Your personal address book in your email client
• A collection of word-processed documents
• A system that issues airline reservations

Some of the benefits of a DB are:

• Self-describing nature of a database system
• Insulation between program and data
• Support for multiple views of data
• Sharing of data and multi-user system
• Control of data redundancy
• Data sharing
• Enforcement of integrity constraints
• Restriction of unauthorized access
• Data independence
• Transaction processing
• Backup and recovery facilities

Database Management Systems (DBMS) can be classified based on several criteria, such as: 

1. data model,
2. single or multi-user , and
3. database distribution

Some Database users are:

• End users
• Application users
• Application programmer
• Privileged/Super users
• DBA’s

7.6. Database design

There are three classic phases for a Database design:

1. Requirements Analysis

   • Planning

   • System definition

2. Database design

   • Logical model

   • Physical model

3. Implementation

   • Data conversion and loading

   • Testing

There are three (3) possible relationships in Database:

• 1:1 (one-to-one) 
• 1:m (one-to-many) 
• m:n (many-to-many)

An Entity Relationship Diagram (ERD) is a visual representation of how items in a database relate to each other. 

A data structure diagram, visually represents the way data entities are related physically.

Database normalization is a process used to organize a database into tables and columns.

There are three main forms: 1st normal form, 2nd normal form, and 3rd normal form.

There are three main reasons to normalize a database.

1. to minimize duplicate data
2. to minimize or avoid data modification issues, and
3. to simplify queries.