Big Idea 5

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65 Terms

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Digital Data

Various types of information including text, numbers, images, and audio

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Big Data

Extremely large and complex sets of data that are beyond the ability of traditional data processing methods to handle

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Name an example of Big Data

  • Social Media: User Posts, Comments, Likes, Shares, and Interactions

  • E-commerce: Customer Browsing Behavior, Purchase History, Reviews, Preferences

  • Healthcare: Electronic Health Records, Medial Imaging, Genomic Data, Patient Monitoring Systems

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Structured Data

Type of data that follows a specific organization or format and has a clear and well-defined structure that makes it easy to understand and process

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Unstructured Data

Information that doesn’t have a specific organization or format

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Semi-Structured Data

Information that falls somewhere between structure and unstructured data; It has some organizational elements but doesn’t adhere to a strict structure like structured data

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Distributed Files Systems

Similar to a virtual storage system that spreads your files across multiple computers or servers; Files are also divided into smaller pieces and stored on different machines

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Node

Each computer that stores a piece of your data

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Data Warehouse

Like a library where you organize and store all your data in a structured way (tables) which make it easier to search, filter, and compare; It is designed to handle lots of data from different sources and make it easier to analyze

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Cloud Storage

A virtual storage space that exists on the internet; It’s not a physical place you can touch but rather a network of powerful computers located in different places around the world

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Why do we process big data?

To extract meaningful insights and valuable information

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Data Collection

Gathering big data from various sources, including social media platforms, sensors, transactions, publicly available data, and crowdsourcing

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Crowdsourcing

Concept that involves obtaining ideas, services, or contributions from a large group of people

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Data Cleaning

“Cleaning” (Getting rid of the errors, noise, or inconsistencies) in big data

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What are the five cleaning steps?

  1. Removing Mistakes

  2. Fixing Missing Parts

  3. Getting Rid of Duplicates

  4. Standardizing Formats

  5. Checking for Inconsistencies

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Data Storage

Efficiently storing big data

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Data Processing

Applying various techniques and algorithms to extract insights and patterns

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What are some examples of data processing?

  • Statistical Analysis

  • Machine Learning

  • Data Mining

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Descriptive Statistics

Help us understand the basic characteristics of big data

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Correlation Analysis

Helps us understand how two or more variables are related

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Regression Analysis

Helps us predict one variable based off of another variable

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Hypothesis Testing

Determine if there is a significant difference or relationship between groups or variables

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Machine Learning

Teaching computers to learn and make decisions on their own based off the patterns found in the data

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What could go wrong with machine learning?

  • Biased Results

  • Limited Generalization

  • Data Dependency

  • Ethical Concerns

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Data Mining

Finding valuable patterns or insights from large amounts of data

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What could go wrong with data mining?

  • Privacy Concerns

  • Bias and Discrimination

  • False Discoveries and Misinterpretation

  • Data Quality and Integrity

  • Ethical Considerations

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Data Visualization

Insights derived from big data being visual presented using charts, graphs, or dashboards

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Decision Making

Utilizing the insights gained from big data to make informed decisions

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Metadata

Data about data

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How is metadata useful?

  • Organization

  • Searchability

  • Data Integrity

  • Data Sharing

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Data security is crucial for protecting information from… and it ensures data…

  • unauthorized access, breaches, or misuse

  • confidentiality, integrity, and availability

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Privacy refers to an individual’s right to control their what>

Personal Information

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What does PII stand for?

Personal Identifying Information

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Computing Innovation

Includes hardware or software innovations, networking, user interfaces, or analytical innovations

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What kind of biases can exist in computing innovations?

  • Biased Data

  • Algorithmic Bias

  • Human Bias

  • Lack of Diversity

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What efforts can help control and reduce bias in computing innovations?

  • Diverse and Inclusive Teams

  • Data Scrutiny

  • Algorithmic Transparency

  • Ongoing Evaluation and Testing

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Name some of the beneficial effects of computing innovations.

  • Speed and Efficiency

  • Information Access

  • Automation and Productivity

  • Connectivity

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Name some of the harmful of computing innovations.

  • Security Risks

  • Dependency and Addiction

  • Job Displacement

  • Privacy Concerns

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Name some of the legal concerns in computing.

  • Data Privacy

  • Intellectual Property

  • Cybersecurity

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Name some of the ethical concerns in computing.

  • Bias and Discrimination

  • AI Ethics

  • Autonomy and Consent

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How can you legally use the work of others?

  • Creative Commons

  • Open Source

  • Open Access

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Creative Commons

Public copyright license that enables the free distribution of an otherwise copyrighted work

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Cybersecurity

Practice of protecting computer systems, networks, and data from unauthorized access, attacks, and damage

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Phishing

Attempt to trick a user into divulging their private information

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How can you protect yourself from phishing attacks?

  • Suspicious email address

  • Suspicious URL

  • Non-secured HTTP connections

  • Requests for sensitive information

  • Urgency and scare tactics

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Rogue Access Points

Unauthorized wireless access point set up by attackers to intercept network traffic and gain unauthorized access to you data

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Why are rogue access points bad?

Hackers can use a rogue access point to capture sensitive data that is flowing through a network

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How can you protect yourself from rogue access points?

  • Use secure and trusted networks

  • Verify network names (SSIDs)

  • Be cautious with sensitive activities

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Malware

Malicious software that is unknowingly installed onto a computer

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Trojan Malware

Malware disguised as a legitimate software with the purpose of tricking you into executing malicious software on your computer

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Spyware

Type of malicious software that is designed to covertly collect information froma user’s device without their knowledge or consent

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Adware

Software designed to display advertisements on a user’s device

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Ransomware

Type of malware that encrypts a victims’s files or locks their entire computing sustem, making it inaccessible

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Keylogger

Keeps track of your keystrokes on your keyboard in an attempt to capture sensitive information like users and passwords

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How can you protect yourself from malware attacks?

  • Antivirus Software

  • Update Software

  • Beware of Phishing Attacks

  • Enable a Pop-Up Blocker

  • Enable Your Firewall

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What does DDoS stand for?

Distributed Denial of Service

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Botnet

Created by users downloading malware, and the malware being programed to conduct an attack on the server by sending fake traffic at a coordinated time

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Why is cybersecurity important?

  • Protecting personal information

  • Prevents theft or fraud

  • Maintain privacy online

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What are some of the potential consequences of cyber attacks?

  • Identity Theft

  • Financial Loss

  • Reputational Damage

  • Disruption of Services

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Data Breaches

Encryption helps safeguard sensitive data from data breaches

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Encrypted data is useless without the

Decryption Key

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What are the first line of defense against unauthorized access to your computer and personal information?

Passwords

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Brute Force Attack

Hackers use automated software that systemically tries all possible combinations of characters until the correct password is found. This method is time consuming.

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Man-in-the-Middle Attacks

When an attacker intercepts and alters communication between two parties

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Dictionary Attacks

Hackers use software that systemically checks common words, phrases, and dictionary terms as passwords.