Information Technology Fundamentals 1.1

• Information Technology Fundamentals are covered in section 1.1.
• This section includes a discussion on Information Technology, Computers, and Information Literacy.

Data and Information

• Information conveys a message and has various contextual meanings.
• Generally, information represents a series of meaningful and useful facts.
• Related terms to consider include data, information, knowledge, and wisdom.
• Data is raw and lacks inherent meaning, such as data in a spreadsheet.
• Information refers to data that has undergone processing and integration to become meaningful (e.g., averages, maximums, charts).
• Knowledge involves useful patterns derived from organized data and information (e.g., IF [condition(s)] THEN [result]).
• Wisdom evaluates discovered knowledge and offers future recommendations.
• Raw data and information can take different forms, including text, numbers, images, audio, or video.
• Raw data must be handled, digested, and converted into useful information.
• The information processing cycle involves input, process, output, storage, and communication.
• Input refers to data acquired or entered into a computer system and validated for completeness and accuracy, including unprocessed text, numbers, images, video, or audio.
• Processing involves operations performed on data to produce information, handled by the CPU.
• Output presents information to the user in the required format, such as soft copy, hard copy, audio, or video.
• Storage saves data or output for future use and it is not lost when the computer is switched off, as it is stored on secondary storage.
• Communication enables computers to receive and send information via emails, instant messaging (IM), SMS, MMS, video conferencing, blogs, or social networking.

What is Information Technology

• Information technologies are systems that capture, process, exchange, store, and/or present data or information.
• Information technologies are electronic hardware and software systems that capture, digitally process, exchange, store, and/or present data or information.

Benefits of Information Technology

• Computers serve as typical examples of information technologies and have numerous benefits.
• Speed is a significant advantage due to rapid processing capabilities.
• Reliability is ensured through hardware and software.
• Consistency provides uniform results.
• Storage has high memory and compatibility with various media.
• Communication is easy to be connected.
• Information and communication technologies (ICTs) have become more powerful, accessible, and widespread.
• Innovation and technology are drivers for economic growth and enhance competitiveness.
• Remarkable changes are occurring in current technology trends, including the:
• Internet of Things (IoT)
• Big Data
• Cloud Computing
• Automation
• Artificial Intelligence and Machine Learning.
• There is a shift from the Internet being a network of computers, servers, and mobile devices to one of all sorts of connected devices.
• The Internet of Things comprises household appliances, security cameras, transportation, medical, and home entertainment systems.
• IoT is a trillion-dollar industry with substantial capital investment.
• Capital investment of IoT has led to reshaping consumer experiences, increased automation, improved information gathering, and limitless potential.
• Smart devices evaluate data and adjust settings as programmed.
• With sufficient data, smart devices can "learn" and modify their code.
• Smart cities use sensors to manage infrastructure like traffic, parking, water, and hydro.
• Self-driving cars use ultrasound sensors, cameras, GPS, and computers.
• The Cloud data centers or server groups, store and analyze data, enable on-line applications and provide backup services.
• Sensors need network connections for data storage and sharing.
• Controllers are responsible for gathering data from sensors and enabling network or Internet connectivity.
• Controllers may make immediate decisions or send data to more powerful computers for analysis.
• Sensors work with actuators to transform electrical input into physical action.
• Artificial Intelligence (AI) devices have the ability to "think" independently.

Big Data

• Big data involves:
• Large data volumes.
• Structured or unstructured data.
• Its analysis helps to provide better decision making.
• Characteristics of big data include volume, velocity, variety, variability, and complexity.
• Volume refers to data collected from multiple sources.
• Business transactions, social media, sensor information and machine-to-machine data.
• Velocity means data streams in rapidly and must be dealt with promptly.
• RFID tags, sensors and smart metering.
• Variety means data comes in all formats.
  • Structured, numeric data.
• Unstructured documents, email, video, audio, stock ticker data and financial transactions.
• Variability involves data flows that can be inconsistent with periodic peaks.
• It can be difficult to manage daily, seasonal, and event-triggered peak data loads.
• Complexity arises when data is from multiple sources, and it is challenging to link, match, cleanse, and transform data across systems.
• Connecting and correlating relationships, hierarchies and multiple data linkages is necessary.
• Collecting and analyzing data achieves:
• Cost and time reductions.
• New product development and optimized offerings.
• Smart decision making.
• Big data is used in Banking to understand customers, minimize risk and fraud, and maintain regulatory compliance.
• Big data is used in Education to identify at-risk students, ensure progress and improve teacher evaluation and support.
• Big data is used in Government to help managing utilities, running agencies, dealing with traffic and preventing crimes and must address transparency and privacy.
• Big data is used in Health Care through patient records, treatment plans, uncovering information can lead to more effective plans/patient care, and prescription information.
• Big data is used in Manufacturing to boost quality and output, and help minimize waste.
• Big data is used in Retail to help with knowing:
• Customers marketing requirements
• How to handle transactions/bring back former clients

Distributed Computing

• Distributed data processing divides large data volumes into smaller pieces.
• Smaller pieces are distributed to many computers and can be processed.
• Each computer analyzes its part of the big data.

Data Visualization

• Data mining discovers patterns in large datasets.
• Mined data must be analyzed and presented to managers and decision makers through charts.
• Examples are line, column, bar, pie, and scatter charts.
• Data analysis involves:
• Inspecting
• Cleaning
• Transforming
• Modeling data to uncover usefull information
• A strategy helps a business identify analysis types needed
• Tools for big data analysis includes:
• Excel(small samples)
• Google Analytics(medium data samples) to applications dedicated to working with larger sets of data.
• Examples are Knime, OpenRefine, Orange, and RapidMiner.

Cloud Computing

• The cloud is a collection of data centers or connected servers.
• Cloud services available to end users are:
• Storing of data such as emails, music, movies and photos
• Access to many applications instead of downloading onto device
• Access apps and data at anytime and place on any device
• Enterprise-level cloud services include:
• Gaining access to organizational data from anywhere
• Stream IT department/functions
• Reduce/remove the need for on site IT support
• Lower equipment costs, plant requirements and personnel training

Automation

• Automation is self-driven and reduces/removes human interaction
• IoT allow for the automating of human tasks
• Uses of automation:
• Smart home, smart buildings, factories and cities
• Smart grids and cars.
• Stores/Services Medical surgery/diagnosis, aircraft auto-pilot

AI and Machine learning

• AI machines demonstrate intelligence
• AI uses intelligent agents to make decisions and percieve
• AI mimics cognitive tasks such as problem solving and learning.
• ML is part of AI that uses statistical techniques to allow computers to "learn"
• ML enables computers to improve without needing to be programmed.
• Common tech of ML include:
• Speech recognition to digital assistants
• Product recommendation that build client profiles
• Convert shapes to written documents
• Detect credit fraud
• Facial recognition.
• Key part to ML, neural networks are computational concepts based around the human brain which allows to recognize trends.
• Layered interconnected nodes.
• The more examples, the better learning Examples are speech processing, image recognition and predictive analysis

Generative AI

• Generative AI technology can create text, photos etc. by learning via existing data
• Chatbots, art creation and music composition are applications

Core Technologies

• GANs has 2 networks, one creates realistic outputs, one is a discriminator to decide what is real.
• Transformer based self attention, is used for for translating languages

Innovation, Tech and Industry

• Hong Kong has a vision to develop a tech center
• A mission to diversify, create jobs and improve life, and helps other nations.

Innovation and Tech Commission

• Hong Kong has a commission to lead the area to become a world class knowledge economy
• Spearhead support tech for transfers
• Culture to promote research, training and tech
• Government has program to promote standards, to have quality staff and innovate.

What is information literacy

• Is understanding of of abilities for individual like: Recognize/locate information needed
• American Library Association

Info is needed to

determine extent

• Access information and efficiently
• Evaluate and critically analyze
• Use appropriate for purpose
• Should understand legal/social/ethics and economics

How does it relate

• ITS broad skills for technology/tools to accomplish things
• Tech skills allow work/personal goals

What is ISP

• ISP is six stage to seek information behavior from library.
• Kuthau Carol first suggested in 1991

ISP steps

Initial is not having knowledge and feelings are apprehension

• When topic identified it gives readiness to search
• Uncertainty cause doubt
• Confident increase as perspective shifts
• Involvement deepen so collect pertinant info
• Presentation put in place so leaning can be used.

Section 1.1 covers IT fundamentals. Topics include information technology, computers, and Information Literacy. The section also includes discussions on data, information, knowledge, and wisdom.