Information Age: Laws and Impact

• The information age started in the 1970s with the digital revolution, marked by the shift from mechanical and analog devices to digital ones.
• Digital devices can connect, share data, and operate faster, transforming business operations.
• Bell's Law: A new computer class emerges roughly every decade, establishing a new industry. This means digital devices rapidly lead to new platforms, industries, and systems about every ten years.

Moore's Law

• Moore’s Law: The number of transistors per square inch on an integrated chip doubles every 18 months due to technological advancements.
• Due to Moore’s Law, the cost of data processing is approaching zero.

Metcalfe's Law

• Metcalfe’s Law: The value of a network equals the square of the number of connected users, meaning network value increases with more connections.

Nielsen's Law

• Nielsen’s Law: Network connection speeds for high-end users increase by 50% annually. Faster networks foster new companies, products, and platforms.

Kryder's Law

• Kryder’s Law: Storage density on magnetic disks increases at an exponential rate.

The Importance of CIS

• CIS is important because it highlights how technology fundamentally reshapes businesses.
• Future business professionals require the ability to assess, evaluate, and apply emerging IT to business challenges.

Nonroutine Cognitive Skills

• Nonroutine cognitive skills are essential, including: abstract thinking, systems thinking, collaboration, and experimentation.
• Abstract reasoning involves creating and manipulating models.
• Systems thinking involves modeling components to reflect the structure and dynamics of observed phenomena.
• Collaboration involves working with others to achieve a common goal.
• Experimentation involves analyzing opportunities, envisioning solutions, evaluating possibilities, and developing promising ones.
• The technology skills gap refers to employers demanding high tech skills from employees who lack them.

Information Systems (IS) vs Information Technology (IT)

• An information system (IS) combines hardware, software, data, procedures, and people to produce information.
• Information technology (IT) includes the products, methods, inventions, and standards used for producing information.
• A system is a group of components that interact to achieve some purpose.
• IS is a group of components that interact to produce information.
• The five-component framework includes computer hardware, software, data, procedures, and people.
• Hardware and people are actors that can take actions; software and procedures are sets of instructions; and data bridges the computer and human sides.
• Ask: How much work is being moved from people to computers when understanding high-tech versus low-tech?

Data vs Information

• Information commonly defined as knowledge derived from data.
• Data defined as recorded facts or figures.
• Information is data presented in a meaningful context.
• Information is data processed by operations like summing, ordering, or comparing.
• Data characteristics required for good information: accuracy, timeliness, relevancy, sufficiency, and cost-worthiness.

Porter's Five Forces

• Competitive strategy shapes the structure, features, and functions of every information system.
• Porter’s Five Forces model determines industry profitability: bargaining power of customers, threat of substitutions, bargaining power of suppliers, threat of new entrants, and rivalry among existing firms.
• Organizations choose a competitive strategy in response to their industry structure.
• According to Porter, organizations can aim to be the cost leader or differentiate their products/services.
• Value defined as the amount a customer is willing to pay for a resource, product, or service.
• Margin: difference between the value an activity generates and its cost.
• A value chain is a network of value-creating activities comprised of five primary and four support activities.
• Linkages: interactions across value activities in Porter’s model of business activities.
• A business process is a network of activities that generates value by transforming inputs into outputs.
• Business process cost: cost of inputs plus the cost of the activities.
• Business process margin: value of outputs minus cost.
• A business process comprises activities where each activity is a business function receiving inputs and creating outputs.
• A repository is a collection of items, like a database.
• Competitive advantage can be gained by creating new products/services, enhancing existing ones, and differentiating from competitors.
• First-mover advantage: gaining market share by being first to develop new technology in a market.
• Second-mover advantage: gaining market share by imitating after a pioneering company and cutting R&D costs.
• High switching costs result from organizations being able to lock in customers or suppliers.

Business Intelligence (BI) Systems

• Business intelligence (BI) systems process operational, social, and other data to identify patterns, relationships, and trends for use by knowledge workers.
• These patterns, relationships, trends, and predictions are business intelligence.
• BI systems have standard components: hardware, software, data, procedures, and people.
• The software component of a BI system is a BI application.
• The BI application uses reporting, data mining, and Big Data applications to produce business intelligence.
• The three primary activities in the BI process are to acquire data, perform analysis, and publish results.
• Data acquisition involves obtaining, relating, and cataloging source data.
• Data acquired from various sources is standardized through master data management.
• BI analysis involves processes for creating business intelligence.
• The three main categories of BI analysis are reporting, data mining, and Big Data.
• Publish results involves delivering business intelligence to the knowledge workers who need it.
• Push publishing delivers business intelligence to users automatically; pull publishing requires users to request the information.
• A data warehouse is a facility for managing an organization’s BI data by obtaining, cleansing, organizing, relating, and cataloging data.
• Granularity refers to the level of detail in the data.
• A data mart, smaller than a data warehouse, addresses the needs of a specific department or functional area.
• Creating a data lake, a central repository for large amounts of raw unstructured data, is another approach to managing an organization’s BI data.
• Data lakes can store more varied data in their raw forms.
• A data lake may become a data swamp if it stores large amounts of data that may never be used.
• The goal of Big Data analysis is to find patterns and relationships in vast data from sources like social media.
• Reporting analysis involves sorting, grouping, summing, filtering, and formatting structured data, which is data in rows and columns.
• A reporting application inputs from multiple sources and applies reporting processes to produce BI.
• Data mining applies statistical techniques to find patterns and relationships for classification and prediction.
• Data discovery includes processes developed to allow users to visually analyze and explore data and data visualization allows users to quickly understand complex data.
• Big data describes data collections with huge volume, rapid velocity, and great variety.
• MapReduce is a technique for using thousands of computers working in parallel.
• Static reports are fixed at creation and do not change; dynamic reports are updated upon request.
• A BI server is a web application built for publishing business intelligence.
• Knowledge management (KM) involves creating value from intellectual capital and sharing knowledge with stakeholders.
• KM improves process quality and increases team strength.
• Content management systems (CMS) support the management and delivery of documents, web pages, and expressions of knowledge.
• Artificial intelligence (AI) simulates human abilities to achieve goals.
• Organizations use AI to increase automation of mundane tasks done by humans.
• AI research aims to create artificial general intelligence, or strong AI, that matches human capabilities.
• We currently have weak AI, focused on specific tasks.
• Some researchers see superintelligence as a potential threat to humans.
• Machine learning, a subset of AI, extracts knowledge from data using algorithms from training data.
• An algorithm is a set of procedures used to solve a mathematical problem.
• Continuous intelligence uses machine learning to analyze realtime data and automatically make business decisions.
• A neural network is a computing system modeled after the human brain, used to predict values and make classifications.