Chapter 3: Information systems and data analytics (Video Notes)

Vocabulary-style flashcards covering the key concepts from Chapter 3: Information systems and data analytics, including TPS, MIS, EIS, ERP, CRM, Big Data and its five Vs, data analytics, and levels of management information.

Transaction Processing System (TPS)

Records historic information and automates the simple manual processes; routinely captures, processes, stores, and outputs low-level transaction data.

Management Information System (MIS)

Converts internal and external data into useful information to support planning, directing, and controlling; provides summary information for decision making.

Executive Information System (EIS)

Provides strategic managers with flexible access to information from the entire business and relevant external data, with drill-down capability.

Enterprise Resource Planning (ERP)

Integrates data from all operations (e.g., operations, sales/marketing, HR, purchasing) into one single system.

Customer Relationship Management (CRM) system

Aims to form and sustain long-term relationships with customers.

Big Data

Large volumes of structured and unstructured data from diverse sources, beyond traditional processing/storage capacities, used to gain insights and potential competitive advantages.

Velocity (Big Data 5 Vs)

Data streams from sources (e.g., social media) at high speed, challenging real-time processing.

Volume (Big Data 5 Vs)

The enormous amount of data being generated and stored.

Variety (Big Data 5 Vs)

The wide range of data formats and types, including structured, unstructured, text, audio, GPS, etc.

Veracity (Big Data 5 Vs)

The trustworthiness and quality of data; higher risk of inaccuracies from diverse sources.

Value (Big Data 5 Vs)

Turning diverse, fast-moving data into meaningful business value.

Big Data benefits

Driving innovation, gaining competitive advantage, and improving productivity.

Big Data risks

Skills availability, security/privacy concerns, and data protection issues due to rapid system development.

Big Data management

Storage, administration, and control of vast quantities of structured and unstructured data from multiple sources.

Big Data analytics

Scrutinising Big Data to identify patterns and relationships to support decision-making and forecasting; includes improving performance measurement.

The Big Data Pyramid

A model showing the progression from Data to Information to Knowledge to Wisdom, with focus areas for data collection, processing, storage, dissemination, and application.

Data

Raw facts collected from various sources before processing.

Information

Processed data that carries meaning and supports decision making.

Knowledge

Understandings and insights derived from information used to make informed decisions.

Wisdom

Applied knowledge and insights guiding sound, context-aware decisions.

Predictive analytics

Forecasting what will happen by identifying relationships and patterns in data; uses statistics, machine learning, and databases.

Data mining

Process of discovering relationships, trends, and patterns in large data sets to turn raw data into useful information.

Descriptive analytics

What has happened? Analyzing past data to describe events.

Prescriptive analytics

What should we do? Recommending actions based on data insights.

Scepticism about analytics

Analytics cannot predict the future with absolute certainty; predictions are probabilistic and rely on reasonable assumptions.

Strategic information level

Long-term, aggregated data from internal and external sources; infrequent and high-level.

Tactical information level

Immediate, highly detailed information; internal sources; frequent; used to implement strategic plans.

Operational information level

Day-to-day, routine information; mainly internal sources; very frequent; supports daily tasks.