chapter 17

Understand how increasingly standardized data, access to third-party datasets, cheap/fast computing, and easier-to-use software are collectively enabling a new age of decision-making.
Be familiar with some of the enterprises that have benefited from data-driven, fact-based decision-making.

Ninety percent of organizational data was created in the last two years, with an estimated 2.5 quintillion bytes of data produced daily.
Big Data: Collections, storage, and analysis of extremely large, complex, and often unstructured data sets that organizations use to generate otherwise impossible insights.
Decision-making is data-driven and fact-based, enabled by:
- Standardized corporate data.
- Access to third-party datasets through cheap/fast computing and software.

Business Intelligence (BI): A term combining aspects of reporting, data exploration, and ad hoc queries, along with sophisticated data modeling and analysis.
Analytics: The use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.
Machine Learning (ML): A type of AI that leverages vast amounts of data for computers to act independently and improve accuracy without additional programming.

Data leverage is central to competitive advantage for firms like Amazon, Netflix, and Zara.
Data-driven strategies helped Walmart rise to the top of the Fortune 500 list.
Enables firms to optimize products and solutions based on derived insights, credited with aiding politicians in elections.

With more data comes increased modeling accuracy. Early movers in capturing these assets can dominate their sectors.
Advantages stemming from algorithms and data readily available to others will be temporary; differentiation in data applications is crucial for strategic advantage.

Disney showcased dynamic pricing by utilizing data from customer patterns to optimize ticket prices for shows like The Lion King, leading to revenue growth.
Dynamic pricing, utilized by services like Uber and sports teams, incentivizes customer behaviors to enhance revenue generation.
- Example: Orlando Magic uses incentives like "Magic Money" to draw fans to games.

Can be perceived as exploitative by consumers, particularly if they have previous purchase experiences or alternatives.
Most effective in markets with constrained supply and fluctuating demand.

Beacons: Bluetooth devices that provide location data for real-time promotions and navigation assistance.

Understand the difference between data and information.
Know key terms and technologies associated with data organization and management.

Data: Raw facts and figures.
Information: Data contextualized to answer a question or aid decision-making.
Knowledge: Insights derived from experience and data interpretation.

Database: A collection of related tables or a single table.
Database Management Systems (DBMS): Software for maintaining and manipulating databases.
Structured Query Language (SQL): Language for creating and managing databases.
Database Administrator (DBA): A professional overseeing database systems.
Table/File: Data organized in columns (fields) and rows (records).
Column/Field: Represents data category in a table.
Row/Record: Single instance of data in a table.
Key: Field(s) that link tables within a database, differentiating between primary and foreign keys.
Relational Database: Standard structure where tables are interconnected based on keys.

Tables include Students, Enrollment, and Faculty.
Each table contains designated fields reflecting student data, course registration details, and faculty information.

Serverless Computing: Cloud computing where third-party vendors manage server-related complexities, freeing developers to focus on business solutions.
Advantages:
- Increases development and deployment velocity.
- Enables focus on building serverless business logic.