Data Resource Management Flashcards

A set of vocabulary flashcards based on the introductory lecture on Data Resource Management, covering database structures, big data characteristics, and analytics terminology.

Data management

The practices, tools, and processes used to manage data across an organization to ensure it is accurate, consistent, and accessible when needed.

Data

Raw symbols or figures that are unorganized and do not provide much value until they are given context.

Information

Data that has been processed and made meaningful, such as numbers organized into a report showing monthly sales trends.

Data governance

The policies and procedures used to manage data within an organization to ensure it is secure, accurate, and used properly.

Rows

Individual records situated within a database table.

Columns

Specific fields of data found within a database table.

Database management system

Software, such as MySQL or Oracle, that allows users to create, manage, and interact with databases.

Primary key

A specific identifier that uniquely identifies each record within a database table.

Foreign key

A database element used to link tables together by connecting a record in one table to a record in another.

Big data

Extremely large data sets originating from many different sources that are difficult to process using traditional methods.

Characteristics of Big Data

Defined by four specific traits: volume, variety, velocity, and veracity.

Data mining

The process of analyzing large data sets to find patterns, trends, and relationships to help organizations make better decisions.

Structured data

Data that is organized in tables, such as information found in a spreadsheet.

Unstructured data

Data that is not organized in a formatted way, including items like videos, emails, or social media posts.

ETL

An acronym representing the process to extract, transform, and load data from different systems into a central data warehouse.

Hadoop

A tool that allows data to be stored and processed across multiple systems.

Steps for collecting data

A three-step process including defining the purpose, developing questions, and selecting tools.

Master data management

A process that ensures key data across an organization is consistent and accurate, providing a single source of truth.

Predictive analytics

The use of historical data to forecast future trends and behaviors to help organizations plan ahead.

Business intelligence

Tools and systems, such as dashboards and reports, used to turn data into insights that support decision making.

Descriptive analytics

A type of analytics that examines past performance to show what has happened, such as past sales.

Prescriptive analytics

A type of analytics that suggests specific actions to improve future outcomes.

Qualitative return on investment (ROI)

An analysis focusing on non-financial benefits and intangible values, such as improved efficiency and better decision making.

Data protection levels

A layered security approach involving securing data at the data level, system level, and user level.