M.10 - Databases

Database

Collection of information, usually stored as computer files.

Operational Database

Stores, updates, and maintains daily, constantly changing data (TPS, OLTP, CRM, SCM, ERP). Used to collect, view, update, organize, move, or delete data.

Analytical Database

Holds historical, stable data used for spotting trends and supporting tactical/strategic decisions. Not constantly updated.

Executive Dashboard

Visual interface for accessing analytical databases; displays query results visually.

Data Mining

Algorithms that discover unknown, useful patterns and relationships in data.

Predictive Analytics

Data mining branch that predicts future trends from historical and current data.

OLAP

Technique for complex analytical queries that decision-makers can answer quickly.

Database Model

Underlying structure of how a database is organized.

Flat File

Single two-dimensional table (e.g., spreadsheet).

Unstructured File

Each document has unique structure; data types vary.

Structured File

Uses uniform format for all records.

Field

Smallest meaningful unit of data; basic building block of databases.

Variable-Length Field

Expands to fit entered data.

Fixed-Length Field

Has a predetermined number of characters.

Record

Collection of related data fields.

Record Type

Template for a record.

Relationship

Association between different record types.

Cardinality

Number of associations allowed between record types.

Entity-Relationship Diagram (ERD)

Visual representation of relationships between record types.

Hierarchical Database

One-to-one or one-to-many relationships arranged in a tree; fast and compact but rarely used.

Graph Database

Tracks relationships using nodes and edges; resembles sociograms.

Relational Database

Stores data in related tables made of records (rows).

Table

Sequence of records in a relational database.

Multidimensional Database

Organizes data over 3+ dimensions for analytics.

Dimension

Category layer (e.g., product, place, customer).

Object Database

Stores data as objects grouped into classes with attributes/methods; good for varied real-world data.

Object-Oriented Database

Another term for object database.

XML

Markup language used to format structured document data.

Database Tools

Software from enterprise systems to small embedded tools for managing data.

Data Dependence

Data tied tightly to programs, making changes difficult.

Data Independence

Data separated from programs; modern tools support this.

Dedicated Applications

Simple data tools for specific tasks (address books, appointments). Limited flexibility.

Word Processing Software

Produces documents; can handle structured/unstructured data; supports single- and multi-level sorting.

Single-Level Sort

Sort using one field.

Multi-Level Sort

Sort using multiple fields.

Spreadsheets

Table-based software with basic data management; easy for flat files.

Database Management System (DBMS)

Software for creating, managing, and accessing databases.

Claris Filemaker / MS Access

Easy DBMS options for individuals and small businesses.

Fields, Tables, Relationships

Core elements of a relational database.

Database Structure

Arrangement of fields, tables, and relationships.

Computed Field

DBMS-calculated value (like a formula).

Field Format

Template for enforcing data display and entry format.

Field Validation Rule

Restriction used to filter allowed data.

Lookup Routine

Validates entry by checking an internal or external database.

Data Type

Defines how data is represented in storage/RAM. (Real, Integer, Date, Text, Memo, Logical, BLOB, Hyperlink.)

Normalization

Designing a database to reduce redundancy and improve efficiency.

Physical Sort Order

Arrangement of data on storage devices.

Sort Key

Field used to sort data.

Sorted Tables

Tables arranged to speed up queries/updates.

Database Index

List of keys pointing to full records; speeds lookups.

User Interface Guidelines

Logical field order, consistent layout, visual cues, easy navigation, scrolling, record controls, platform-aware design, on-screen instructions.

Report

Printed/screen list of selected database data.

Report Generator

Tool for specifying report content/format.

Report Template

Outline/specifications of a report.

Query Language

Language for database commands.

SQL Query

Command starting with an action keyword to operate on the database.

CREATE

Makes a database/table.

DELETE

Removes a record.

INSERT

Adds a record.

JOIN

Combines data from two tables.

Dot Notation

Distinguishes fields with same names in different tables.

SELECT

Searches for records.

UPDATE

Edits field data.

Global Update

Updates multiple records at once.

Parameters

Detailed specifications for a command.

Boolean Operators (AND, OR, NOT)

Used for complex SQL conditions.

Big Data

Massive datasets too large/complex for traditional database tools to process, analyze, or manage.

3rd Platform

Tech platform built on cloud computing, mobile devices, social networking, and big data.

High Volume

Extremely large amounts of data.

High Velocity

Rapid data generation and processing speeds.

Variety

Many types/forms of data.

Veracity

Data reliability/accuracy may be uncertain.

Low-Density Value

Contains large amounts of unimportant or low-value detail.

Mainstream Big Data Exploration

Analytical use of big data to produce commercial benefits.

NoSQL

Technologies for managing non-relational databases that don’t use the SQL model. Good for big, unstructured, distributed data.

NoSQL Technologies

Tools enabling distributed, flexible, and scalable non-relational databases.

Distributed

Data stored across many devices.

Dynamically Scaling

Easily adds storage/devices as data volume or velocity grows.

Flexible Data

Can store varied and changing datatypes/structures.

Non-Relational

Uses models other than relational tables and SQL.

Scale Up / Vertical Scaling

Add resources to a single device (CPU, RAM, storage).

Scale Out / Horizontal Scaling

Add more devices or nodes (LAN or cloud).

Schema

Organizational blueprint of a relational database.

Schema-Less Database

NoSQL structure allowing fields to be added/modified/distributed while the database runs.

Key-Value Data Model

Simplest NoSQL model where each item has a unique key and an associated value.

Column-Oriented Data Model

Stores data in columns (not rows); ideal for analyzing large chunks of data.

Blockchain

Distributed ledger database using a peer-to-peer network.