Descriptive Analytics II: Business Intelligence, Data Warehousing, and Visualization (copy)

A set of 55 comprehensive vocabulary flashcards covering Business Intelligence, Data Warehousing architectures, ETL processes, OLAP operations, and Business Reporting based on Descriptive Analytics II.

Business Intelligence (BI)

A historical term that originally encompassed everything related to the use of data for managerial decision support; now treated as a key subset of business analytics representing descriptive analytics.

Descriptive Analytics

The branch of business analytics that addresses the questions "What happened?" and "What is happening?" using enablers such as business reporting, dashboards, scorecards, and data warehousing.

Predictive Analytics

The branch of business analytics that answers "What will happen?" and "Why will it happen?" through enablers including data mining, text mining, web/media mining, and forecasting.

Prescriptive Analytics

The branch of business analytics that answers "What should I do?" and "Why should I do it?" using optimization, simulation, decision modeling, and expert systems to identify the best actions.

Data Warehouse (DW)

A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format, functioning as an integrated, subject-oriented, time-variant, and nonvolatile database to support decision support system (DSS) functions.

Subject-Oriented Data

A core characteristic of data warehouses where information is organized around major enterprise subjects (such as customers, products, or sales) rather than around operational applications or business processes.

Integrated Data (DW Characteristic)

A data warehouse characteristic where data gathered from disparate operational and external sources are standardized into a consistent format, structure, and naming convention across the entire enterprise.

Time-Variant Data (Time Series)

A data warehouse characteristic where data are maintained across historical and near-current time horizons to enable trend detection, temporal pattern analysis, and historical comparisons.

Nonvolatile Data

A data warehouse characteristic stating that once data are recorded into the repository, they are read-only and cannot be changed or overwritten by users.

Summarized Data (DW Characteristic)

A data warehouse characteristic where granular operational records are pre-aggregated across various dimensions to accelerate analytical query processing and decision making.

Data Mart (DM)

A departmental, small-scale data repository focused on a single subject area or a strategic business unit rather than the entire enterprise.

Dependent Data Mart

A departmental data mart that is populated with a subset of data extracted directly from a centralized enterprise data warehouse.

Independent Data Mart

A small data warehouse designed for a strategic business unit or department that extracts data directly from operational source systems without feeding through an enterprise data warehouse.

Operational Data Store (ODS)

A type of database often utilized as an interim staging area for a data warehouse, primarily designed for short-term operational reporting and near-real-time tactical decision making.

Oper Mart

An operational data mart created directly from an operational data store to support near-real-time tactical decision-making and business operations.

Enterprise Data Warehouse (EDW)

A large-scale, centralized data warehouse that integrates data across multiple subject areas for the entire enterprise to support cross-functional optimization and strategic decision making.

Metadata

Described as "data about data"; details the contents of a data warehouse, including its structure, usage, sources, data acquisition rules, and technical features.

Three-Tier Architecture (DW)

A data warehousing architecture separated into three tiers: Tier 1 (client workstation front-end), Tier 2 (application server middle tier), and Tier 3 (database server back-end).

Two-Tier Architecture (DW)

A data warehousing architecture where the application server and the database server are combined into a single tier communicating with client workstations.

Single-Tier Architecture (DW)

An architecture where reporting tools and OLAP clients connect directly to operational data sources through middleware without a physically separated data warehouse layer.

Web-Based DW Architecture

A three-tier data warehousing architecture comprising a data source layer, an OLAP middle layer for data transformation, and a top-tier reporting layer accessed through web browsers.

Data Mart Bus Architecture

A data warehouse architecture where individual dimensional data marts are developed incrementally and linked together across the enterprise using shared, conformed dimensions.

Hub-and-Spoke Architecture

Also known as the Corporate Information Factory; an architecture featuring a normalized relational warehouse (the hub) that feeds dependent, summarized data marts (the spokes).

Centralized Data Warehouse Architecture

A data warehousing architecture featuring a single normalized relational warehouse containing atomic and summarized data that directly serves end-user applications without dependent data marts.

Federated Architecture

A data warehousing architecture that integrates existing data warehouses, data marts, and legacy systems logically or physically using shared data mapping and metadata without building a new central repository.

Inmon Model

An enterprise data warehouse development approach that follows a top-down philosophy, building a centralized, normalized EDW first before creating any departmental data marts.

Kimball Model

A data warehouse development approach that follows a bottom-up philosophy, building subject-specific dimensional data marts iteratively and linking them via conformed dimensions.

Hosted Data Warehouse

A cloud-based or third-party managed data warehouse alternative that minimizes upfront infrastructure investment, frees in-house capacity, and offers scalable processing capabilities.

Dimensional Modeling

A retrieval-based database design technique optimized for high-volume query access and intuitive analysis, typically structured into star or snowflake schemas.

Star Schema

The most common and simplest style of dimensional modeling, composed of a central fact table surrounded by and linked directly to several non-normalized dimension tables.

Snowflake Schema

An extension of the star schema in which dimension tables are normalized into multiple related tables, producing a diagram resembling a snowflake.

Fact Table

The central table in a dimensional schema that stores numeric business measurements, performance metrics, and foreign keys referencing associated dimension tables.

Dimension Table

A table in a dimensional model containing descriptive attributes (such as customer details, products, or locations) that give context to the numerical metrics stored in a fact table.

Multidimensionality

The ability to organize, present, and analyze business data by multiple dimensions, such as sales by region, product, salesperson, and time.

Measures (DW)

The numerical, quantitative values stored in a data warehouse (e.g., money, sales volume, headcount, inventory profit) used to quantify business performance.

Dimensions (DW)

The categorical perspectives or business context (e.g., products, salespeople, market segments, business units, geography) used to slice, filter, and view quantitative measures.

Online Transaction Processing (OLTP)

Computing systems focused on efficiently capturing and recording day-to-day business transactions (from ERP, CRM, and POS) into normalized relational databases.

Online Analytical Processing (OLAP)

Computing systems and tools focused on converting transactional data into multidimensional information to support ad hoc querying, decision analysis, and managerial reporting.

Slice (OLAP Operation)

An OLAP operation that creates a two-dimensional sub-cube from a multidimensional data array by setting a single specific value for one dimension.

Dice (OLAP Operation)

An OLAP operation that extracts a smaller sub-cube from a multidimensional array by selecting specific values or ranges across two or more dimensions.

Drill Down/Up

An OLAP navigation technique that moves between levels of data aggregation, traversing from high-level summaries down to detailed data (drill down) or vice versa (drill up).

Roll Up (OLAP Operation)

An OLAP operation that aggregates data relationships along one or more dimensional hierarchies to compute summarized totals.

Pivot (OLAP Operation)

An OLAP operation that rotates the dimensional axes of a report or query display to provide an alternate analytical perspective on the data.

ETL (Extract, Transform, Load)

The core data integration process responsible for extracting data from multiple source systems, transforming and cleansing it into a consistent schema, and loading it into a data warehouse.

Data Integration

A comprehensive data management discipline that comprises three major technical processes: data access, data federation, and change capture.

Enterprise Application Integration (EAI)

A technology framework providing a vehicle for pushing message-oriented data transactions between source systems and a data warehouse.

Enterprise Information Integration (EII)

An evolving software space enabling real-time, virtual data integration from relational databases, multidimensional databases, and Web services without persistent physical storage.

Data Warehouse Administrator (DWA)

The professional responsible for designing, managing, and maintaining a data warehouse, possessing technical expertise in software, networking, business strategy, and communication.

Data Lake

A large-scale storage architecture designed for Big Data that stores massive volumes of raw, unstructured, semi-structured, and structured data in its native format.

Schema-on-Write

A data management approach used in traditional SQL data warehouses where data must be structured, cleansed, and conformed to a defined table schema before storage.

Schema-on-Read

A data handling approach used in data lakes and NoSQL systems where raw data are stored without a rigid table structure, and schema rules are applied only when data are queried.

Business Report

A written communication artifact containing structured information regarding business matters, designed to improve managerial decision-making using internal and external data.

Metric Management Reports

Business reports designed to track performance through standardized quantitative measures, including Service Level Agreements (SLAs) for external parties and Key Performance Indicators (KPIs) for internal processes.

Balanced Scorecard-Type Reports

Integrated performance reports that assess organizational health across four core perspectives: financial, customer, internal business processes, and learning and growth.

Visual Analytics

An analytical discipline combining information visualization (descriptive and backward-focused) with predictive analytics (future-focused) to support interactive decision exploration.