Business Intelligence and Big Data

Big Data

data that is enormous in size and highly complex, ranging from sensor data to social medial

Key Characteristics of Big Data

• volume (size of date)

• velocity (speed data is generated/processed)

• variety (different types of data sources/formats)

• veracity (trustworthiness and quality)

• vulnerability (risks tied to use of personal data)

• value (usefulness or benefits derived from data)

Data Warehouse

large database holding business data from multiple sources across an organization, enabling cross-functional decision making

Data Mart

smaller, more focused version of a data warehouse, often used by specific departments or small businesses

Data Lake

stores all data in its raw, unaltered form. no ETL process is applied until data retrieval

Extract, Transform, Load (ETL) Process

extract data from multiple sources, processes it into unified format suitable for analysis, and loads it into a data warehouse

Business Intelligence

range of applications, technologies, and practices designed to extract, transform, analyze, and visualize data to support better decision-making

Analytics

extensive use of data, quantitative analysis, and statistical tools to support evidence-based decision-making

Descriptive Analytics

preliminary stage of analysis focused on identifying patterns and answering questions like who, what, where, and when

Visual Analytics

pictorial or graphical data presentations (e.g. word clouds or conversion funnels)

Regression Analysis

identifies relationships between variables to make predictions

Predictive Analytics

techniques used to analyze current data and make informed predictions about future probabilities and trends

Time Series Analysis

focuses on time-based data trends to extract meaningful statistics

Optimization

allocating resources effectively to minimize costs or maximize profits

Simulation

replicating real-world systems responses to various inputs

Scenario Analysis

predicts future outcomes based on potential events

Monte Carlo Simulation

explores thousands of possible outcomes factoring in numerous variables and their potential values

Data Mining

process of exploring large amounts of data for hidden patterns and trends to inform decision-making

Self-Service Analytics

empowers end users to independently access approved data sources, perform analyses, and make decisions

Data Governance

management of data’s availability, usability, integrity, and security within an organization; ensures compliance with regulatory requirements

Four Vs of Big Data

• volume

• variety

• velocity

• veracity

now six

• vulnerability

• value