Business Analytics (BA): The process of collecting, storing, and analyzing data to help business users make better decisions.

Data Mining: The practice of examining large databases to generate new information and find patterns.

Big Data: Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations.

Predictive Analytics: The use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.

Descriptive Analytics: The process of using data to understand past and present business performance and make informed decisions.

Prescriptive Analytics: Analytics that use optimization and simulation algorithms to advise on possible outcomes and answer ‘what should we do?’

KPI (Key Performance Indicator): A measurable value that demonstrates how effectively a company is achieving key business objectives.

Data Visualization: The graphical representation of information and data to provide an accessible way to see and understand trends, outliers, and patterns.

Dashboard: A visual display of the most important information needed to achieve one or more objectives consolidated and arranged on a single screen.

Data Warehousing: A system used for reporting and data analysis, and is considered a core component of business intelligence.

Machine Learning: A type of artificial intelligence that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.

Data Analytics: The process of analyzing raw data to find trends and answer questions.

Segmentation: The process of dividing a broad consumer or business market into sub-groups based on some type of shared characteristics.

Conversion Rate: The percentage of visitors who take a desired action on a website.

Click-Through Rate (CTR): The ratio of users who click on a specific link to the number of total users who view a page, email, or advertisement.

A/B Testing: A randomized experiment with two variants, A and B, which are the control and treatment in the controlled experiment.

Heat Maps: Graphical representations of data where individual values contained in a matrix are represented as colors.

Customer Lifetime Value (CLV): A prediction of the net profit attributed to the entire future relationship with a customer.

Churn Rate: The rate at which customers stop doing business with an entity.

Web Analytics: The measurement, collection, analysis, and reporting of web data for purposes of understanding and optimizing web usage.

SEO (Search Engine Optimization): The practice of increasing the quantity and quality of traffic to your website through organic search engine results.

Cost Per Click (CPC): A method used by websites to bill based on the number of times a visitor clicks on an advertisement.

Return on Investment (ROI): A performance measure used to evaluate the efficiency of an investment.

Bounce Rate: The percentage of visitors who navigate away from the site after viewing only one page.

Customer Acquisition Cost (CAC): The cost associated in convincing a customer to buy a product/service.

Social Media Analytics: The practice of gathering data from social media websites and analyzing that data using social media analytics tools to make business decisions.

Engagement Rate: A metric that measures the level of engagement that a piece of created content is receiving from an audience.

Funnel Analysis: A method for understanding the flow and conversion rates of potential customers through a website.

Sentiment Analysis: The process of computationally identifying and categorizing opinions expressed in a piece of text.

Data-driven Decision Making: Making decisions that are backed up by hard data rather than making decisions that are intuitive or based on observation alone.