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Glossary Business Analytics Terms

4 min read



Mario Galal

BI Analyst

mario@nilebi.com

Analytics: The process of examining data to uncover patterns, trends, and insights for decision-making.

Big Data: Extremely large datasets that require advanced methods and tools to analyze effectively.

Business Intelligence (BI): Technologies and strategies used to analyze business information and support better decision-making.

Dashboard: A visual representation of key performance indicators (KPIs) and metrics.

Data Cleaning: The process of removing or correcting inaccurate, incomplete, or irrelevant data from a dataset.

Data Mining: The practice of exploring large datasets to identify patterns, correlations, and trends.

Data Modeling: Creating a framework that organizes and defines data relationships for analysis.

Data Visualization: Graphical representations of data, such as charts, graphs, and maps, to communicate insights.

Descriptive Analytics: Analyzing historical data to understand past performance.

Diagnostic Analytics: Identifying the causes behind specific trends or anomalies in data.

Predictive Analytics: Using historical data and algorithms to forecast future outcomes.

Prescriptive Analytics: Recommending actions based on insights derived from data analysis.

ETL (Extract, Transform, Load): A process for extracting data from different sources, transforming it into a usable format, and loading it into a system.

Key Performance Indicators (KPIs): Quantifiable measures used to evaluate success in meeting objectives.

Machine Learning: Algorithms that enable systems to learn from data and improve performance over time.

Natural Language Processing (NLP): An area of AI focused on enabling computers to understand and process human language.

Predictive Modeling: The creation of models to forecast future trends or behaviors.

Real-Time Analytics: The analysis of data as it is generated or received.

Self-Service Analytics: Tools that allow users without technical expertise to access and analyze data independently.

Structured Data: Data that is organized in a defined format, such as tables.

Unstructured Data: Data that doesn’t have a predefined format, such as images, videos, or social media posts.

Data Governance: The policies and practices ensuring the proper management of data within an organization.

Data Warehouse: A centralized repository for storing and managing large volumes of data.

Data Lake: A storage system for large amounts of raw, unstructured, or semi-structured data.

Correlation: A statistical measure indicating the extent to which two variables change together.

Outlier: A data point that significantly differs from others in the dataset.

Regression Analysis: A statistical technique used to predict the value of one variable based on another.

Time Series Analysis: Analyzing data points collected or recorded at specific time intervals.

Cloud Analytics: Data analysis performed using cloud-based tools and infrastructure.

Benchmarking: Comparing performance metrics against industry standards or competitors to identify areas for improvement.

 

 

This glossary introduces core concepts in business analytics, aiding beginners in understanding terminology for practical applications.

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