Data Analytics Glossary

Kaggle is a platform for data science competitions and a community of data scientists and machine learning engineers with a vast range of datasets, tools, and resources. Learn how businesses can leverage Kaggle's resources and community to improve their data science capabilities and drive innovation in their industries.

Learn about Linear Discriminant Analysis (LDA), a dimensionality reduction technique used in data science for classification tasks. Reduce the complexity of data and extract valuable insights. Explore applications in customer segmentation and fraud detection.

Lead Scoring is a method used to rank potential customers based on their behavior and demographic characteristics, helping sales and marketing teams prioritize leads for improved efficiency and effectiveness.

Learn more about libraries in software development and how they can be useful. This article provides a basic overview of libraries, their role in software tools, and how they can be implemented in different contexts.

The article provides an overview of Customer Lifetime Value (CLV), explaining its importance in making informed decisions about customer acquisition, retention strategies, and resource allocation. It also highlights common problems and solutions related to CLV calculations, as well as the various uses of CLV in marketing, customer retention, product development, and financial forecasting.

Looker is a cloud-based business intelligence software and big data analytics platform that provides a centralized platform for data analysis. Its flexibility, scalability, and ease of use make it a popular choice among data scientists and business analysts. With Looker, businesses can analyze customer behavior, monitor KPIs, and visualize data to gain insights and make data-driven decisions.

Louvain is an unsupervised algorithm for community detection in networks or graphs. Learn how it works, its key highlights, and how it can be applied in business. Read on to find out more.

Learn about machine learning, a subfield of artificial intelligence that enables computers to automatically improve their performance on a specific task without being explicitly programmed. Discover the key highlights of machine learning and how to apply it to your business to gain insights, automate tasks, and improve customer experience. Check out some helpful references and follow these steps to apply machine learning to your business.

Learn about market basket analysis, a powerful analytics use case that can help you uncover hidden patterns in customer purchasing behavior. Also known as product basket analysis, this technique allows you to identify which products are frequently purchased together, enabling you to optimize your sales and marketing strategies. Check out our glossary entry and start leveraging market basket analysis today.

Learn about the median, a basic data analytics concept, on Graphext's glossary. Understand its definition, how it differs from the mean, and when to use it.

Learn how to handle missing values in your data with our advanced guide on missing value treatment. Explore various methods to impute or remove missing data, and ensure your analyses are accurate and reliable. Visit our website to read more!

Learn about the concept of mode in data analytics and its usefulness in determining the most common value in a dataset. Discover its applications in business and how it can provide valuable insights for decision-making. References from Statistics How To, Investopedia, and Khan Academy provided.

Learn about the modern data stack, a collection of technologies and tools used to manage and analyze data. Discover the benefits of data warehouses, data lakes, and data meshes, and how businesses can use them to make data-driven decisions. Explore the future of data architecture and gain insights to inform your strategies and stay competitive.

Learn the basics of multivariate analysis, also known as multivariable analysis, multiple regression analysis, multivariate statistics, and more. Discover how it can be used in data analytics and gain a deeper understanding of this important concept. Find out more on Graphext.

Learn about mutual information correlation in data analytics. Discover how it works and its impact on data analysis. Read more on the Graphext glossary.

Learn about Natural Language Processing (NLP) and Image Models in data science. Discover how these concepts are applied in business to gain valuable insights and automate tasks. Explore resources to learn more about NLP and Image Models, including sentiment analysis, object detection, image classification, and machine translation.

NPS Analysis is an advanced analytics use case for measuring customer satisfaction. Learn more about NPS Analysis and how it can improve your business with Graphext's glossary.

This article provides an introduction to natural language processing (NLP), a subfield of data science that deals with human language and computers. Learn about NLP tasks such as tokenization and named entity recognition, and how deep learning models have revolutionized NLP. Discover how businesses can apply NLP to improve customer support, sentiment analysis, and machine translation.

Learn about network analytics and graph analytics with our advanced glossary. Understand the intricacies of webflow status and how it affects your network analysis. Created and curated by Victoriano Izquierdo.

Neural networks are a type of machine learning algorithm modeled after the human brain. They can be used for various tasks, including image recognition, natural language processing, and prediction. Learn how neural networks can improve business operations.

Learn about no-code data analytics and its importance in business analytics. Discover how to leverage this concept and streamline your data analysis process without coding skills. Read more at the Graphext Glossary.

Meta Description: Learn about noise reduction, an advanced technique used to remove unwanted noise from data and improve accuracy in data analysis. Find out more on Graphext's glossary.

Learn about null values, also known as NaNs or Nones, in data analysis. Understand their basic properties and significance in data manipulation. Explore this term in the Graphext glossary.

Learn about the data analytics concept of outliers. Find out what they are, why they matter, and how to identify them. Visit the Graphext glossary for more information.