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Data Mining vs Data Warehousing: 8 Critical Differences

Analytics Vidhya

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

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Fundamentals of Data Mining

Data Science 101

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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What is data architecture? A framework to manage data

CIO Business Intelligence

Data architecture components A modern data architecture consists of the following components, according to IT consulting firm BMC : Data pipelines. A data pipeline is the process in which data is collected, moved, and refined. It includes data collection, refinement, storage, analysis, and delivery.

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How Data Cleansing Helps Predictive Modeling Efforts

TDAN

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. The discipline is a key facet of the business analyst role. This is the purview of BI.