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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information. What is Data Science? financial dashboard (by FineReport).

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Challenges of machine learning There are some ethical concerns regarding machine learning, such as privacy and how data is used. Unstructured data has been gathered from social media sites without the users’ knowledge or consent.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Prescriptive Analytics provides precise recommendations to respond to the query, “What should I do if ‘x’ occurs?”

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. This data is gathered into either on-premises servers or increasingly into cloud data warehouses and data lakes.

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A Guide to Data Analytics in the Travel Industry

Alation

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? How is data analytics used in the travel industry?