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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

They emphasize access to and manipulation of large databases of structured data, often a time-series of internal company data and sometimes external data. This data visualization and analytics software helps users create dashboards and power predictive applications and real-time analytics applications.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. Predictive analytics is the most beneficial, but arguably the most complex type. Predictive analytics is the most beneficial, but arguably the most complex type.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics.