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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. Forecasting models. XLSTAT is an Excel data analysis add-on geared for corporate users and researchers. Analytics, Data Science

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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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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. QuickSight offers scalable, serverless visualization capabilities.