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18 Examples Of Big Data Analytics In Healthcare That Can Save People

datapine

Big data has changed the way we manage, analyze, and leverage data across industries. One of the most notable areas where data analytics is making big changes is healthcare. The application of big data analytics in healthcare has a lot of positive and also life-saving outcomes. 3) Real-Time Alerting.

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Predictive Analytics Made Last Summer The Season Of Altcoins

Smart Data Collective

Data analytics has been the basis for the cryptocurrency market for years. In 2018, a study from the University of Bremen in Germany discussed some of the implications of big data for the altcoin industry. They found that predictive analytics algorithms were using social media data to forecast asset prices.

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A Guide to Data Analytics in the Travel Industry

Alation

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. What’s more, many companies struggle with rigid legacy technologies that increase the risk of a data breach.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. It’s an extension of data mining which refers only to past data.

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The future of casino marketing strategy is digital plus data

BizAcuity

In 2018, the US Supreme Court’s decision to legalize sports betting was historic. Thanks to data analytics, these decisions can now be backed by data. Real-time decisions can be taken in line with data insights. Predictive Analytics. Gaming analytics is still evolving. Player Churn.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

It enables orchestration of data flow and curation of data across various big data platforms (such as data lakes, Hadoop, and NoSQL) to support a single version of the truth, customer personalization, and advanced big data analytics. Shared Data Catalog to preserve context and enforce Governance.