Remove 2020 Remove Data Analysis Remove Predictive Analytics
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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

New technologies, especially those driven by artificial intelligence (or AI), are changing how businesses collect and extract usable insights from data. Here are the six trends you should be aware of that will reshape business intelligence in 2020 and throughout the new decade. New Avenues of Data Discovery.

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How Big Data is Changing the World of Investing

Smart Data Collective

Last year, in an article that talked about the impact big data has on finance, we said that location data sets can make investing easier. Companies spent nearly $11 billion on financial analytics in 2020. For instance, real-time car purchases can help predict the price of Rolls Royce shares in the near future.

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IBM Emphasizes The Benefits Of Data Analytics For Renewable Energy

Smart Data Collective

Kaiserwetter, a German data analytics firm that specializes in managing wind farms, has developed a pioneering system that combines several digital technologies that are making headway. Big data is going to be essential to help them meet those demands.

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Navigating the 2024 Data Analyst career growth landscape

Pickl AI

Summary: The blog delves into the 2024 Data Analyst career landscape, focusing on critical skills like Data Visualisation and statistical analysis. It identifies emerging roles, such as AI Ethicist and Healthcare Data Analyst, reflecting the diverse applications of Data Analysis.

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Curve Finance Data Challenge Review & Insights Research

Ocean Protocol

Abstract This research report encapsulates the findings from the Curve Finance Data Challenge , a competition that engaged 34 participants in a comprehensive analysis of the decentralized finance protocol. Part 1: Exploratory Data Analysis (EDA) MEV Over 25,000 MEV-related transactions have been executed through Curve.

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Data-driven Attribution Modeling

Data Science Blog

Additionally, it allows for quick implementation without the need for complex calculations or data analysis, making it a convenient choice for organizations looking for a simple attribution method. One of its main advantages is its simplicity; it is a straightforward and easy-to-understand approach. References Zhao, K., Mahboobi, S.

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Optimizing clinical trial site performance: A focus on three AI capabilities

IBM Journey to AI blog

Research conducted by the Tufts Center for Study of Drug Development and presented in 2020 found that 23% of trials fail to achieve planned recruitment timelines 1 ; four years later, many of IBM’s clients still share the same struggle. AI models can be designed to detect anomalies in real-time site performance data.

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