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White paper: Graph visualization and AI

Cambridge Intelligence

The State of AI in 2023 – McKinsey) A fraud visualization app to spot fake Amazon reviews written by AI Our white paper, Graph visualization and artificial intelligence , looks at how successful businesses work with the latest graph visualization and AI technologies.

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3 tips for finding analytics talent

Tableau

By communicating your need for analytics talent within the strategic framework of building a Data Culture, you’ll not only build a stronger case for more resources, you’ll also help prospective employees better understand how they’ll impact the organization’s success. Start with a specific project. Start there. US48214821, September 2021.

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University Web Developer Programs Must Prep Students For Big Data Era

Smart Data Collective

According to economic analysts, the market size for big data is currently estimated to be $203 billion. Unfortunately, there is a growing shortage of data scientists. As we pointed out in a previous post, a white paper from PwC shows that the time that it takes to fill a Data scientist job is twice as high as the national average.

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3 tips for finding analytics talent

Tableau

By communicating your need for analytics talent within the strategic framework of building a Data Culture, you’ll not only build a stronger case for more resources, you’ll also help prospective employees better understand how they’ll impact the organization’s success. Start with a specific project. Start there. US48214821, September 2021.

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Enterprise fraud management, AI and data visualization

Cambridge Intelligence

While it has always been a data-intensive process, enterprise fraud management today is more complex and more important than ever. This blog post explores the evolving role of enterprise fraud management, examines the impact of AI and showcases the importance of visual data analysis. What is enterprise fraud management?

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5G use cases that are transforming the world

IBM Journey to AI blog

Edge computing Edge c omputing, a computing framework that allows computations to be done closer to data sources, is fast becoming the standard for enterprises. According to this Gartner white paper (link resides outside ibm.com), by 2025, 75% of enterprise data will be processed at the edge (compared to only 10% today).

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Leveraging Generative AI in Genomics with IBM’s watsonx Platform

IBM Data Science in Practice

Genetic Data Analysis : Advanced AI techniques, such as deep learning, are used to analyze complex genetic data, providing deeper insights into genetic variations and their implications. These insights can lead to the identification of novel genetic markers associated with diseases.

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