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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Data Platforms.

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How AI and ML Can Transform Data Integration

Smart Data Collective

The data integration landscape is under a constant metamorphosis. In the current disruptive times, businesses depend heavily on information in real-time and data analysis techniques to make better business decisions, raising the bar for data integration. Why is Data Integration a Challenge for Enterprises?

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Managing risk in machine learning

O'Reilly on Data

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Data Platforms.

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Security In Automated Document Processing: Ensuring Data Integrity And Confidentiality

Smart Data Collective

A security breach could compromise these data, leading to severe financial and reputational damage. Moreover, compromised data integrity—when the content is tampered with or altered—can lead to erroneous decisions based on inaccurate information. You wouldn’t want to make a business decision on flawed data, would you?

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Why you should care about debugging machine learning models

O'Reilly on Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. There are several known attacks against machine learning models that can lead to altered, harmful model outcomes or to exposure of sensitive training data. [8] 2] The Security of Machine Learning. [3]

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Big Data, Machine Learning and Alteryx Inspires 2019

David Menninger's Analyst Perspectives

This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center. The strong attendance was a reflection of the strong growth Alteryx has experienced over the last year; roughly 50% growth year-over-year.