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Automated records management: What is it and what are its benefits?

Managing records is extremely important for businesses, and many successful companies are starting to automate this task as they move towards digital methods. Let’s start by understanding what record management is all about.

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Implementing governance applications to content

In today’s world, organizations know data governance is key to managing data well. It helps ensure data quality, meets regulations, and guides decision-making. By setting up good data governance, companies can make the most of their data and succeed.

In this article, we’ll guide you through some important steps to implement data governance effectively.

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GDPR Data discovery: Ensuring compliance in the digital age

With data breaches on the rise and stricter data privacy laws worldwide, organizations must reassess how they manage personal data of their consumers. One crucial aspect of this is understanding “Data Discovery.”

Data discovery involves cataloging the data an organization collects, how it’s utilized, stored, processed, and its movement within and outside the organization.

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How can we ensure that machine learning models are not biased?

Bias has been an intrinsic part of human existence throughout history. Despite our efforts to eliminate bias and make impartial decisions, it persists. Ironically, even when we entrust algorithms with decision-making to reduce human bias, these very algorithms often exhibit biases of their own.

To ensure fair and ethical machine learning models, we must actively combat bias. In this article, we’ll explore ways to ensure that ML models are not biased.

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The ethical implications of AI and machine learning

Topics like “data ethics” and “AI ethics” use to be topics that weren’t really discussed. Nowadays, the world’s largest tech firms are hiring more people to deal with the ethical issues that come from using a lot of data, especially for AI.

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What are some challenges of AI and machine learning?

Machine learning plays a significant role in our daily lives. The global machine learning market is expected to grow notably in 2024, leading to a rising demand for professionals in this field. AI and machine learning careers have seen substantial growth, providing well-paying and satisfying opportunities over the past four years. Despite these perks, entering the world of machine learning comes with its own set of challenges.

This article will explore some challenges faced in these fields, as professionals strive to gain essential skills and venture into it.