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The benefits of automated error handling in ECM migration

In the world of data-driven decision-making, mistakes are going to happen. Even the best data systems will have errors sometimes. The most important is how those errors are handled. To get the most out of data, organizations need a solid way to deal with errors.

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Navigating ECM migration: Challenges and solutions

Enterprise content management (ECM) systems are crucial for modern businesses, making operations smoother, improving teamwork, and ensuring content is managed well. But getting ECM right can be tough. It takes careful planning, a clear understanding of what the organization needs, and a willingness to tackle problems head-on.

In this article, we dive into the common challenges companies face when implementing ECM and share some practical solutions.

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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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Data integrity vs. data quality: Achieving data quality and validation

When data integrity is discussed, it involves ensuring that the data within an organization is complete, accurate, consistent, accessible, and secure. These aspects together determine the reliability of the data. Assessing data quality against these criteria helps determine how suited the data is for its intended use. For organizations relying on data for decision-making, providing data access to teams, and offering data to customers, maintaining good data quality and integrity is crucial.