Business data has been around for decades, but it has become apparent that as new, emerging technologies such as AI, IoT, and predictive analytics continue to make their mark, having access to sufficient and accurate data has never been more critical.
However, the past year has been like no other and, due to the current climate, management of this data may have taken a step back with organizations failing to maintain quality information without the use of increased automation effectively.
Organizations need to understand the significance of manually managing and storing data, particularly if they hold sensitive information.
With businesses holding more critical data than before, companies need to ensure they have a robust automation framework to reduce human error and data mismanagement risks.
More organizations need to take a forward-vision look toward automation tools that enable businesses to collect, store, manage and analyze quality data.
Utilizing tools such as machine learning designed to carry out repetitive tasks in aggregation and curation, enterprises can remove the need, or at least reduce the time spent on manual data management.
Gartner predicts that automation will reduce manual Data Management tasks by 45 percent by as soon as 2022; enabling businesses to save time and money and enabling CTOs and CIOs to spend their time on business-critical tasks.
With human error playing a pivotal role in data quality and mismanagement, now is the time to let automation use their data and make the most of what they have.
Organizations need to understand the significance of manually managing and storing data, particularly if they hold sensitive information.
With businesses holding more critical data than before, companies need to ensure they have a robust automation framework to reduce human error and data mismanagement risks.
More organizations need to take a forward-vision look toward automation tools that enable businesses to collect, store, manage and analyze quality data.
Utilizing tools such as machine learning designed to carry out repetitive tasks in aggregation and curation, enterprises can remove the need, or at least reduce the time spent on manual data management.
Gartner predicts that automation will reduce manual Data Management tasks by 45 percent by as soon as 2022; enabling businesses to save time and money and enabling CTOs and CIOs to spend their time on business-critical tasks.
With human error playing a pivotal role in data quality and mismanagement, now is the time to let automation use their data and make the most of what they have.
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