Managing data is a big challenge facing today’s businesses. Many organizations don’t think they have enough budget, staff, or knowledge to create and maintain a useful information governance program. Data management— the practice of organizing and maintaining data processes to meet ongoing information lifecycle needs— is becoming increasingly difficult due to rapid changes in technology, regulations, information usage, and organizational priorities.
According to computing.co.uk, "The penalties for improper use of data are increasing thanks to GDPR. A 2016 Gartner Data Quality Market Survey estimated that the average cost of poor data quality grew from $8.8 million in 2015 to $9.7 million in 2016, a 10 percent increase."
Hence, improving data quality and accuracy is critical. Yet, while organizations have access to huge volumes of data, often times they don’t have the resources to act on this information.
Automation is the Solution
Automation is becoming a crucial requirement of data management, with IT resources needing to be used more strategically now than ever before. Historically, IT budget was spent on precautionary measures to mitigate risk and reduce costs to the organization, instead of on strategic initiatives that can actually help generate revenue for the organization.
Now with automated data, large amounts of information can be processed automatically rather than manually. Data automation provides more accurate data while reducing mundane tasks— thus speeding up the processing of large volumes of data and creating a foundation for future analytics (for revenue generation).
Automation and Beyond
Data automation also eliminates the need to make regular manual updates and deletions of records by configuring policies. Doing so will provide current, relevant data that should help businesses improve decision making and risk management planning. Furthermore, automation can be used for functions such as backup and archiving, data de-duplication, policy management, recovery and restoration, and much more.