In the age of digital transformation, enterprises are inundated with massive amounts of data. However, studies have revealed that a significant portion of this data falls into the category of ROT (Redundant, Obsolete, or Trivial), with no legal, regulatory, or business value. This excess data not only consumes valuable storage space but also hinders productivity and poses risks to data security. In this blog post, we will explore the concept of ROT and the importance of defensible data management. Additionally, we will outline a five-step approach utilizing AutoClassification to effectively manage ROT and optimize data governance.
What is ROT?
ROT encompasses three types of data: Redundant, Obsolete, and Trivial.
Redundant data refers to exact duplicates and copies of the same file, taking up unnecessary storage space.
Obsolete data is content that is considered outdated based on an organization’s standards and processes, such as files that haven’t been accessed in years.
Trivial data holds no enterprise value and includes files like temporary files, database files, and out-of-office email replies.
The Benefits of Managing ROT
Defensibly managing and removing ROT offers several advantages for organizations:
Cost Reduction: By eliminating redundant content, storage costs can be significantly reduced.
Enhanced Efficiency: Removing ROT reduces system backup time and resources, leading to improved productivity.
Optimized Content Searches: Filtering out irrelevant content enables employees to find pertinent information more quickly.
Data Security: ROT often contains unknown or duplicate content that may include sensitive personal data, making its elimination crucial for data protection.
Compliance and Lifecycle Management: Properly removing content that has reached the end of its useful lifecycle ensures legal defensibility.
Managing ROT with AutoClassification: A Five-Step Approach
1) Locate.
Scan all content from everywhere across the organization.
Perform comprehensive scans across the organization to identify ROT in all data sources. This includes emails, shared drives, repositories, enterprise content management systems (ECMs), and cloud storage environments.
2) Identify.
Determine the kind, type and context of all content.
Utilize machine learning algorithms to determine the nature of content, distinguishing between ROT and valuable data. The algorithms learn from patterns and auto-identify ROT content, including exact duplicates, near duplicates, temporary files, and irrelevant emails.
3) Analyze.
Know where it is & what it is to make better business decisions.
Reduce risk and gain insights into the location and nature of ROT content to make informed business decisions. Real-time reports provide visibility into the actual costs associated with storing unnecessary data, enabling organizations to devise strategies for reducing storage expenses.
4) Action.
Establish processes and workflows to effectively manage ROT.
AutoClassification helps automate file classification based on content, apply metadata, and define rules for defensible handling of ROT. Create schedules to regularly scan repositories and determine appropriate outcomes for ROT content throughout the enterprise.
5) Monitor.
Implement automated, ongoing scans to identify and manage ROT continuously.
By monitoring and auditing data environments for new and edited content, organizations can apply relevant rules and workflows to move, archive, sequester, or delete ROT on a perpetual basis, without causing system downtime.
Proactively managing ROT is crucial for modern organizations seeking to optimize data governance and maximize operational efficiency. With the assistance of AutoClassification, businesses can streamline the identification and removal of ROT, leading to cost savings, improved productivity, and enhanced data security. Embrace the power of AutoClassification today and embark on a journey towards efficient data management.
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