We talk a lot about data in the data world – imagine that! Sometimes, we talk about data at rest, but when do we all rest? Do we even rest as much as our data does? There is some idea that you need to work harder to get more recognition. That if you don’t work hard, you will never feel complete. I don’t think you become complete only because other people appear to value you.
Longing for connection and acceptance is legitimate, but that sense of belonging and being accepted by others isn’t the one thing alone that makes you feel whole. You need a sense inside of you that you are valid, whether anyone else knows it or tells you. That comes from being secure in who you are and giving yourself the space to feel what you need to feel. To me, this comes with resting.
Not sleeping, although sleep is critical. Resting is something woven into your life throughout the day. Resting can be many different things, but it could be staring at the wall, napping (I know that falls under sleeping, too), meditating, or any number of other restful things. Maybe that’s reading an enjoyable book or making art. Whatever it is to you, that feels more restful than the grind of whatever you think you need to do to “become a better version of yourself.”
What is data at rest?
Data at rest refers to inactive data that is stored physically in any digital form (e.g., databases, data warehouses, archives, tapes, off-site backups, or on hard drives). This type of data is not being transferred or processed by systems; rather, it is static and stored in a location until it is needed.
Key Characteristics of Data at Rest
- Inactivity: Unlike data in transit or data in use, data at rest is not actively moving through networks or being processed by systems.
- Storage: It is stored on various physical media, such as hard drives, SSDs, optical disks, or cloud storage services.
- Security: Protecting data at rest often involves encryption, access controls, audits, and other security measures to prevent unauthorized access or breaches.
- Longevity: Data at rest may be kept for extended periods, depending on regulatory requirements, archival purposes, or business needs.
By securing data at rest, organizations can safeguard sensitive information, maintain regulatory compliance, and ensure data integrity and confidentiality.
How do we optimize data so it can be at rest more often?
We talk a lot about optimizing our data meaning how can users and applications get this data faster, and let’s look at all the ways we do this. Optimizing data to ensure it can be at rest more often involves a combination of data management practices, efficient storage strategies, and reducing unnecessary data movement. Here are some strategies to achieve this:
Archival Policies: Implement data archival policies to move infrequently accessed data to lower-cost, long-term storage solutions. This reduces the amount of data actively processed and transferred.
Retention Policies: Define data retention policies to ensure data is stored only as long as necessary for compliance and business needs, then appropriately deleted or archived.
Data Tiering: Use data tiering to automatically move data between different storage types based on access patterns. Frequently accessed data is kept in high-performance storage, while infrequently accessed data is moved to slower, less expensive storage.
Compression: Use data compression techniques to reduce the amount of storage space required, enabling more data to remain at rest without frequent access.
Eliminate Redundancy: Implement data deduplication to remove duplicate copies of data, reducing storage requirements and minimizing unnecessary data movement.
Indexing: Optimize database indexes to speed up query performance and reduce the need to read data repeatedly from storage.
Partitioning: Database partitioning divides large databases into more manageable sections, improving your ability to archive or delete data that is no longer needed.
In-Memory Caching: Use in-memory caching for frequently accessed data to reduce the need to repeatedly read the same data from disk storage.
Batch Processing: Implement batch processing for data-intensive tasks to minimize the frequency of data movement. Batch jobs can process large volumes of data at scheduled intervals, keeping data at rest more often.
Edge Computing: Process data at the edge of the network where it is generated rather than constantly moving it to central servers. This reduces data transfer and keeps data at rest locally.
Access Control: Implement strict access control policies to limit who can move and access data, ensuring that data remains at rest unless absolutely necessary.
Auditing/Data Usage Monitoring: Monitor data usage patterns to identify unnecessary data movements and optimize workflows accordingly.
By employing these strategies, organizations can optimize their data management practices, ensuring that data remains at rest more often, which can enhance security, reduce costs, and improve overall system performance.
Do we protect ourselves as much as our data?
It seems that we tend to optimize our data and systems far more than ourselves. And by optimizing, I don’t mean squeezing out as much performance from ourselves as possible. I mean optimizing in the sense of letting ourselves rest. How do we translate all the ways we let data rest into ways we can let ourselves rest?
1. Archival/Retention Policies/Partitioning
- Humans: Take regular vacations and breaks and divide large projects into smaller, more manageable tasks to avoid feeling overwhelmed.
2. Data Deduplication
- Humans: Eliminate unnecessary activities and focus on essential tasks to reduce workload.
3. Indexing
- Humans: Organize tasks and information for easy access to improve efficiency and reduce stress. Use some method of organizing, whether it’s on paper or digitally.
4. In-Memory Caching
- Humans: Keep essential information and tools readily available to quickly handle frequent tasks.
5. Batch Processing
- Humans: Group similar tasks together and complete them at set times to enhance efficiency. Also known as habit stacking. You can try designating specific times for checking emails or performing administrative tasks rather than doing them sporadically throughout the day.
6. Edge Computing
- Humans: Handle tasks and decisions as close to their origin as possible to reduce delay and effort. Of course, remembering you may want to keep in mind the batch processing example.
7. Access Control
- Humans: Set boundaries and limit commitments to prevent overload and maintain focus. Learn to say no to unnecessary obligations and delegate tasks when possible to avoid taking on too much.
8. Auditing/Data Usage Monitoring
- Humans: Regularly review and adjust routines and habits to improve efficiency and reduce stress. Conduct regular reviews of your goals and tasks to identify areas for improvement and eliminate unproductive habits
Both sets of strategies aim to enhance efficiency, reduce unnecessary activity, and improve overall well-being, whether for data or for yourself.
How much is enough?
The idea of doing less or being less may not be very tempting to you or maybe it’s the thing you’ve been thinking a lot about. I’m not an advocate of less for the sake of less, though. I got to the point where I wanted zero calendar instead of zero inbox. Zero calendar to me means little to no meetings on my calendar, which, as you can imagine, is difficult. At a certain point, the quest for less became a burden.
It’s really about building resilience and knowing what your limits are. No one can tell you what you can and can’t do, as we are all so different. You have to figure out what the right balance is for you. I just find if I’m in a quest to optimize excessively, either my data or my life, it’s time to take a step back.
Do I need another degree, certification, award, or whatever else thing I think I need? Is my data optimized well enough? My data may not be optimized well enough, but is it good enough – not perfect – just good enough? The same goes for my life. I will never feel altogether better if I’m constantly in optimizing mode or seeking the acceptance of others above the acceptance of myself. Sometimes, the best thing one can do is rest more.
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