Mastering Data Storage: 7 Essential Practices

2025-12-27 Data Storage Case Studies Comments Off on Mastering Data Storage: 7 Essential Practices

Mastering Data Storage: Seven Strategic Pillars for Modern Organizations

In our frenetic, data-driven world, efficiently managing the immense oceans of information isn’t just a good idea; it’s absolutely paramount. Organizations that truly master data storage don’t just safeguard their most precious digital assets. No, they actually pave a wide, clear path for innovation, unlock new growth opportunities, and, frankly, gain a serious competitive edge. It’s about transforming a necessity into a strategic powerhouse, something I’ve seen firsthand countless times.

Think about it: every transaction, every customer interaction, every research breakthrough — it all generates data. And if you can’t access it quickly, secure it robustly, and scale it effortlessly, well, you’re leaving a lot on the table. It’s like trying to run a marathon with lead weights tied to your ankles, you just won’t perform your best. Let’s dig into some actionable strategies that can elevate your approach.

1. Implement a Tiered Storage Strategy: Not All Data is Created Equal

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Imagine your data as different types of luggage on a journey. You wouldn’t keep your passport, wallet, and phone in a dusty old trunk in the attic, would you? Of course not, you’d have them close at hand. Similarly, not all data demands the same level of immediate access or performance. This is where a shrewd tiered storage strategy becomes your best friend, allowing you to categorize information based on its access frequency, criticality, and overall business value. This isn’t just about saving a few bucks; it’s about intelligent resource allocation.

Understanding Your Data’s Lifecycle

The first step, and honestly, the most crucial, involves a thorough data classification exercise. You need to identify what data is ‘hot’ – accessed constantly, critical for real-time operations, perhaps customer-facing or transactional. Then there’s ‘warm’ data, maybe accessed frequently but not moment-to-moment, perhaps monthly reports or operational analytics. And finally, ‘cold’ data, which is rarely accessed but must be retained for compliance, historical analysis, or long-term archiving. Think of legal documents from five years ago or legacy project files.

Categorizing your data this way helps you avoid the common pitfall of treating everything as high-priority, which is incredibly inefficient and costly. When I was consulting with a medium-sized e-commerce firm, they were storing every single piece of customer interaction, regardless of age, on their fastest, most expensive SSD arrays. They were bleeding money! Once we helped them classify their data and move older, less accessed records to more cost-effective tiers, their storage costs plummeted by nearly 40% in the first year alone. It was a revelation for them, you see.

Technologies for Every Tier

Once you’ve got a handle on your data classifications, you can align specific storage technologies to each tier:

  • Hot Data (Tier 0/1): For your mission-critical, high-transactional data, nothing beats the speed of Non-Volatile Memory Express (NVMe) SSDs or traditional enterprise-grade Solid State Drives. These offer blistering input/output operations per second (IOPS) and minimal latency, essential for databases, virtual machines, and real-time analytics. They’re pricy, sure, but the performance dividends are often worth every penny for your most active datasets.
  • Warm Data (Tier 2): Here, you’ll find a sweet spot between performance and cost. High-capacity, high-performance Hard Disk Drives (HDDs), perhaps in a hybrid array with some SSD caching, can serve this tier admirably. Network-Attached Storage (NAS) or Storage Area Networks (SANs) often house this data, providing a balance for frequently accessed but not real-time critical information.
  • Cold Data (Tier 3/Archival): This is where you really start to optimize costs. Object storage in the cloud (think Amazon S3 Glacier, Azure Blob Archive, Google Cloud Storage Coldline) is a fantastic, highly scalable, and extremely cost-effective option for long-term retention. For even deeper, more infrequent archiving, traditional tape libraries (yes, they’re still around and incredibly reliable for certain use cases!) or even optical disc storage can be considered. The key is understanding that retrieval times will be longer, but the cost per gigabyte is significantly lower.

By intelligently shifting data across these tiers as its value and access patterns change over its lifecycle, you achieve a delicate, yet powerful, balance of performance, accessibility, and cost-efficiency. It’s truly a game-changer for budget management and operational agility.

2. Prioritize Data Security and Compliance: The Unbreakable Foundation

In an age where data breaches make daily headlines and regulatory fines can cripple a company, data security isn’t just important, it’s the absolute bedrock of trust and business continuity. Protecting sensitive information is non-negotiable, end of story. Organizations simply can’t afford to be complacent here; the fallout from a security incident is always far-reaching, encompassing financial penalties, reputational damage, and a complete erosion of customer confidence.

The Dual Pillars of Protection

Think about securing your data from two angles: when it’s just sitting there, at rest, and when it’s actively moving, in transit. Robust encryption methods are your primary defense for both.

  • Data at Rest: This means encrypting files and databases on your storage devices – whether they’re on-premises servers, cloud storage buckets, or even individual laptops. Technologies like AES-256 encryption should be standard. It transforms your data into an unreadable cipher text, meaning if an unauthorized party somehow gains access to your storage, they’re met with gibberish. Disk encryption, database encryption, and even file-level encryption all play a vital role here. Consider how devastating a lost unencrypted hard drive would be, for instance.
  • Data in Transit: When data travels across networks – from a user’s computer to a server, between data centers, or to a cloud service – it’s vulnerable to interception. Secure Socket Layer/Transport Layer Security (SSL/TLS) protocols are essential for encrypting this data stream, ensuring that communications remain private and untampered with. Whether it’s VPNs, secure FTP, or HTTPS for web traffic, always ensure your data’s journey is a private one. You wouldn’t send sensitive mail in an open postcard, would you? Treat your data with the same caution.

Beyond encryption, strict access controls are paramount. Implementing Role-Based Access Control (RBAC) ensures that users can only access the data absolutely necessary for their job functions. A sales associate doesn’t need access to HR records, nor does a junior developer need to modify production database schemas. Granular permissions prevent insider threats and limit the blast radius should an account be compromised.

Navigating the Regulatory Labyrinth

The compliance landscape is a dense jungle, and it’s constantly growing. Regulatory bodies around the world are increasing their scrutiny, and ignorance is definitely not a viable defense. Regular, thorough audits are critical not only for internal security posture checks but also to demonstrate adherence to industry-specific standards and governmental regulations.

  • GDPR (General Data Protection Regulation): If you handle data for anyone in the EU, or even process data from EU citizens, this is your north star. It mandates strict rules for data privacy, consent, and breach notification. Ignoring it can lead to eye-watering fines, we’re talking millions, sometimes billions, of euros.
  • HIPAA (Health Insurance Portability and Accountability Act): Essential for any organization dealing with protected health information (PHI) in the US. It requires robust safeguards for medical records and patient data.
  • SOC 2 (Service Organization Control 2): A voluntary compliance standard for service organizations, particularly relevant for cloud providers, that specifies how they should manage customer data based on five ‘trust service principles’ – security, availability, processing integrity, confidentiality, and privacy.
  • ISO 27001: An international standard for information security management systems (ISMS), providing a comprehensive framework for managing information security risks.

Maintaining rigorous documentation of your security policies, audit trails, and incident response plans is crucial. When regulators come knocking, you need to show, not just tell, that you’re doing your due diligence. A robust security posture maintains customer trust, protects your brand, and quite frankly, helps you sleep better at night, knowing you’ve minimized those potential penalties.

3. Establish Clear Data Governance Policies: Taming the Data Beast

Without clear guidelines, data, no matter how valuable, can quickly devolve into an unmanageable, chaotic mess. It’s like having a sprawling library with no cataloging system; you know the books are there, but finding anything useful becomes a nightmare. Establishing robust data governance policies isn’t just about setting rules; it’s about creating a framework that defines how your organization manages its data throughout its entire lifecycle. This fosters accountability, ensures data quality, and ultimately makes your data a reliable asset rather than a liability.

Crafting a Data Blueprint

Data governance is the blueprint for how data is handled across your organization. It answers fundamental questions:

  • Who owns the data? Defining data ownership is critical. Is it the department that created it, or the department that uses it most? Clear lines of responsibility prevent ambiguity and ensure someone is ultimately accountable for its quality and integrity.
  • Who can access, modify, or delete data? This circles back to access controls, but governance takes it a step further by defining the policies behind those controls. What are the criteria for granting access? How are modifications tracked? Under what circumstances can data be permanently deleted?
  • What are the standards for data quality? Data is only as good as its quality. Governance policies establish rules for data entry, format consistency, accuracy, and completeness. This might involve setting up data validation checks at the point of entry or defining acceptable error rates. Poor data quality can lead to flawed insights, wasted resources, and incorrect business decisions, so it’s a vital consideration.
  • How long should data be retained? Data retention policies are crucial for both compliance and operational efficiency. You can’t just keep everything forever; that’s expensive and clutters your systems. On the other hand, deleting data prematurely can lead to compliance violations or loss of valuable historical context.
  • What is the data’s lineage? Understanding where data originated, how it has been transformed, and where it has moved within your systems is critical for trust and auditing. Data lineage tools can map these journeys, providing transparency and helping to troubleshoot issues.

These policies should be documented, regularly reviewed, and communicated widely. They shouldn’t be dusty documents hidden away on a server; they need to be living guidelines that everyone understands and adheres to.

Accountability Through Policy and Practice

Implementing role-based access controls (RBAC) becomes the practical enforcement arm of your data governance policies. These controls ensure that specific roles (e.g., ‘Financial Analyst’, ‘Marketing Manager’, ‘HR Administrator’) are granted only the necessary permissions to perform their duties. This significantly reduces the risk of accidental data modification or unauthorized access.

Beyond access, maintaining detailed audit logs is non-negotiable. Every access, every modification, every deletion – it needs to be recorded. These logs are invaluable for:

  • Accountability: If an issue arises, you can trace back actions to specific users, holding individuals accountable for their data handling.
  • Troubleshooting: They help diagnose errors or understand how a data inconsistency might have occurred.
  • Compliance: Regulators often require audit trails to demonstrate adherence to privacy and security mandates.
  • Security Investigations: In the event of a breach, logs are critical for understanding the scope of the incident and identifying the point of entry.

When I was working with a healthcare startup, they initially had a fairly loose data access policy. It was well-intentioned, aiming for flexibility, but it meant almost anyone could access patient records for ‘operational needs.’ We helped them implement granular RBAC based on clear governance policies, cutting down unauthorized access attempts by over 70% in three months. It wasn’t about restricting people; it was about protecting sensitive patient information and fostering a culture of mindful data stewardship. It really brought home how critical these policies are for both security and operational integrity.

Effective data governance transforms your data from a potential liability into a highly reliable and strategic asset, empowering informed decision-making across the board.

4. Automate Data Backup and Recovery Processes: Your Digital Safety Net

Let’s be brutally honest: manual backups are a recipe for disaster. They’re prone to human error, often get forgotten amidst daily chaos, and can easily lead to inconsistent, unreliable data copies. In today’s landscape, where a single ransomware attack or hardware failure can bring an entire business to its knees, automating your data backup and recovery processes isn’t merely a convenience; it’s a fundamental necessity. It’s your digital safety net, and you really want it to be robust, don’t you?

Beyond the Basic Backup: Resilience by Design

Automation ensures consistency, reliability, and most importantly, that you actually have a recent, viable copy of your data when disaster strikes. But not all backups are created equal, and a smart strategy employs a mix:

  • Full Backups: A complete copy of all your data. While comprehensive, they take the longest and consume the most storage space. You might do these weekly or monthly.
  • Incremental Backups: After a full backup, these only save data that has changed since the last backup (of any type). They’re fast and efficient on storage, but recovery can be slower as it requires restoring the full backup plus every subsequent incremental.
  • Differential Backups: These save all data that has changed since the last full backup. They’re a middle ground – faster than full backups, take more space than incremental, but recovery is quicker as you only need the last full and the last differential backup.

Many organizations leverage a blend, perhaps daily incremental backups with weekly differentials and monthly fulls. The ‘3-2-1 Rule’ of backup is still golden: maintain at least three copies of your data, store them on at least two different types of media (e.g., disk and cloud), and keep at least one copy offsite. This simple rule drastically reduces the risk of total data loss.

Implementing automated backup software, whether it’s an on-premises solution or a cloud-based service, ensures these processes run on schedule, without human intervention. These systems can often perform deduplication and compression too, further optimizing storage space and network bandwidth, which is a neat bonus.

And here’s a crucial, often overlooked, point: immutable backups. This isn’t just a fancy term; it’s a lifesaver against ransomware. Immutable backups cannot be modified, encrypted, or deleted for a set period, even by administrators. If ransomware encrypts your live systems, you know you have a clean, uncorrupted copy to restore from. This single feature is, in my opinion, one of the strongest defenses against a modern ransomware attack, offering unparalleled peace of mind.

The Acid Test: Why Recovery Drills Matter

Having backups is one thing; being able to recover from them is entirely another. I’ve heard countless horror stories from companies who diligently backed up their data, only to find their recovery procedures failed spectacularly when they actually needed them. It’s a bit like having a fire extinguisher but never checking if it’s charged.

Regularly testing your recovery procedures isn’t an optional extra; it’s absolutely vital. This means:

  • Simulated Disasters: Periodically conduct drills where you simulate a data loss event and attempt to restore critical systems and data from your backups. Document every step, identify bottlenecks, and refine the process.
  • Defining RTO and RPO: Establish clear Recovery Time Objectives (RTO) – how quickly you need systems back online, and Recovery Point Objectives (RPO) – how much data loss you can tolerate (e.g., losing the last 15 minutes of data is acceptable, but not the last 24 hours). These metrics should guide your backup frequency and recovery strategy.
  • Full System Restores: Don’t just test individual file restores. Can you bring an entire database or application server back online from scratch using your backup and recovery tools? This is the ultimate test of your plan.
  • Offsite Recovery: If your offsite backup is in the cloud, can you actually retrieve a large dataset efficiently and within your RTO? Test it.

Remember that e-commerce firm I mentioned? After we fixed their tiered storage, we ran a recovery drill. They discovered their ‘automated’ cloud backup hadn’t actually been syncing correctly for two weeks due to a minor authentication error. Imagine if a real disaster had hit! That drill, which felt like a chore at the time, probably saved their entire business. Testing isn’t a cost; it’s an investment in resilience. It confirms your digital safety net is actually there and, crucially, that it works.

5. Optimize Data Storage for Performance: Speed is the Name of the Game

In our hyper-connected world, slow data retrieval isn’t just an inconvenience; it’s a productivity killer, a revenue drain, and a frustrating experience for users and customers alike. Imagine your sales team waiting minutes for a customer’s history to load, or your analytics platform taking hours instead of minutes to process a query. The costs quickly mount, both in terms of lost time and missed opportunities. Optimizing data storage for performance is about ensuring your data moves as swiftly as your business demands.

Unleashing Speed: Tactics for Agile Data Access

There are several powerful strategies you can employ to supercharge your data access speeds:

  • Caching Mechanisms: This is often the first line of defense against slow data. By storing frequently accessed data in faster, temporary storage locations closer to the processing units, you dramatically reduce retrieval times. This can involve:
    • In-memory caching: Storing data directly in RAM for ultra-fast access, ideal for very hot data.
    • SSD caching: Using SSDs as a cache layer for traditional HDDs. The system intelligently moves frequently accessed blocks of data to the faster SSDs, accelerating read performance without the full cost of an all-SSD array.
    • Content Delivery Networks (CDNs): For web-facing assets, CDNs cache content at edge locations geographically closer to your users, drastically reducing latency and improving website load times.
  • Database Indexing and Query Optimization: Poorly written database queries or missing indexes are notorious performance bottlenecks.
    • Indexing: Just like a book’s index, database indexes allow the system to quickly locate data without scanning every single row. Properly designed indexes can transform query times from minutes to milliseconds.
    • Query Optimization: Regularly review and refactor slow queries. Database administrators should profile queries to identify inefficient operations and optimize joins, subqueries, and filter conditions. Sometimes, a slight tweak in a query’s structure can yield massive performance gains.
  • Data Compression and Deduplication: These techniques not only save storage space but can also indirectly boost performance, especially over networks.
    • Compression: Reduces the size of data, meaning less data needs to be read from storage and transferred across the network. This speeds up I/O operations and reduces bandwidth consumption.
    • Deduplication: Identifies and eliminates redundant copies of data blocks, storing only a single instance. Like compression, this reduces the physical storage footprint, which can translate to faster backup windows and more efficient use of high-performance storage.
  • Network Infrastructure: Don’t overlook the plumbing! Even the fastest storage can be bottlenecked by a sluggish network. Ensure you have adequate bandwidth, low-latency connections, and reliable network hardware between your users, applications, and storage systems. Upgrading to 10 Gigabit Ethernet (10GbE) or even higher speeds, where appropriate, can make a huge difference.

Proactive Monitoring: Your System’s Early Warning

Performance optimization isn’t a ‘set it and forget it’ task. It requires continuous vigilance. Regularly monitoring key performance metrics is absolutely essential to identify and address bottlenecks before they impact users. What should you be looking at?

  • IOPS (Input/Output Operations Per Second): How many read/write operations your storage system can handle per second. High IOPS are crucial for transactional databases.
  • Throughput (Bandwidth): The amount of data transferred per second, typically measured in MB/s or GB/s. Important for applications dealing with large files, like video editing or big data analytics.
  • Latency: The delay between a request for data and the beginning of its retrieval. Lower latency means faster response times.
  • CPU and Memory Utilization: High usage here can indicate a need for more processing power or RAM, especially if it’s impacting storage performance.

Tools exist that provide real-time dashboards and alerts for these metrics. They can help you spot trends, predict potential issues, and pinpoint the exact source of a slowdown. For instance, a sudden spike in disk queue depth might indicate an I/O bottleneck, prompting you to investigate whether a new application is consuming too many resources or if a hardware component is failing. Proactive monitoring helps you stay ahead of the curve, ensuring your storage infrastructure remains a high-performance engine rather than a frustrating drag.

6. Plan for Scalability and Future Growth: Building for Tomorrow, Today

In the dynamic digital landscape, data volumes don’t just grow; they explode. Failing to plan for this inevitable expansion is akin to building a house without considering that your family might grow. You’ll quickly run out of space and face costly, disruptive renovations. Designing storage solutions with inherent scalability is paramount, ensuring your infrastructure can gracefully accommodate increasing data volumes and evolving computational demands without compromising performance or your budget. It’s about future-proofing your investment.

Building for Tomorrow, Today

Think about scaling your storage as either expanding outwards or expanding upwards:

  • Horizontal Scaling (Scale-Out): This involves adding more independent storage nodes or servers to your existing infrastructure. Each new node adds capacity and often performance, and the system works together as a unified whole. Cloud storage, object storage systems, and distributed file systems are excellent examples of horizontal scaling. It’s often more resilient, as the failure of one node doesn’t bring down the entire system. It allows for highly flexible expansion as your data needs evolve, adding capacity without major architectural overhauls.
  • Vertical Scaling (Scale-Up): This involves upgrading existing storage devices with more powerful components – adding more disks, faster processors, or more RAM to a single storage array. While it can provide immediate performance boosts, it has practical limits. Eventually, you’ll hit the maximum capacity or processing power of a single device, and then you’re back to needing a new, larger system, which can be expensive and disruptive.

The trend is definitely towards horizontal scaling, especially with the prevalence of cloud technologies. It offers unparalleled flexibility.

Storage Virtualization: This technology decouples the physical storage hardware from the software that manages it. It creates a pool of storage resources that can be provisioned and managed centrally, regardless of the underlying hardware. This provides immense flexibility, making it easier to add new storage, migrate data, and manage different types of storage from a single interface. It really simplifies capacity planning and resource allocation, allowing you to react quickly to changing needs.

Of course, planning for future growth also means anticipating the types of data you’ll be storing. Are you expecting an explosion of unstructured data from IoT devices, high-resolution media files, or massive datasets for AI/Machine Learning initiatives? These all have different storage characteristics and performance demands. A static, rigid storage solution won’t cut it.

Cloud-Native Thinking and Strategic Partnerships

The cloud has, undeniably, revolutionized scalability. Cloud providers offer elastic storage services that can scale almost infinitely, allowing you to pay only for the capacity and performance you consume. This eliminates the upfront capital expenditure of buying hardware and the headache of capacity planning for physical infrastructure. It’s a hugely attractive proposition for many organizations, offering unparalleled agility. You can spin up terabytes of storage in minutes, then scale it down just as easily.

However, it’s not a silver bullet. You must carefully consider potential vendor lock-in. While convenient, relying too heavily on one cloud provider’s proprietary services can make it difficult and costly to switch later. A hybrid or multi-cloud strategy can mitigate this risk, giving you flexibility and bargaining power.

And don’t forget the importance of strategic vendor partnerships. Choose storage providers that offer flexible licensing models, clear upgrade paths, and a track record of innovation. Engage in regular discussions with them about your projected growth and explore how their solutions align with your long-term vision. A good vendor relationship can transform a complex scaling challenge into a manageable, well-supported evolution of your storage infrastructure. It’s truly a collaborative effort, not just a purchase. When you’re planning, think five years ahead, not just five months, because the data won’t stop coming, that’s for sure.

7. Educate and Train Your Team: Your People, Your Strongest Firewall

We can invest in the most cutting-edge hardware, implement bulletproof security software, and craft the most intricate governance policies, but if your team isn’t on board, if they’re not educated, it’s all for naught. A well-informed, security-conscious team is, without a doubt, your first and often strongest line of defense against data breaches, accidental data loss, and operational inefficiencies. Human error, after all, remains one of the leading causes of data incidents. So, truly, your people are your strongest firewall.

Your People, Your Strongest Firewall

Think about it: who interacts with your data daily? Who creates it, modifies it, shares it, and stores it? Your employees. Therefore, empowering them with the knowledge and best practices for data management isn’t just an HR initiative; it’s a critical component of your overall data strategy.

What should this training cover? It needs to be comprehensive and relevant:

  • Security Awareness: This is foundational. Teach them about phishing attempts, social engineering tactics, strong password practices (and why multi-factor authentication is non-negotiable), and the dangers of clicking suspicious links or opening unsolicited attachments. Illustrate with real-world examples; a compelling anecdote about a local company that got hit often resonates more than abstract policies.
  • Compliance Requirements: Help them understand why certain data needs to be handled in specific ways. Explain the basics of GDPR, HIPAA, or whatever regulations apply to your industry. When people understand the ‘why’ behind the rules, they’re much more likely to follow them meticulously. It’s not just about ticking boxes; it’s about protecting sensitive information.
  • Proper Data Handling: This includes everything from data classification (e.g., ‘confidential,’ ‘internal only,’ ‘public’) to secure sharing protocols. When is it okay to email a spreadsheet, and when should a secure file transfer service be used? How should sensitive documents be stored on shared drives? These seemingly small details prevent huge headaches down the line.
  • Data Retention Policies: Employees need to know what data to keep, for how long, and when it’s appropriate to delete it. This prevents unnecessary data sprawl and ensures compliance with retention mandates.
  • Incident Reporting: What do they do if they suspect a security incident or accidentally mishandle data? A clear, easy-to-follow process for reporting issues without fear of reprisal is crucial. You want them to report, not to hide, potential problems.

Cultivating a Data-Aware Culture

This isn’t a one-and-done training session. Data management education needs to be an ongoing process.

  • Regular Refreshers: Conduct annual or semi-annual training sessions. Cyber threats evolve, and so should your team’s knowledge.
  • Varied Formats: Don’t just lecture! Use interactive modules, quizzes, simulated phishing exercises, and real-life case studies. Make it engaging, even a little fun sometimes. People learn better when they’re actively participating.
  • Leadership Buy-in: Senior leadership must champion data management best practices. When leaders prioritize security and data integrity, it sets the tone for the entire organization.
  • Open Communication: Foster an environment where employees feel comfortable asking questions about data handling and security. Establish clear channels for support.

I remember one company where employees were constantly saving sensitive customer data to their personal cloud storage accounts, thinking they were being efficient. They had no malicious intent, simply a lack of awareness about company policy and the security implications. Once we implemented regular, engaging training sessions that clearly explained the risks and provided secure, company-approved alternatives, that behavior stopped almost immediately. It showed me just how powerful education truly is. It fosters a culture of responsibility and vigilance, turning every employee into a conscious guardian of your organization’s digital assets. It’s perhaps the most human-centric and impactful investment you can make in data management.

Conclusion: Your Data, Your Strategic Compass

In essence, truly effective data storage management transcends mere technical implementation. It’s a holistic, strategic endeavor that integrates technology, policy, and people. By embracing a multi-tiered approach, prioritizing robust security and compliance, establishing clear governance, automating essential processes, relentlessly optimizing for performance, planning for dynamic growth, and crucially, educating your entire team, organizations can transform their data storage from a mere repository into a dynamic, strategic asset.

This isn’t just about preventing problems; it’s about unlocking potential. Your data, when managed intelligently, becomes a powerful compass, guiding efficiency, sparking innovation, and propelling your business forward in an increasingly competitive world. So, what are you waiting for? Start building those robust foundations today, your future self (and your shareholders!) will definitely thank you for it.

References

  • Gartner Research. (2015). Save Millions in Storage Costs With These Effective Data Management Best Practices. (gartner.com)
  • Enterprise Storage Forum. (n.d.). Data Storage Management | 7 Best Practices. (enterprisestorageforum.com)
  • Tableau. (n.d.). 7 Best Practices for Successful Data Management. (tableau.com)
  • UC San Diego Library. (n.d.). Best Practices for Data Management. (lisn.ucsd.edu)
  • TRG Datacenters. (n.d.). Best Practices for Data Center Storage Management. (trgdatacenters.com)