Authored by: Shriram Pore, Vice President – Engineering at MSys Technologies
By adopting best practices, organizations can maximize their operating efficiency and functional effectiveness while reducing costs associated with creating, managing, and optimizing storage infrastructure.
With the total data volumes set to reach 175 ZB by 2025, handling data efficiently has assumed strategic significance. Data is generated at breakneck speed today, and the unprecedented rate of digitalization is making it difficult for firms to manage vast amounts of information. Nonetheless, firms have realized the importance of efficient data handling and are willing to employ the best strategies to generate, store, and handle information on multiple fronts. Against this background, this article highlights the best practices that can help companies efficiently manage the data to further their business prospects.
Best Data Management Practices
a) Data Tiering: All data sets are not created equal, and their classification based on their importance and accessibility is the basis of the data tiering. The approach allows the strategic data to be stored in high-performance storage systems while less important/accessed information is handled through lower-cost mechanisms. By achieving this classification, organizations can reduce storage costs, optimize efficiency, and manage their data with desired excellence and efficiency. This storage solution is typically called DHSM – distributed hierarchical storage management, where faster tiers could be suitable from Cache, Persistent RAM/ NonVolatile RAM, Flash, SAS/SATA drives, cloud storage tier to archival/tape storage.
b) Capacity Forecasting and Planning: It is essential for organizations to proactively plan for future storage requirements to stay up to speed with segment and competition realities. To that end, firms must analyze historical data, current capacities, and emerging trends to predict future storage requirements accurately. This proactive planning, in turn, will help firms optimize resource allocations, reduce operational bottlenecks, and improve performance parameters besides minimizing the underutilization or overutilization of the firm’s data storage systems. New age solutions are via analytics where the data growth is tracked over a period compared to Low Water Mark(LWM) & High Water Mark(HWM) to notify promptly to grow the storage capacity, thus helping even predict ahead of time which CIOs can take as inputs. It also helps in budgeting storage expenses.
c) Deduplication and Compression: Both these techniques are proving crucially instrumental in enhancing the efficiency of data storage systems. Deduplication identifies identical data sets and erases the redundant ones to offer significant savings in the storage space. Deduplication can be inline or offline based on the performance parameters and also works at the file level, fixed block sizes, or variable block sizes, which brings significantly different storage utilization optimization levels. The compression technique, on the other hand, saves space by reducing the size of the data file without causing any harm to the information contained in the data sets. Both these techniques prove helpful in improving the efficiency of storage systems consumption and, thus, the overall costs associated with data storage and infrastructure.
d) Automation and Orchestration: Automating and synchronizing workflows and orchestration can bring significant advantages to data storage and management infrastructure. Automation reduces processing times, reduces human errors, and cuts costs significantly, bringing strategic and tactical benefits to the table. Orchestration further enhances operational efficiency by coordinating multiple automated operations so that storage systems enjoy improved synchronization across networks.
e) Lifecycle Management: An effective life cycle management of the data can help optimize the storage capacity by creating discrete records, deleting duplicate entries, and ensuring compliance with regulatory provisions. The process entails managing the data throughout its lifecycle, i.e., from its creation to its deletion, and includes creating data backup plans, replicating across data centers across geographies, devising recovery mechanisms, and managing data retention policies to ensure the availability and protection of data as per the norms and procedures.
Differentiators would be Content/Data Tagging and a storage management engine processing the data based on the tags – for all the above best practices and subsequent Tools and Technologies to be most effectively implemented, content/data tagging and a storage management engine is a novel way of achieving it. Content/Data tagging can be done at various levels in terms of the content type itself, varied sizes, and form factors. The storage management functions can be built into a containerized microservice-based architecture, driven by a storage management engine based on the tags, user needs, or even plans provided.
Efficient Storage Management: Tools and Technologies
1) Virtual Storage: By combining multiple physical storage units into a single system, storage virtualization helps firms build centralized and scalable storage solutions for the long term. The process also helps achieve efficient utilization of resources besides simplifying the routine management procedures such as data migration and provisioning to enhance operational efficiency, storage optimization, and quick access and sharing of data among key stakeholders throughout the business ecosystem.
2) Cloud Solutions: Flexibility, scalability, and efficient utilization of resources are vital benefits that encourage firms to migrate to cloud solutions. Cloud storage also helps organizations offload their on-premises storage requirements, thereby becoming instrumental in achieving significant cost savings while scaling infrastructure to accommodate the additional data storage demands. The leading names in the cloud storage industry that most firms are banking upon include Amazon, Google, and Microsoft.
3) Containerization: With the help of containerization technologies such as Docker and Kubernetes, organizations can create independent software that can be deployed in different environments with the desired speed and agility. These independent packages, termed containers, thus simplify the application deployment, synchronizing disparate modules and swiftly scaling operations in case an urgent expansion needs to accommodate extra data and information.
4) AI-driven Storage Management: The role of Artificial Intelligence (AI) in creating, managing, and optimizing the storage space is increasingly becoming prominent. AI algorithms enable organizations to forecast storage requirements accurately, analyze current capacities, and make data-based decisions to deliver optimized performance. Besides, AI can enhance systemic efficiency and operational readiness, which is particularly significant when handling large-scale projects.
Organizations must start devising data storage optimization strategies wherein the focus of the planning shifts from tackling data overload to the optimum utilization of the storage infrastructure. The tools discussed above can streamline this strategic shift, and by equipping organizations with capabilities to create, manage, and control data optimally, new-age storage technologies can play a decisive role in changing the fortunes of firms across the business verticals.