A goldmine with no pickaxes – that’s how one can describe how much data is available to enterprises with an inability to extract relevant information and value from it. The churn rate of information continues to grow for organisations across the world, but it remains unused in storage systems.
IDC’s research shows that global data quantities will grow up to 175 zettabytes, with other sources even pushing that number up to 180 zettabytes. However, only a small fraction of organisational data is analysed or used to leverage strategic decisions.
Holding this power and being unable to wield it in the right way makes it useless, leading to a basic misunderstanding about how valuable data is to modern business. Most global businesses, in fact, treat data storage as an offhand compliance requirement or a cost centre that is managed rather than cultivating it.
When your organisation truly understands not just the value of data itself but how it is stored and managed across its entire lifecycle, you can truly transform your business.
The Cost of Treating Data as Storage Alone
Approaching data management with single-minded focus on data storage only leads to tunnel vision. Organisations that follow this approach cause a domino effect of issues leading to unforeseen expenses, starting with storage costs. Over time, enterprises can end up lodged in an endless web of purchasing more storage capacity without any increase in business value to match. Such enterprises are heading towards over-provisioned, underused, and fragmented business models that are split across systems and vendors.
Hidden Data
Business leaders that do not consider data management with a 360-degree approach find themselves neck-deep in issues related to data location, accessing, and trust. Time-bound and vital information gets hidden under mountains of data where it finally becomes obsolete. The designated teams end up wasting endless time looking for datasets, recreating analyses that were already completed, or working with archaic information that leads to incorrect decision-making.
Compliance Concerns
The biggest, most expensive issue that comes with treating data as a simple storage related problem – compliance. Regulations that are in place across countries, like India’s Digital Personal Data Protection Act (DPDPA) and Europe’s General Data Protection Regulation (GDPR) need organisations to follow the mandated data retention periods, deletion timelines, and audit capacities. Any company that has focused on a storage-first approach will fail to accurately locate and identify personal data, understand their timelines, or follow compliance with data subject requests.
Financial Pitfalls
Fines are levied not just for data breaches but being unable to follow proper data governance. Major retailers and businesses across the world have been penalised for not being able to prove that they properly store and dispose of personal information according to regional regulations. Following a basic storage-centric approach creates unnecessary nightmares where personal data exists indefinitely without accurate categorisation and lifecycle controls.
Strategizing Data
Nobody likes to be thought of as an obligation, ILMs included. However, when ILMs are treated as strategic enablers, it gives businesses an edge over competition. Doing this changes the gear on decision making, data curation, and risk mitigation. The time required to access and analyse relevant information drops dramatically, freeing up more time for your data analysts to spend on better research than finding and cleaning data.
NetApp is one of the companies that offer you modernisation for data management that brings instant access to old datasets and real-time comparative analysis. ILMS allow you to change your unused data into advantageous assets. One such example is how banks across the world are using their archived transaction information to train machine learning technology and develop sophisticated fraud detection algorithms.
Data, therefore, isn’t just storage burden – it is a treasure trove of actionable insights waiting to be processed and employed accurately across the whole lifecycle. When used in this manner, data becomes the base for AI systems to spot fraud patterns in milliseconds, directly resulting in lowered losses and increased customer trust.
OpenText leads the way in showing how proper data curation throughout the lifecycle can compound the value over time. The enterprise IMS OpenText brings allows your organisation to automate the process of classification, enrichment, and preservation of data from the journey of creation to the final step of deletion. It allows historical data to remain accessible and relevant even years after creation: this aids regulatory investigation sand advanced analytics.
Your enterprise can go well beyond achieving operational efficiency – you can respond to market opportunities and regulatory requests with unmatched speed and accuracy. It is easier to flip your entire business strategy when you have the ability to access and process historical data analysis.
Crucial Shifts for Enterprises to Make
Changing the way you approach the data lifecycle management process needs you to revisualize your entire approach across three dimensions. This is not just in reference to technical changes but cultural and operational changes that need to be followed across the enterprise.
Centralising ILM:
Give up the data silo system and shift to a more controlled approach with a unified approach and access for analytics and compliance needs. Traditional systems evolved organically and created isolated data storage repositories that were managed by multiple teams and departments. These incompatible siloed systems and frameworks make it impossible to understand data relationships, follow consistent retention policies, or provide unified access.
The step to centralise ILM doesn’t need consolidation of all data into one giant repository – it requires the implementation of a combined governance framework, standardized metadata schemas, and a coordinated lifecycle policy that works across even distributed systems.
Intelligent data fabric architectures give you centralized management capabilities while holding on to the flexibility of distributed storage optimized for different workload requirements.
Improving Retrieval:
Use metadata and classification to make your retrieval and governance process smarter, meaning you no longer look at it as an afterthought. You go beyond simply capturing basic information like the file size, creation date, and storage location.
Rich, contextual metadata gives you the description of the data, its significance to your business, regulatory needs, and predictable usage patterns. It allows automated policy enforcement where needed, smart archival decisions, and quick discovery of the required information.
Advanced classification doesn’t stop at tagging, it incorporates ML to automatically identify personal data, assess the critical nature of it, and predict future access patterns. This allows your organisation to automate the migration process of frequently accessed data to high-performance storage and shift out dormant data into cost-effective archival systems, all while maintaining accessibility.
Finetuning Retention and Disposal:
Scale up with smarter retention and disposal approaches. Manual ILM processes can no longer handle that level of scale with the data volumes and regulatory needs that exist today. You need the automation that intelligent ILM services offer, bringing you:
• New data classification – based on the content type, source, and context
• Retention policy application – depending on regulatory needs and value
• Data migration between storage tiers – based on access patterns and costs
• Audit trail and compliance report generation – without human intervention
• Secure disposal process execution – depending on the expiration of retention periods
• Data quality monitoring and anomaly flagging – indicating governance issues
Having these features doesn’t require extravagant investments. They form the essential foundation for operating in a data-intensive regulatory landscape. NetApp’s storage solutions go on to show that automation can significantly reduce overhead while also working on compliance accuracy and cutting down storage costs with intelligent tiering.
Opportunities for Indian Enterprises
India stands at the pinnacle of change where regulatory requirements and technological advancement are bringing new opportunities for true transformation. The DPDP act brought new light to compliance – it’s not just an obligation, but a catalyst for revolutionising data management practices to drive significant strategic advantages.
By following the DPDP compliance requirements, you can also find your organisation building data governance capabilities with strategic ILM practices. Your enterprise can follow all regulations and achieve maximum business value. DPDP works as the perfect method to invest in comprehensive data lifecycle management platforms.
The digital environment in India brings the advantage of modernising data lifecycle management without legacy constraints. Enterprises can follow a cloud-native ILM process with AI and ML based classification and automated policy enforcement from the get go.
Through iValue Group’s network, your organisation can access the tech giants like OpenText and NetApp. Their top-notch, enterprise-grade ILM solutions are changing how organisations approach data storage and processing from basic to layered and advanced, allowing them to jump maturity curves. Indian enterprises that work with international clients have to follow the specifications of GDPR, CCPA, and other sector-specific requirements. Handling these requirements with mature ILM capabilities ensure that you get enhanced data governance across your international presence, bringing revenue opportunities and lowering risks as well.
Aspect | Indian Enterprises | Mature Markets |
Legacy System Dependencies | Minimal; opportunity for modern tech adoption | High; legacy integration complexity |
Regulatory Drivers | DPDP as a strategic inflection point | Compliance as an established norm |
ILM Technology Adoption | Greenfield, cloud-native solutions with AI automation | Incremental modernization constrained by legacy |
Access to Enterprise ILM Tools | Increasing availability via global investments | Broad access but often legacy-bound |
Global Compliance Readiness | Growing multi-jurisdictional capability | Mature compliance ecosystems |
Competitive Differentiation | Leapfrogging with strategic ILM investments | Focused on optimization and sustainment |
