Data has long been recognised to be the most valuable asset held by any organisation and, with the arrival of accessible generative AI tools, the potential to exploit the information resource is enormous. 59% of CEOs cite AI as the technology that will have the biggest impact on their industry over the next three years. However, AI – and the development of specific AI use cases – is adding complexity to already challenging data management processes, especially for organisations with a mix of on premise and cloud systems.
From the initial data capture to consolidation, storage, security and accessibility, there are a myriad of issues to consider. Where is the data located and is it compliant with each local market regulation? Is data secure? What are the archiving and deletion policies? What is the data redundancy model to enable business resilience? Furthermore, with the extraordinary escalation in data volumes, especially the increase in unstructured data, the cost of storage – and the cost of deletion – need to be considered as does the implication on a business’ sustainability strategy.
Gold Rush versus Corporate Risk
Digitisation across both public and private sectors has transformed organisations’ perceptions of data value over the past decade. Yet while CEOs are keen to explore analytics and AI to drive value, improve efficiency and achieve competitive advantage, for those tasked with managing data resources the focus is on managing and reducing risk.
Most organisations are now generating enormous volumes of structured, semi-structured and unstructured data – but how much of that data is valuable? Is it clean? Does it need to be accessible – and for how long? Is it secure? All of these questions need to be addressed before an organisation can confidently embrace new analytics and generative AI tools.
With pressure ramping up from senior management entranced by opportunities to innovate, CIOs need to quickly achieve up to date data management strategies that minimise risk and cost while expanding information value.
Inside Track
One of the biggest issues facing companies of every size today is not only the volume but the diverse locations of data. In addition to on premise legacy systems, with a mix of private cloud and public cloud, including third party ERP and CRM applications, there is no single, or simple, data model.
While there are a number of issues to address, including storage, deletion, and data security, it is also vital to determine the value of data to the business. Data management costs – especially storage and deletion – can escalate and without a clear understanding of how and where the business will gain value from this insight, the cost to value equation can be lost. As such, there are a number of key areas to consider to improve the cost, efficiency and, therefore, value of data management.
Hidden Deletion Fees
Deletion strategies – how long is data held, especially under the ‘right to be forgotten’ within GDPR – are a key aspect of any data management strategy. In addition to determining whether tools can be used to automate this process or if manual management is required to ensure compliance, companies need to consider how to balance deletion models with the need to retain vital records.
With data typically archived on lower cost cloud storage platforms prior to deletion it is also vital to understand the cost models deployed for these platforms. Is the platform charging to upload data and download data? Is it charging to delete data? These costs can quickly escalate and need to be factored in to data management strategies for both deletion and redundancy.
Encryption Imperative
There is no longer any question about whether or not to encrypt data. Zero trust policies are now standard within any security posture and any data that leaves the business should be encrypted. Traditional barriers to encryption have been removed: given the number of Open Source technologies that support encryption, there is limited additional cost associated with this rigorous approach. Companies will have to factor in a small additional cost for the extra storage associated with the encryption, but given the overall data volumes, this is minimal.
There are also serious security risks associated with super cheap storage typically used for archiving or back-up. These platforms use Identify and Access Management (IAM) policies which can be confusing and have led to significant data loss in recent years when business have failed to implement policies correctly. When assessing any data storage platform, it is essential to look at more than cost.
Innovative Data Storage Reduction Models
One of the biggest concerns for organisations is the amount of data duplication associated with today’s business models. Cloud based third party CRM solutions, for example, are widely used, with organisations routinely uploading information already stored in a Google Drive. Not only does this model add to the storage burden but it demands complete trust in the vendor to safeguard the business’ data. The latest generation of tools is taking a more efficient approach: rather than the upload the entire file, a business can simply attach a link. The data never leaves the business, and the link can be redacted at any time. This makes the entire data management process simpler, less demanding of storage resource and, critically, more secure.
Conclusion
The rapid adoption of AI is encouraging companies to look again at data management strategies. Legacy technologies not only represent a heightened security risk but can fundamentally constrain a business’ ability to explore and exploit its valuable information resources. For example, AI simply cannot be run across legacy on premise systems. This refocus on data management is welcome: this is simply not an area that can be set in stone but one that requires continual assessment and reconsideration.
However far a company has progressed in its digital transformation journey, data management strategies need to be reviewed at least once a year, preferably more often. Evolving security needs to be assessed. Storage platform costs compared and innovative, often Open Source, solutions understood and considered. Data-led business opportunities are fast evolving and if companies are to truly maximise the value of increasing information resources, a rigorous and regularly reviewed data management strategy is a must.
