Effective data hygiene hinges on robust indexing and classification.
When data is accurately indexed, businesses gain comprehensive insights into a file—its creation date, author, size, and more. Incorporating classification further clarifies the nature of the data and dictates its management according to regulatory and corporate policies.
The Impact of Proper Data Management
The benefits of proper data management are substantial, ranging from regulatory compliance to cost savings. Efficient data management accelerates retrieval, enhances query performance, and sets the stage for AI integration. With the global data classification market projected to grow at an annual rate of 24% from 2024 to 2031, reaching a valuation of $9.5 billion, businesses are beginning to recognise its importance.
In this article, we will delve into four key business advantages that highlight the significance of indexing and classification.
Ensuring Regulatory Compliance
Consider a business with poor data classification and indexing. Data is scattered across laptops, inboxes, and servers without proper governance. This scenario is more common than you might think, with Forbes estimating that up to 33% of organisations suffer from poor data management practices. In extreme cases, “dark data”—data that is not responsibly managed—could account for as much as 88%. Under these conditions, compliance with regulations like GDPR, CCPA, and PDPB is unattainable.
Regulations require precise and detailed data retrieval. Businesses have two choices: a slow manual approach to data governance or an automated process using third-party tools. Indexing software plays a crucial role in the automated approach, scanning files, extracting metadata, and categorising data efficiently. When combined with relevant record classification, this creates a powerful intelligence source about the data.
Categorised files simplify regulatory compliance. Data subject requests can be addressed promptly, avoiding fines for non-compliance. Personal protected information that exceeds legal retention limits can be easily identified and deleted. In the event of a ransomware attack, businesses can quickly identify and report affected data, meeting regulatory requirements such as those outlined in DORA.
Cutting Costs with Smarter Storage
Data indexing is essential for creating efficient storage solutions. By organising and classifying data, businesses can ensure that only relevant and frequently accessed data is stored on primary storage platforms. This enables better tiering, where data is allocated to the most suitable storage solution based on usage patterns and importance.
For instance, frequently accessed data can be stored on high-performance systems, while less critical data can be moved to cost-effective storage solutions or deleted. This tiered approach optimises storage costs and enhances system performance by preventing primary storage platforms from becoming overwhelmed.
Data indexing and classification also support cost-effective data lifecycle management policies. By identifying and archiving unnecessary data, companies can avoid expanding storage infrastructure. This proactive approach helps prevent costly and disruptive upgrades to primary storage platforms. A Forrester Total Economic Impact study found that businesses who work with a leading data indexing and classification provider can reduce backup and data costs by 66% on average. These savings result from reduced data duplication and lower storage costs. In 2024, cost optimisation surpassed AI preparation as the top data storage priority for IT leaders, highlighting the financial benefits of good data management, and it’s a trend that’s likely to continue this year.
Advancing Sustainability Goals
There is often a disconnect between sustainability targets and the actions taken to achieve them. Loughborough University’s Digital Carbon Footprint Toolkit, for example, shows the worst-case scenario of carbon emissions from data, including dark data.
Some companies store unnecessary, outdated, and non-compliant records by default. This leads to massive amounts of stored data, not because it is needed, but due to poor data management practices.
Rising energy and storage costs drive companies to cut back, but without classification and indexing, they cannot determine what data is safe to delete. This means legal teams are hesitant to approve data removal without knowing its contents.
Sustainability officers typically focus on reducing energy consumption through measures like turning off lights, installing electric charge points, or putting monitors in sleep mode. However, significant impact comes from reducing unnecessary storage and compute resources.
Proper data management can lead to the removal of petabytes of unnecessary data, resulting in fewer storage arrays, servers, and lower power and cooling requirements. This can lead to shutting down entire computer rooms, floors of data centres, or even decommissioning entire facilities.
Unlocking AI-Driven Insights
Preparing data for AI presents challenges, with Komprise’s research showing governance and security concerns (45%) and data classification and tagging (41%) being the most significant. Businesses are quickly realising that AI’s effectiveness depends on a solid data foundation.
A robust data engineering framework with clear indexing and classification makes it easier to use generative AI applications for querying data using natural language processing. Without proper data management, businesses lack the foundation for AI insights and must manually sift through files to find relevant information.
Leading data classification services leverage retrieval-augmented generation (RAG), a bespoke question-answering system that uses classified data rather than random internet information. This provides source-based insights, showing where data came from, why it is classified a certain way, and how it aligns with regulatory requirements.
Most AI tools lack this level of transparency. When using tools like ChatGPT, Alexa, or Siri, the source of information is not immediately clear. Enterprise classification and indexing businesses, however, must verify their AI-driven insights because compliance relies on transparency on classified and indexed data.
Conclusion
Businesses are beginning to understand the importance of data classification and indexing, driven primarily by regulatory requirements. GDPR was the initial push, but now there are additional regulations like the EU AI Act to consider. Every customer has the right to be forgotten, but businesses must know where their data is to comply. They also need to understand if record retention policies override GDPR requirements.
The benefits of data classification and indexing extend beyond compliance. They support enhanced AI-driven insights, improved cost savings, sustainability, and smarter data management. Companies that embrace these practices now will not only meet compliance requirements but also gain a competitive edge.
About the Author
Mark Molyneux is EMEA CTO at Cohesity. A modern platform for the AI era. Our mission at Cohesity is simple: to protect, secure, and provide insights into the world’s data. The largest organizations around the globe rely on us to strengthen their business resilience. With the Cohesity Data Cloud, we are able to deliver on that mission. Our customers can recover from cyber events faster, manage and secure their data at enterprise scale, and gain valuable insights with our industry-leading AI capabilities.
