Why Indexing and Classification are Crucial for Corporate Data Hygiene

Effective data hygiene begins with proper indexing and classification. When data is accurately indexed, businesses gain a comprehensive understanding of each file—its creation date, author, size, and more. By adding classification, companies can easily determine what the data represents and how it should be handled in compliance with regulations and company policies.

The consequences of this are significant. Proper data management not only aids regulatory compliance and reduces costs but also accelerates data retrieval, boosts query efficiency, and lays the foundation for AI applications. With the global market for data classification projected to expand at 24% annually, reaching an estimated $9.5 billion by 2031, organisations are becoming increasingly aware of the value it provides.

This article highlights four critical business benefits that demonstrate the true impact of indexing and classification.

Ensuring Compliance with Regulations

Imagine a business that lacks proper data classification and indexing. Data is scattered across various locations—laptops, email inboxes, thumb drives, and servers—with no organised system in place. This is more common than one might think, with Forbes estimating that as many as 33% of organisations struggle with poor data management practices, and some experts suggest that up to 88% of data could be classified as “dark data.” In such a chaotic environment, adhering to regulations like GDPR, CCPA, and PDPB is nearly impossible.

Regulations require precise and detailed access to data, forcing businesses to choose between a slow manual approach or automating the process with third-party tools. This is where indexing software proves invaluable. It scans files, analyses their formats, extracts metadata, and categorises everything. Once classified, businesses can manage data more efficiently.

Proper categorisation makes regulatory compliance far more manageable. For instance, when a company receives a data subject request, it can locate the required data without delay, avoiding fines due to missed deadlines or failure to retrieve data. Files containing personal data that are no longer needed can be quickly identified and securely deleted. In case of a ransomware attack, businesses can immediately pinpoint which files have been affected and take swift action. Such proactive measures are critical for compliance with regulations like DORA, which demand timely reporting on compromised data.

Reducing Costs Through Smarter Storage Solutions

Data indexing plays a pivotal role in optimising storage strategies. By categorising and organising data, businesses can ensure that only frequently accessed (hot) data remains on high-performance storage platforms. This allows for more effective tiering, directing data to the most suitable storage or cloud solution based on its usage.

For instance, frequently accessed data can be placed on high-speed, low-latency storage systems, while older or less critical data can be moved to more cost-effective, high-capacity storage or even deleted. This approach not only reduces storage costs but also improves system performance by preventing primary storage from being overloaded.

Moreover, effective data indexing and classification allow businesses to implement data lifecycle management policies that help avoid unnecessary expansion of storage infrastructure. By identifying data that no longer serves a purpose, companies can prevent costly and disruptive upgrades to primary storage platforms.

According to a Forrester Total Economic Impact study, one leading data indexing and classification provider helped clients reduce backup and data costs by an average of 66%. These savings stem from a combination of factors, including reduced data duplication and lower storage costs. 

As cost optimisation becomes a primary focus, it is now regarded as a more immediate priority for IT leaders than preparing data for AI, a shift that reflects the growing recognition that efficient data management not only supports AI but also reduces operational costs.

Supporting Sustainability Objectives

A significant gap often exists between a company’s sustainability goals and the actual steps taken to achieve them. This gap is often caused by overlooking opportunities for decarbonisation. The Digital Carbon Footprint Toolkit from Loughborough University, for instance, provides an overview of the potential carbon emissions from data, including the emissions associated with dark data.

Many businesses tend to store everything by default—outdated records, unnecessary files, and even non-compliant data. This lack of governance results in excessive storage, with organisations often keeping records for arbitrary time periods—whether seven years, ten years, or indefinitely. This issue is a primary reason why cloud providers store massive amounts of data: customers fail to manage their data effectively.

Rising energy and storage costs are compelling businesses to take action, but without effective classification and indexing, it’s difficult to determine what can be safely deleted. Legal teams often hesitate to approve data removal without knowing exactly what it is.

Sustainability officers, who typically don’t work in IT, often focus on more visible actions like turning off lights or installing electric vehicle charging stations. True sustainability impact comes from reducing unnecessary storage and computational resources. By implementing better data management practices, companies could remove vast amounts of unnecessary data and physical infrastructure. This could lead to the decommissioning of entire data centres, reducing energy consumption, cooling requirements, and associated carbon emissions—a significant step toward meeting sustainability objectives.

Enabling AI-driven Insights

According to research from Komprise, a key challenge in preparing data for AI is managing governance and security (45%), followed by data classification and tagging (41%). As businesses realise, AI is only as effective as the data that underpins it.

When businesses have robust indexing and classification frameworks, leveraging generative AI applications becomes much easier. AI tools designed to help businesses query their data through natural language processing can only function effectively when the data is properly classified. Without this, businesses must sift through an overwhelming number of files to retrieve meaningful insights.

Leading data classification services provide retrieval-augmented generation (RAG), which pulls information directly from a company’s classified data instead of relying on generic information from the internet. When businesses need to verify compliance with specific regulations, RAG provides precise, source-based insights, explaining where the data originated, how it’s classified, and how it aligns with regulatory standards.

Unlike typical AI tools like ChatGPT, Alexa, or Siri, which don’t provide immediate transparency regarding their data sources, leading classification and indexing systems must ensure that AI-driven insights are trustworthy and compliant. This transparency is crucial for maintaining data security and regulatory adherence.

Organising Data for the Future

Organisations are increasingly recognising the importance of data indexing and classification, primarily due to the pressure created by regulatory compliance. GDPR was the initial catalyst, but businesses now face additional regulations such as the EU AI Act. Customers have the right to be forgotten, but how can companies ensure this if they lack visibility into where their data resides? Furthermore, how can businesses determine if a retention policy allows them to legally keep data beyond the scope of GDPR?

Companies are starting to realise that the advantages of proper data classification extend far beyond compliance. It’s not just about reducing duplicates or cutting costs; it’s about preparing for future AI insights, improving security, contributing to sustainability, and optimising overall data management. Organisations that embrace this now will not only stay ahead of regulatory requirements—they will gain a competitive edge in the market.