Missed insights, security gaps, rising costs: The heavy toll of poor data management and how to fix it

IMAGINE a storeroom where everyone keeps piling in items without a second thought. This is what the digital repositories of some companies are starting to resemble – messy, disorganised and overwhelming.

The consequence? Storage costs creep up, security lapses happen and valuable insights go unnoticed.

With the accelerating wave of digitalisation – and now artificial intelligence (AI) – businesses are generating more data than ever, but many are struggling to keep that data in check.

Another reason for the data explosion is the increasingly accessible and affordable storage options over the years, whether they are cloud services or on-premise hardware.

This means many organisations have not thought through or implemented a successful strategy to leverage their previous data trove, says Craig Bates, Asia-Pacific’s senior vice-president of Splunk.

More than 70 per cent of organisations worldwide, across 16 countries including Singapore, have over 1PB – or 1,000TB – of data, he adds. As such, they will soon encounter new issues – from hidden security gaps to poor-quality data that undermines their AI ambitions.

According to Splunk’s New Rules of Data Management 2025 report, over 70 per cent of global IT, engineering and cyber security professionals said poor data handling practices have led to bad decisions. And three in four cited growing volumes as the biggest contributor to rising data costs.

Traditionally, companies have tried to solve this by moving all their data into a central platform to make it easier to analyse, states Bates. This is time-consuming, and it costs money if you are pulling out of a cloud provider.

“It does not make sense to shift data around,” says Bates. “At today’s huge data volumes, you need to reach the data where it is.”

The new rules of data management

To keep up with ballooning data volumes – and extract real value from them – organisations need to move away from outdated data management frameworks, says Bates. That means focusing on three new rules:

1. Data quality

Poor data quality – when information is incomplete, outdated or difficult to read – can slow down incident response, or worse, miss threats altogether.

According to Splunk, 73 per cent of organisations that make data quality a priority have seen faster response times, and more than half say they are better at neutralising threats.

2. Data reuse

Instead of duplicating data or moving it across systems, teams should securely access the same datasets where they already reside. This reduces unnecessary transfers, cuts down clutter and enables faster collaboration.

A shared-access model also breaks down silos – for instance, both security and application teams can analyse the same log files for different needs.

Organisations that adopt this approach report fewer breaches, faster incident response and fewer challenges handling high data volumes, says Splunk.

3. Data tiering

Tiering data involves organising it based on how often and how urgently they are needed. Splunk reports that half of the organisations that have implemented data tiering say it has helped cut storage expenses.

They also gain faster access to frequently used data, stronger protection for older data types, and fewer issues around access speed, migration and cost management.

When applied together, these principles can enhance security, strengthen system visibility and reduce storage overheads – while helping firms stay compliant and responsive. Across Asia-Pacific, organisations are already seeing results.

Singapore Airlines (SIA), for example, tapped its high-quality, live data to support multiple business needs.

Using Splunk as its central analytics platform, SIA aggregates logs from check-in systems, mobile apps and crew platforms to maintain uptime and quickly troubleshoot issues – especially during peak travel or major IT rollouts.

Beyond operations, SIA leverages Splunk’s dashboard to track how customers interact with its digital services. For instance, identifying the most-used features across its app and website to help the team prioritise improvements that enhance travellers’ experience with the airline.

Even non-technical staff can build dashboards and monitor trends, enabling faster decisions and a smoother travel experience across touchpoints.

In Indonesia, digital payments platform DANA turned to Splunk to improve visibility and make better use of its data.

By unifying infrastructure and application data into a single, real-time view, DANA enhanced data quality and enabled cross-team access – helping teams respond to issues faster and make smarter decisions.

With end-to-end visibility across its systems, the company has also cut downtime, and is better positioned to adapt quickly to digital trends and customer needs.

How do you deal with messy data?

Messy data, notes Bates, can jeopardise a company’s pace of innovation. Scaling AI and automation is only beneficial if the underlying data is of high quality and accessible.

To get started, he recommends that chief information officers in the region take these steps:

• Map and audit data sources: Understand where your data resides, what systems it touches, and which sources are most critical to security and performance. “We always find data in places where customers never thought of,” says Bates.
• Assess data maturity: Evaluate how far along your organisation is in areas like governance, automation and tool integration. This helps identify what is needed for a more proactive, AI-ready strategy.

As a valued partner, Splunk works with customers to create a roadmap to adopt the new data management strategy – strengthening security, improving system visibility and setting the stage for effective AI use.

“Oftentimes, we are able to find opportunities to reduce the amount of data that customers bring onto our platform, and to repurpose that, and treat it in different ways, so that they are able to address business metrics, achieve consistency and drive greater business value,” says Bates.

Download Splunk’s 2025 data management report for more insights.