Today, Machine Learning (ML) and Artificial Intelligence (AI) tools are continually analyzing data to derive insights that drive business decisions. Data is a part of almost every decision. That said, the efficacy of this data analysis depends on the quality of data being fed into the systems.
A survey found that while 91% of data professionals polled were actively building AI applications, only 1 in every 3, trusted the data being used.
Unsurprisingly, the focus has shifted from data collection to data integrity and data quality. Over the years, data has been steadily growing in volume and complexity. Hence, the way we handle data has to change. Let’s take a look at the key 2025 data quality trends defining how businesses with manage their data.
Multi-cloud data architecture
A majority of data being handled today is stored on the cloud. In a bid to optimize costs and mitigate the risk of downtime, businesses are now evolving to a multi-cloud network architecture.
Simply put, this involves using multiple cloud computing platforms to store and manage data. A survey found that 89% of companies follow this approach. This includes public and private clouds.
Distributing data across multiple platforms in this way helps avoid vendor lock-ins. It also improves flexibility and resilience. That said, it makes interoperability and standardization of data fields a critical requirement for data quality management. Data owners will also need to carefully plan and coordinate security measures across the different platforms.
Scalability as a focal point
As the amount of data being handled increases, so does the risk of data quality issues. Data coming in from different sources can complicate quality management and give rise to inconsistencies. Then there are issues like data duplication, incorrectly configured systems that lead to data corruption, incomplete migration, and so on. This not only affects data analysis but also puts organizations at risk of expensive data breaches. In 2024, the average cost of a data breach across the globe was $4.88million.
To tackle this, 2025 data quality trends point towards prioritizing scalable data quality measures. Automated data quality tools can help. They make it easier to discover, profile, catalogue data and apply sophisticated business rules to improve overall data quality. In turn, potential data quality issues become easier to spot and address.
Increased demand for real-time analytics
A study found that businesses operating in real-time saw a 62% higher revenue growth as compared to slower competitors. Their profit margins also grew by 97%. Reliable data is the foundation for real-time operation. Hence, businesses must be able to detect and address data quality issues as and when they arise.
There has been a noticeable shift from traditional batch data processing to real-time data processing. This is expected to continue as the demand for real-time analytics increases. Adding fuel is the rise of edge computing and IoT devices that make data more accessible.
Of all the 2025 data quality trends, this is particularly relevant for financial service providers, logistics companies, retail and other such dynamic sectors. In addition to systems that support real-time data processing, implementing event-driven architectures can help these businesses navigate unpredictable market changes and make the most of real-time analytics.
Growing market for data monetization
Data is no longer just a tool to help businesses grow. For many businesses, data has become a product in itself. No-code and low-code solutions make data accessible to a wider audience and reduce the non-technical team’s dependence on IT departments. In turn, this encourages agility and allows business units to make faster decisions and independently develop data solutions.
It also opens up new revenue sources. The market for data monetization is expected to reach $15.5 billion by 2030. That is an annual growth of 20%. 2025 will see more frequent instances of the sale of raw data as well as subscription-based data products that add value. The future may see data marketplaces emerge as popular venues for monetization.
Ethical AI
There’s no denying the presence of AI. According to a study, AI’s contribution to the economy could cross $15.7 trillion by 2030. When it comes to data integrity, AI can be automated to detect anomalies and improve customer engagement with personalized offers. Done right, AI-driven personalization can play a big role in revenue growth through this route.
That said, as the use of AI increases, the need to address the ethical principles behind these models also becomes stronger. AI models need to be free from bias. Hence, through 2025, businesses will need to pay more attention to the quality of data being fed into these systems and integrate checks to make processing transparent.
Stronger data governance frameworks
As the demand for personalized service increases so does the amount of data businesses gather. As a result, data governance is no longer considered optional. Today, it is a mainstream necessity.
A good data governance program gives organizations a framework to ensure proper data handling. It creates a shared language as the foundation for effective collaboration. Organizations with a planned data governance program have seen improvements not only in data integrity itself but also in the quality of data insights and analytics.
It also protects businesses from fines for violation of privacy regulations. In 2023, businesses in the EU paid a total of 2.1 billion in fines alone. As a result, the year ahead may see businesses strengthening data governance frameworks and adopting privacy by design policies.
Summing it up
Today, data management is all about staying ahead of the curve. Keeping track of 2025 data quality trends is instrumental to staying competitive in 2025’s data-driven landscape. Whether it’s ensuring your current data quality system can match the scale of your company’s growth or ensuring real-time processing, being proactive is the need of the hour.
Choosing the right data quality tools lays the foundation for this. Embrace the trends that you see adding value to your organization and take deliberate steps to incorporate them. Remember, every small change can have a big impact.
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