Data Quality in 2025 | Pillars of Data Quality | Data Quality Improvement Strategies | Real World Examples of Data Quality Improvement
How to achieve data quality & what success looks like in 2025
What does excellent data quality look like in 2025 and how can businesses achieve it in practical terms? This article explores the pillars of data quality, proven strategies for improvement, and real-world case studies to illustrate what success looks like.
What is Data Quality Mean?
High-quality data isn’t just about being “clean” or “accurate”—it’s about delivering the clarity and reliability needed to make decisions that count. In 2025, data quality means meeting these critical benchmarks:
- Accuracy: Information must reflect reality without errors.
- Accessibility: Teams must be able to access the right data when and where they need it.
- Consistency: Data should tell the same story across systems, teams, and departments.
- Completeness: Every critical data point must be captured to ensure a full picture.
- Contextual Relevance: Data should always be fit for its intended purpose.
Modern tools and processes mean there’s no excuse for poor-quality data. Automated solutions and proactive quality controls can identify and resolve issues before they cascade into larger problems.
How to Achieve Data Quality in 2025
1. Define Data Standards Early: Establish clear rules for what “quality” means in your context. Set up consistent standards for data entry, naming conventions, and validation.
2. Use Technology to Automate Quality Control: Automating tasks like duplicate detection, error correction, and data format checks can free up teams and ensure consistency. Platforms like Qlik Sense SaaS integrate these capabilities seamlessly.
3. Make Data Quality a Shared Responsibility: Data quality isn’t just an IT issue. Equip all teams with the tools, training, and confidence to maintain high standards.
4. Centralise Your Data Siloed systems lead to inconsistency and inefficiency. Migrating to cloud-based platforms ensures a single, reliable source of truth that’s scalable for your needs.
5. Continuously Monitor and Optimisation: Data quality isn’t a one-time fix. Implement regular reviews and proactive monitoring to adapt to changing requirements and evolving datasets.
What Success Looks Like: Case Studies
Streamlining Healthcare Decisions at West Gippsland Healthcare Group (WGHG)
The Challenge:
- Fragmented data systems led to delayed insights and inefficiencies.
- Manual reporting consumed excessive staff time and was prone to errors.
- Decision-makers lacked a single source of truth to guide resource allocation.
The Solution:
- Centralised data management through Qlik Sense SaaS, uniting previously siloed systems.
- Automated reporting pipelines replaced manual processes, improving accuracy and saving time.
- Custom dashboards provided leadership with instant access to key metrics.
The Result:
- Reduction in time spent on manual reporting tasks.
- Faster, data-driven decision-making for critical operations.
- Improved alignment between data insights and patient care strategies.
Read the case study here.
FMCG Operations, Transformed at Fyna Foods
The Challenge:
- Disjointed systems made it challenging to track inventory and operational efficiency.
- Reporting processes were too slow to adapt to fast-moving market demands.
- Collaboration across teams was hindered by a lack of real-time data access.
The Solution:
- Migrated on-premise systems to Qlik Sense SaaS for enhanced scalability.
- Designed real-time dashboards to monitor performance and inventory levels.
- Introduced automated validation checks to standardise data quality.
The Result:
- Reduction in time spent on manual reporting tasks.
- Improved cross-team collaboration via shared, real-time insights.
- Enhanced agility, allowing faster responses to market trends.
Read the case study here.
Data Quality in 2025
Data quality is essential for driving decisions, improving operations, and achieving meaningful results. As these case studies show, investing in the right tools, processes, and expertise pays off across industries.
At Notitia, we specialise in helping organisations create trust in their data.
Whether you need to overhaul your data systems, implement automation, or upskill your teams, we’re ready to help. Let’s talk about how we can transform your data quality in 2025 and beyond.
