08/05/2025
Table of ContentsBusinesses are collecting more data than ever — customer behaviour, sales trends, operational metrics, you name it. Instead of clarity, however, they are left with overwhelming clutter.
Despite the abundance, organisations face significant challenges in extracting meaningful insights.
From startups in Southeast Asia to Fortune 500s in the US, companies face the same data headaches: poor data quality, scalability issues, weak governance, and inaccessible insights. These challenges don’t just slow things down; they limit growth, efficiency, and innovation.
Yet, the opportunity is massive. According to Fortune Business Insights, the global data analytics market is projected to grow to US$961.89 billion by 2032 from US$348.21 billion in 2024, with a compound annual growth rate (CAGR) of 13.5%. This reflects how organisations aim to harness their data more effectively to stay ahead in performance, innovation, and resilience.
To get there, you need an objective view of your enterprise’s data and analytics capabilities. Knowing exactly where you stand lets you unlock real value from your data. This guide outlines how to improve data quality, strengthen governance, and bring clarity to your decision-making.
6 Ways to Achieve Business Clarity Through Data
Clarity is possible, and it doesn’t require a massive overhaul.
It starts with intentional steps that help you understand your data, use it wisely, and make confident decisions. Here are six practical ways to cut through the noise and move your business from data overload to data-driven clarity:
1. Appoint Data Champions
Businesses should appoint multiple data champions across teams to build a strong data culture. These individuals will take the lead in driving data initiatives within their areas. They are key to helping organisations promote data literacy, encourage data-driven decision-making, and align data efforts with business goals.
Given regulators' and stakeholders' rising expectations, today’s data champions can also oversee data privacy, regulatory compliance, and data quality — embedding responsible data practices throughout the organisation.
Data champions are accountable for tracking and reporting the value of data initiatives. With HFS Research revealing that fewer than one in three leaders are fully satisfied with how well their data supports business goals, many companies still face challenges linking data quality to business outcomes. The right people can help close this gap.
2. Clean Up Your Data House
Businesses today face a growing problem of data debt: the accumulation of outdated, inaccurate, or poorly managed data. HFS Research data shows that over 40% of organisational data is bad or unusable, leading to an estimated 35% loss in potential value across business functions. This not only affects productivity but also creates hidden costs that slow down decision-making and innovation.
With the rapid rise of AI tools, the urgency to clean up data has become even more critical. Many organisations are eager to integrate AI into their operations, but poor data quality remains a major roadblock. According to our AI and Information Management Report, 52% of organisations faced significant challenges with internal data quality during AI implementation efforts.
To address this, businesses should take a structured approach to data cleansing and governance. This requires identifying key data assets, assessing their quality, and removing duplicates or outdated entries. Also, invest in tools or processes that ensure data remains accurate and up to date. Cleaning up your data house is not just a technical task — it’s a strategic move that enables better data-driven insights, smoother AI adoption strategies, and stronger business outcomes.
3. Break Down the Silos
Data silos remain one of the most persistent barriers to operational efficiency and advancement in modern enterprises. When departments store data in isolated systems, it hinders collaboration and slows down decision-making.
According to the IBM Data Differentiator, a staggering 82% of enterprises report that data silos disrupt their critical workflows. This fragmentation affects day-to-day operations and undermines strategic initiatives that rely on integrated, real-time insights. Businesses must recognise that breaking down these silos is not just a technical challenge — it requires teams to constantly adhere to best practices when leveraging new platforms and following strict guidelines. Moreover, the cost of inaction is significant. IBM also found that 68% of enterprise data remains unanalysed due to being siloed with no clear access and visibility, representing a massive untapped resource.
To address this, companies should prioritise implementing unified data platforms, encourage cross-functional data sharing, and invest in data governance frameworks that promote transparency and accountability.
4. Migrate to a Database Platform
Businesses relying on outdated data systems should explore migrating to a modern database platform. This move centralises data storage, improves accessibility, and supports real-time analytics for faster, data-driven decisions. A unified database not only prevents data siloes, but also reduces duplication, strengthens data security, and makes it easier to integrate with business intelligence tools like Qlik.
When planning a migration, begin by auditing your current systems. This will help you choose a database platform that aligns with your business needs — whether on-premises, cloud-based, or hybrid.
Database platforms also offer massive scalability and flexibility, enabling organisations to adapt swiftly and confidently in a data-driven environment. They integrate seamlessly across various technologies and data sources, allowing businesses to respond effectively to real-time demands.
5. Don’t Just Analyse, Visualise
Data analysis alone is no longer sufficient. Organisations must also focus on how data is visualised to drive timely and impactful decisions. Visualisation tools help translate complex datasets into intuitive, interactive dashboards that make patterns and insights easier to understand and act upon.
According to Qlik, businesses experience time savings of up to 35% on data analysis thanks to powerful capabilities in visualising, aggregating, and organising data. This accelerates the analytics process and empowers teams to make faster, more informed decisions.
By embedding visual analytics into everyday workflows, organisations can ensure insights are not just generated but also understood and applied where they matter most.
6. Use AI to Spot What You Can’t
Traditional analytics methods often fail to uncover deeper, hidden insights, especially within unstructured data. This is where AI and machine learning come in. By embedding these technologies into data analytics tools, organisations can significantly enhance their ability to extract, analyse, and interpret complex data sets.
In fact, businesses have been adopting AI and big data analytics trends at a rate of 60%, recognising the value of these tools in boosting the efficiency and depth of their data analysis. Use cases include customer churn prediction, fraud detection, and demand forecasting, among many more examples. With AI-powered platforms, teams can move beyond surface-level reporting to uncover patterns, anomalies, and opportunities that would otherwise go unnoticed.
Find Out How Data-Ready Your Business Is
Achieving clarity in a world of data overload is not only strategic; it’s essential. From appointing data champions to leveraging AI for deeper insights, each step outlined above helps build a stronger, more agile, and data-driven organisation.
That’s where AvePoint and Qlik can help. We enable businesses like yours to confidently turn data into decisions through:
- Data integration and transformation
- Advanced analytics and visualisation
- AI-powered insights
- Scalability and flexibility
Knowing where to begin (or how far you’ve come) requires an honest and objective assessment of your current data and analytics capabilities. Our free data assessment provides:
- Data strategy evaluation
- Data and analytics capabilities review
- Industry benchmarking
- Insights and best practices to level up your data strategy
Ready to assess how data-ready your organisation truly is? Take the first step towards clarity today.
