The Key Data Trends Shaping 2026
In today’s article, John Tallon, Practice Director at Storm, discusses the top data trends he expects to see in 2026, and how businesses can better prepare for what’s to come.
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From informing daily decisions to fuelling long-term business strategy, data is a key driver of business operations. However, not only are businesses using data to support planning, but they are also increasingly using data to finetune AI models and tools. With that comes a whole new set of challenges around data quality, data governance, and perhaps most importantly, security. Issues that will be key business priorities for 2026. Below we explore how businesses can tackle these issues head on and keep up with these data trends coming in the year ahead.
Unified Data Platforms to Enhance Governance and Security
With organisations increasingly leaning on data to power insights and train AI tools, robust data governance will become non-negotiable. Fragmented legacy systems, siloed data stores, and manual processes that make it more difficult to effectively govern and secure data will simply no longer cut it. For this reason, we expect that unified data platforms will dominate in 2026. More businesses will move to integrated, enterprise-wide data platforms that enforce consistent governance rules, metadata standards, access control, and compliance policies in order to reduce the risk of uncontrolled data sprawl.
Further, secure and well-governed data can:
Increase confidence in analytics, reporting, and AI models
Accelerate insights and better inform strategic decisions
Lower risk of misinformed actions
In the year ahead, we expect data governance to shift from being an IT concern to a strategic imperative that underpins the credibility of all data-driven initiatives. Unified data platforms, such as Microsoft Fabric, will be central to achieving this enhanced level of data governance. Microsoft Fabric can help businesses tackle security and governance challenges by integrating all enterprise data into one platform to centralise control and streamline data-based workflows, including data governance. The centralisation of business data means organisations can easily apply consistent governance policies across all data sets, and built-in security and compliance features help control access, encrypt, and protect sensitive data.
Data Readiness for Smarter AI Adoption
Many organisations are planning to increase investment in AI in 2026. However, before AI can deliver real business value, data must be prepared and cleaned. Duplicate, incomplete, inconsistent, or ungoverned data will only undermine outcomes and potentially lead to misinformed decisions.
In 2026, organisations will need to invest heavily in cleaning up their data estates. Otherwise, their ability to adopt AI effectively may be hindered, which will ultimately affect competitiveness. A data preparation project involving data cleansing, consolidating data sources, removing obsolete records, and applying consistent formats, controls and policies will be an essential first step. The main objective for many organisations will be to build data estates that are ready for AI workloads, machine learning, and advanced analytics.
In addition, ongoing maintenance will be required to keep data usable and trustworthy. This means teams will need to routinely audit their data to ensure the correct controls and policies are in place, as well as ensuring data is current and consistent. Organisations should also consider using advanced tools to streamline this process, rather than carrying out ad-hoc data dumps and manually preparing data. It may be useful to consider an automation solution that ingests, transforms, and validates data to ensure that analytics and AI tools are always operating on high-quality, timely data.
The Rise of the Data Analyst
As the maturity of tools like Microsoft Fabric and Copilot grows, the role of the data analyst is set to expand beyond traditional boundaries. Non-technical employees in departments such as HR, finance, and sales will increasingly be empowered to query and analyse complex data sets using natural language prompts, without needing advanced technical skills. This shift means data consumption will happen directly within everyday business applications, not solely in specialised BI dashboards, democratising data analysis to help accelerate decision-making and foster a more data-driven culture across the organisation.
However, it’s important to note that empowering data analysis in this way will rely heavily on the foundation of unified data governance, as mentioned previously. Without robust governance and security controls, there’s a risk that analysts, especially those outside IT, might inadvertently base decisions on unverified or “hallucinated” data. Ensuring that all data accessed and analysed is trustworthy, current, and well-governed will be essential to realising the full benefits of this new wave of self-service analytics.
If you would like to learn more about the data trends to come in 2026 and how you can get ahead, get in touch with one of our data specialists today.
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