The pressure to achieve more with enterprise data is a pain many can relate to. In fact, three-quarters of leaders say they are under growing pressure to drive business value with data. That’s according to Salesforce’s State of Data and Analytics report, which surveyed more than 10,000 leaders across analytics, IT, and business. It also found that incomplete, outdated, or poor-quality data is the biggest obstacle to achieving this.
At 3T, we understand how this places pressure on organizations using MongoDB, increasing the need for stricter governance, smarter automation, and more effective workflows across complex environments. The most successful will rise to the challenge with tools and strategies that allow them to meet demands for accurate, transparent, and immediate data.
With that in mind, here are five must-know data analysis trends for 2026 and beyond.
1) AI will become a standard part of data analysis
AI is increasingly becoming an expected tool, rather than a differentiator. The Artificial Intelligence Report by Financial Information Management (FIMA) shows that 91% of respondents already rate their organizations’ AI capabilities as adequate or strong. For many, 2026 will be more about integrating AI with data analytics best practices.
As natural language querying, via tools like ChatGPT, becomes the norm, people will expect to query business data in this way (and get a clear, accurate response). This will see organizations shift toward AI-powered analytics and tools that interpret data and surface insights automatically. But remember that AI tools can have limitations around usability, efficiency, and data integrity, so it’s important to evaluate more secure and robust options.
Data analysts will need visual tools that automate and simplify complex database tasks, which would otherwise be time-consuming, manual and error-prone. Part of this is to empower more people to access data, while keeping sensitive information under wraps.
And, as we’ve talked about previously, with the right tools, AI and MongoDB could revolutionize data insights.
2) Data will be “pulled together” automatically across systems
Data fragmentation not only delays findings, but the inability to get the full picture (and issues like inconsistent formatting) harms accuracy too. A major challenge for organizations is data availability and quality. That’s driving growing interest in knowledge graphs and embeddings, with over half of respondents to the FIMA report saying they are exploring them to unify data across silos. That means less manual movement and reliance on experts knowing where the right data is.
That’s good news in almost everyone’s book, as Salesforce’s State of Data and Analytics report found 94% of business leaders say they’d perform better with direct data access in the programs where they work most.
So the expectation for 2026 is clear: analysts (and the wider business) want a unified view of data. And that requires the right tools to bridge the skills gap.
94% of business leaders say they’d perform better with direct data access in the programs where they work most.
3) Real-time analytics will overtake historical reporting
Demand for immediate insights is growing. According to Fortune Business Insights, in 2024 the global real-time analytics market was valued at $890.2 million. It expects this to grow to more than $5.2 billion by 2032.
Meanwhile, Salesforce’s research found 88% of data and analytics leaders are changing how they evaluate analytics software and implementations due to advances in AI, with ‘real-time data’ among the top data challenges. It’s easy to understand why this is worthy of closer attention, as there are all kinds of use cases requiring real-time insights, from AI chatbots for customer service to threat-detection for cybersecurity.
Organizations now expect analytics platforms to deliver real-time (or close to) insights rather than batch-only reporting. The good news is that for those willing to invest in real-time analytics, waiting around for reports about what happened yesterday may soon be a thing of the past.
In 2024 the global real-time analytics market was valued at $890.2 million. It expects this to grow to more than $5.2 billion by 2032.
4) Data governance and access control will become just as important as insights
As businesses empower more users to access data and generate insights, it’s increasingly important to manage data governance and compliance carefully. Awareness is also growing that data governance goes beyond compliance, and when properly implemented, offers a competitive advantage (thanks to benefits like improved data-driven decision making and fewer errors).
Over 65% of data leaders said data governance was their main focus in 2024 (ahead of data quality, self-service analytics, etc) and that’s only set to increase in 2026. Those that succeed will make sure to use tools that ensure permission-based access, traceability, and auditability, as these are fast becoming a must-have, rather than a nice-to-have.
5) The human analyst becomes more valuable, not less
While AI is capable of serving up information at speed, businesses still rely on human judgement for data-driven decision making. And analysts will have even more value as organizations integrate AI into their data pipelines. From checking the accuracy of the insights to contextually communicating the findings, the analyst will be key to businesses getting results from their data strategy.
And the data backs this up. The Salesforce research I mentioned earlier found 84% of business leaders say AI insights are only relevant if they’re grounded in business context, while 89% with AI in production have experienced inaccurate or misleading outputs due to poor data foundations.
To get this right in 2026, organizations need frameworks that allow them to carefully balance AI with human oversight.
89% of business leaders with AI in production have experienced inaccurate or misleading outputs due to poor data foundations.
The takeaway
With data quality, integration, and governance under greater scrutiny than ever, the organizations that succeed in 2026 will be those who turn data complexity into clarity, seamlessly, securely, and in real time.
At 3T, we have the tools to turn MongoDB complexity into clarity, so you get access to more insights that allow for real-time decision making and greater business value.
Experience the benefits of Studio 3T for yourself with a free trial or get in touch for a demo.
