Advanced Analytics in 2025: the intersection of enterprise data intelligence, business intelligence and artificial intelligence

Even as 2025 dawns, we still have a disconnect between data and decision making. It is no exaggeration to say that the average business executive is drowning in data. Unfortunately, making data useful to leaders requires highly specialized tools and specialists for advanced analytics. While data engineers and data scientists have impressive coding and other technical skills that enable them to process large volumes of data, there is a significant gap between technical skills and meeting business requirements.

Given most data scientists have come up through the academic ranks, it becomes a game of 20 questions for business leaders to tease out their daily realities from the complexities of the generated reports and dashboards and this leads to the quest for new and better advanced analytics solutions.

The Elusive Perfect Advanced Analytics Solution

While it is easy to find numerous definitions of data analytics on the internet, understanding the true nuances are where the challenges lie. Yes, data analytics is the science of analyzing raw data in order to make conclusions about that information or made simple: turning raw data into actionable decisions.

According to Gartner Managing Vice President Thomas Oestreich in his presentation on 5 Things That Keep Data Management Leaders Up at Night, “Data management leaders face numerous challenges, including increased demand for new data assets, governance challenges brought on by GenAI, improving operating models, and modernizing architecture and infrastructures.”

So how does one first understand where all of the source data originates, then contextualize that data and finally combine it in such a way as to making it actionable information by the business executives who have an unquenchable thirst for that knowledge in order to limit the impact identified by Mr. Oestreich above?

Business Intelligence, Artificial Intelligence and Enterprise Data Intelligence Made Simple

Unfortunately, the answer to that last question is not a one size fits all solution. In 2025, advanced analytics will evolve even further as we see the intersection of legacy technology and concepts with new advancements on the GenAI front.

• Business Intelligence: this market segment emerged in the late 1980’s and classified any technology that delivered “concepts and methods to improve business decision making by using fact-based support systems” introducing the first real (read usable) automated advanced analytics. Turn the clock forward to today and there are literally hundreds of automated BI tools available on the market and most (if not all of) these tools can require massive programming and setup from highly experienced resources in order to generate very insightful analysis to simple spreadsheets that shift the burden to the user to tease out helpful insights.
• Artificial Intelligence: The recent shift and awareness around AI has largely been driven by foundational models and specifically GenAI and Large Language Models (LLM), such as ChatGPT and Gemini, and the ability to work with unstructured data such as text, images, audio and video and the generative capabilities that bring to life a human type interaction that allows for the machines to understand the intent of the human and the desired outcome working with the data that they have been trained on.
• Enterprise Data Intelligence: Put simply, an enterprise data intelligence platform is more marketing-savvy way of referring to a data science platform which is a collection of generative AI, machine learning and business intelligence technologies with the express purpose of providing dashboards and reports on past, current and potential future states of your business operations, productivity, and ultimately profitability.

The bottom-line goal is to achieve actionable insights and automation ensuring individuals throughout your organization get the information they need in a human-focused format that it is actually usable. When business leaders ultimately get the information directly and in realtime, without waiting on others (i.e. data scientists, coders, etc), they control the formats & reports and can easily modify them by themselves.

Advanced Analytics in 2025

So how does one win the advanced analytics race in 2025?

The answer is actually easier to implement than you may think. Emerging open source, no-code intelligent cloud solutions like UBIX can deliver on the promise of an enterprise data intelligence platform to supercharge the quality of reporting and analysis with a decision intelligent cloud. By consuming all on-premise infrastructure, cloud-based infrastructure and cloud application datasets directly, UBIX makes the integration seamless and ensures that your existing data assets are fully utilized by LOB with a simple natural language query. This also frees data scientists and data analysts to address innovations instead of generating more superfluous reports.

Understanding the intersection of an enterprise data intelligence platform, your current business intelligence solutions and emerging GenAI with a decision intelligent cloud and how a no code solution can deliver on the promise of bridging the communication gap between the average business executive and the average technical/IT resource has never been easier. Download our free eBook titled “Solving the Problem of Data and Decision Making” to help better understand the details of emerging AI concepts and how to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–2025 Advanced Analytics Readiness Workshop, you can contact one of our experts today.