There are literally hundreds of articles written on the fact that data by itself is relatively useless, and in some cases even dangerous, yet billions of dollars are spent collecting, storing and managing data. The rational for why data by itself is useless is the recognition that without context it can’t be used as information for decision making. Unfortunately, analyst firms like Forrester report that an average, between 60% and 73% of all data within an enterprise goes unused for analytics. Which opens the opportunity for how to unlock insights for legacy data as a prime directive for most every organization today.
Back in 2017 The Economist reported that “The world’s most valuable resource is no longer oil, but data.” Turn the clock forward to 2025 and the proliferation of new artificial intelligence (AI) Generative AI (GenAI), and Reinforcement Learning has made that prediction more real than ever. The bottom line here is recognizing that all AI transformation initiatives must start with an understanding of legacy data. But just ingesting legacy data is not enough. Understanding source, context, reliability, and timeliness is also required.
Industry analyst firms like Gartner host webinars as well as offer eBooks on how to become a better data and analytics leader. The core of their advice hinges on an understanding of the correct use of data for decision making and the alignment of business and technical stakeholders to ensure success in a timely fashion.
Ultimately the business side of any organizations requires the right information is provided to the right person at the right time to ensure productivity, a competitive edge as well as profitability. Having business executives tapping into legacy data without the need for specialized business intelligence tools or resources like data scientists to customize reports. The correct application of GenAI plus reinforcement learning to legacy data can open an entire new world of possibilities to business executives.
Some key use cases include:
It also helps to understand the differences in value between Business Intelligence, Artificial Intelligence and Enterprise Data Intelligence when making investments in unlocking the value of legacy data.
A data intelligence cloud delivers on the promise of business-led AI transformation by providing a pre-configured, enterprise-grade cloud infrastructure from day one where organizations can immediately migrate existing data and analytic workloads and simultaneously build new AI-driven insights on the cloud.
Emerging open source, no-code intelligent cloud solutions like UBIX can deliver on the promise of a data intelligence cloud to supercharge the quality of reporting and analysis. It starts with a comprehensive access to all available data. 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. The good news is that you can realize results in days, not months or even years. This is what also frees data scientists and data analysts to address innovations instead of generating more superfluous reports.
Realizing the promise of a data intelligence cloud starts with an understanding of the realities (as opposed to the hype) of emerging GenAI + Reinforcement Learning with a no code solution that delivers on the promise of bridging the communication gap between the average business executive and the average technical/IT resource. 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 Data Intelligence Cloud Workshop, you can contact one of our experts today.