5 Steps to Implement an Enterprise Data Intelligence Cloud for AI Effectively the First Time

It should be no secret and no surprise that data is the new currency, and the ability to manage that data to effectively meet LOB requirements in a timely fashion sets the requirements bar even higher for IT teams. This is where emerging Enterprise Data Intelligence Cloud for AI solutions enter the equation.

Put simply, an Enterprise Data Intelligence Cloud for AI is a more marketing-savvy way of referring to a data science platform which is a collection of generative AI, machine learning, AgenticAI and business intelligence technologies with the express purpose of turning data into knowledge by providing dashboards and reports on past, current and potential future states of your business operations, productivity, and ultimately profitability.

Historically these solutions have required highly specialized resources to understand and tame these highly specialized tools. And given the average technical debt these resources face, the time lag for delivery of results often lagged behind the impact window for response, especially in light of the current statistics for AI transformation success versus failure.

The Cost of AI transformation failure

A new report from MIT Media Lab's Project NANDA is creating a huge buzz in board rooms and IT labs alike by reporting “that 95% of investments in gen AI have produced zero returns.” This is spawning a lot of press on the true cost of AI transformation and articles like Harvard Business Review’s “Generative AI Beware the AI Experimentation Trap” beg the question “If 95% of the tens of billions invested in experimentation has failed to produce value, is the effort to experiment with AI a complete waste?”

The short answer is yes, as those companies that fail to successfully accomplish AI transformation may struggle to meet tomorrow’s business profitability requirements. So, this begs the question of how to effectively implement elements of AI transformation while mitigating the risk of failure. The most likely business use case target the biggest LOB value, namely an Enterprise Data Intelligence Cloud for AI.

5 steps to implementing an effective Enterprise Data Intelligence Cloud for AI

Implementing an effective data intelligence cloud for I effectively the first time can mean the difference between profit and market failure. These 5 steps will ensure your success:

1. IDENTIFY: Identify business leaders and prioritize decision requirements that will most impact enterprise critical success factors
2. CONNECT: All available data sources inside and outside the enterprise should be identified and connected to the model along with access to business policies
3. ENABLE: Develop a new data analytics ecosystem to combine the best of current BI investments with new GenAI and reinforcement learning platforms to enable business-led AI transformation
4. EMPOWER: Business leaders get trained to satisfy their own requests for realtime analytics all with the only requirement being the ability to ask a question and therefore freeing valuable data science resources to focus on bigger picture revolutionary change opportunities
5. ITERATE: Understand that this is a process, not a project, so business-led AI transformation will be an ongoing learning experience for both the human and machine elements of the solution to planning, execution, analysis, and improvement recognition iterated ad infinitum

UBIX delivers an Enterprise Data Intelligence Cloud for AI effectively in days not months or years

Why wait for specialized resources like data scientists and data analysts to catch up with LOB requirements when you can empower those LOB subject matter experts to bridge the gap between data and domain expertise to get faster and more insightful insights than normal? Or even worse why trust that nothing will be lost in translation between the technical expert and the domain expert when scoping out the next business initiative?

Open source, no-code intelligent cloud solutions like UBIX can deliver on the promise of an enterprise data intelligence cloud for AI to supercharge the quality of reporting and analysis with a rapid innovation program:

• Deploy: Unlock your own secure virtual private cloud with all the benefits to get up and running with same-day deployment—no delays and streamline infrastructure setup with reusable, error-free code templates as well as automate routine tasks and free up your team to focus on innovation.
• Analyze: Tap into a big data analytics store with endless insights and easily integrate with 300+ connectors to unlock all your data to seamlessly connect and analyze data from your legacy systems and then dive into a data playground designed to supercharge your analytics.
• Transform: Accelerate innovation with ModelSpace and SolutionSpace and access a no-code model library for both analytics and AI, enabling rapid innovative development to launch and scale effortlessly with one-click rollouts.

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 ChatUBIX using simple natural language query . This also frees data scientists and data analysts to address innovations instead of generating more superfluous reports.

Understanding the nuances of an enterprise data intelligence cloud for AI and how a no code solution can deliver on the promise of bridging the communication gap between LOB and IT has never been easier. Download our free eBook titled “5 Steps to AI Business Transformation Success” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AgenticAI Readiness Workshop, you can contact one of our AI experts today.