Your company’s most valuable data, decades of financial records, customer histories, and supply chain information, is a goldmine. The problem? It’s often locked away inside powerful, well-managed but rigid legacy systems like SAP or Oracle. For many organisations, this creates a major barrier to deploying AI on legacy systems at scale. You know you need to innovate with AI and modern analytics to stay competitive, but the thought of a massive, multi-year “rip and replace” migration is probably not an option. It feels like you’re stuck: risk falling behind, or risk a project that could disrupt your entire business?
The good news is, this is a false choice. You don’t have to break your existing foundation to build something new. With Google Cloud, you can create a flexible, intelligent bridge to your current systems. This allows you to start reaping the benefits of AI and modern data analytics today, taking low-risk, high-value steps that free you from vendor lock-in without the immediate need for a full migration. Here are two practical examples of how to do just that.
Solution 1: Create a BigQuery Analytics Layer for Real-Time Insights
The Problem
Waiting days for a specialist to build a new report from your SAP or Oracle system is a familiar pain point. Your business teams need to move fast, but legacy reporting is often slow and requires expert knowledge. They can’t explore the data themselves, which means opportunities are missed and decisions are delayed.
The Solution
The first, easy step is to replicate your legacy data into BigQuery, Google Cloud’s serverless data warehouse. What makes this so simple is that you skip the entire complex setup phase. There are no clusters to provision or servers to manage. You simply connect your legacy data source, and your data has a new, flexible home for analysis. It’s a low-risk first step that gives you a quick win without disrupting your core business operations.
Once your data is in BigQuery, you put Looker on top. This is where Looker is fundamentally different from most dashboarding tools. Instead of letting everyone define their own calculations in separate reports—which often leads to different teams reporting different numbers for the same metric—Looker uses a universal semantic modeling layer. Think of it as a single, governed source of truth for your most important business metrics, like “quarterly sales” or “customer lifetime value.” This ensures that key metrics mean the exact same thing for everyone, everywhere, building a foundation of enterprise trust.
On top of this trusted foundation, Looker provides a “Google-easy” experience for your business teams. They get an intuitive, drag-and-drop canvas to build their own compelling reports and dashboards. And now, this is supercharged with Gemini in Looker. Your teams don’t even need to be experts in the tool; they can simply ask questions in natural language, ask for help creating visualizations, or have AI assist with formula creation. It’s a powerful way to deliver governed, self-service analytics to your entire organization, solving a real business problem almost immediately.
Solution 2: Turn Your Legacy System into a Conversation Partner
The Problem
Your employees have questions. “What’s the status of purchase order #12345?” “How much of product Y do we have in the Brussels warehouse?” The answers are in your system, but finding them requires navigating complex screens and reports. This manual effort, repeated hundreds of times a day across your organization, adds up to a huge loss in productivity.
The Solution
With your data already available in BigQuery from the first solution, you can now give it a voice. We can build a secure, internal AI assistant using Gemini and the Vertex AI platform. This isn’t a generic chatbot, but an expert on your business data.
The standard approach on other platforms often requires you to assemble a complex pipeline: you need to set up and manage a vector database, write code for data chunking and embedding, and then orchestrate the entire retrieval process. It’s a significant data science project before you even get to the “chat” part.
Google’s innovation is to turn this complex engineering problem into a much simpler configuration task. You simply point Gemini at your secure BigQuery data. It then handles the indexing and optimizing your data for semantic search completely automatically. This turns a multi-month engineering effort into a task that can be completed in days.
With Gemini and BigQuery, your team can now ask questions like:
- “What was our sales total for product X in Q2 in the Benelux?”
- “Show me all open invoices for customer Z.”
And there you have it. You’ve just turned your legacy system from a complex database into an easy-to-use conversation partner, empowering your team and accelerating decision-making across the board.
Your Journey Away from Lock-In Starts Here
You don’t have to be trapped by past technology choices. The journey to a more flexible, AI-driven future doesn’t start with a risky migration. It starts with smart, strategic steps that add immediate value.
Need help building that bridge to your legacy systems? At GC innovate, we have the deep expertise in both Google Cloud and enterprise environments to guide you. Backed by the entire Cronos network, we can help you design and implement these solutions, ensuring you take the right first step.
In need of support? Contact us today!
