While AI has been the key business technology story of the 2020s, the real story gets less attention: data. It’s impossible to achieve AI's remarkably transformative effects – such as new competitive advantages, innovative business models, invaluable insights, and game-changing automation – without a single source of accessible, accurate, real-time data. 

While data is crucial to solving business challenges of all kinds, it often proves difficult to centrally access.

Yet the payoff of centralized data is considerable. When generative AI is augmented with your organization’s unique data, it can answer domain-specific questions, extract insights, and recommend best actions from data too large and dynamic for humans to analyze. It can save employees time with summaries, translations, code, and copy for emails, reports, and marketing content.

How generative AI tools can securely access internal data

Because few companies have the deep AI expertise or pockets required to train generative AI models from scratch, retrieval-augmented generation (RAG) is often used to enable secure access to proprietary data without the need to ingest and store it. This access enables contextual results while addressing privacy concerns. However, the data needs to be AI-ready, meaning it must be unified and integrated into vector databases or knowledge graphs.

In the Google Cloud ecosystem, a company may centralize their data using BigQuery as their data lake. From there, organizations can use Google Cloud’s Vertex AI, a fully managed generative AI development platform with 160+ foundation models and built-in vector and graph databases, to implement their generative AI initiatives.

Solving the data problem to smooth the path for generative AI and RAG

To create AI-ready data — and an intelligence-ready organization — you need two key data management capabilities: 

• Extract, load, and transform (ELT), which is the ability to reliably, securely, and cost-effectively move and integrate disparate data sources into a data warehouse or data lake and then integrate that data into AI-ready vector databases or knowledge graphs.
• Solid data governance tools that protect data security and access while ensuring data quality. 

Slow, manual ELT processes keep data inaccessible and prevent your teams from focusing on more interesting and valuable challenges. Automating ELT and data governance accelerates access to quality data not just for AI, but reporting, predictive modeling, Customer 360, and other use cases as well. 

Google Cloud and Fivetran partner to deliver fully automated, high-performance data integration, helping you realize greater value from your data and AI with less work. With Fivetran, you get a single, secure platform to seamlessly move any data into Google BigQuery or BigLake, enabling you to better leverage Vertex AI. By automating ELT, schema management, and security, Fivetran eliminates manual data processes and operational complexity, empowering teams to focus on developing strategic, production-ready AI use cases. 

You can set up Fivetran’s fully managed, self-healing data pipelines to BigQuery in just a few steps. With our no-code interface, managing your connection is straightforward and doesn't require special AI expertise.

With Fivetran and BigQuery, you can:

• Simplify data integration across hybrid and multicloud environments with 700+ data source connectors to create a single source of AI-ready data truth.
• Eliminate manual pipeline maintenance with automated error resolution.
• Scale data operations effortlessly with pipelines that automatically adjust to increasing data volumes and deliver 99.9% uptime.
• Ensure real-time data access for AI, predictive modeling, and advanced analytics with automated management, transformations, and updates.
• Keep data secure and compliant with end-to-end encryption, built-in governance tools, and automated compliance features.

Assess your data maturity and enterprise intelligence readiness

To benchmark your organization’s AI readiness — and to help make the case that AI starts with optimizing how you move and transform data — Fivetran and Google Cloud worked with IDC to create an online self-service assessment. Consider using it if your:

• Leaders, managers, and staff are unable to surface actionable data insights without asking the data team.
• Data team is bogged down by ELT work that slows access and limits their own strategic value.
• Analysis and BI tools are stuck in the past or lack the real-time data needed for actionable intelligence.
• AI adoption is lagging because your data structure can’t support RAG or fine-tuning models.

Find out where your organization stands against peers in enterprise intelligence readiness by taking the five-minute assessment now. And to learn more about Fivetran, our free trial period, and streamlined procurement through Google Cloud, visit Fivetran on Google Cloud Marketplace.

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