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Using AI augmentation to empower database administrators

23 Mar 2022

As data platforms rapidly evolve and become more powerful, DBAs are the important link between data scientists and business users.

This article first appeared on Capgemini’s Data-powered Innovation Review | Wave 3.

Written by:

Arvind Rao
Partner Architect Advisor
Google Cloud

Most enterprises already have the talent in-house to start using AI to unlock the full potential of their data. They are the database administrators. They know the data, they know the organization, and they are trusted advisors – they just need a little help from data-platform vendors.

The world’s largest organizations generally understand that to continue to succeed in today’s competitive environment, they need to become data-powered enterprises. They acknowledge that it’s imperative to modernize their data and harness the full power of tools such as AI to derive actionable insights. However, many of these companies have also learned that human resources are a major challenge in making this transformation.

In short, there are not enough data scientists – those who create the solutions that leverage state-of-the-art technologies such as AI. Based on my experience in data analytics over the past couple of decades, in an ideal world data scientists would account for 10 to 15 percent of the staff at a data-powered organization. Yet the majority of organizations – including most successful technology enterprises – have not achieved that ideal/goal.


DBAs to the rescue

The good news is most enterprises already have the talent to successfully make this transformation. Database administrators (DBAs) – those who manage a company’s data warehouses and similar data platforms – are the backbone of most IT operations. These professionals understand the data an enterprise has collected, where it’s stored, and how to use it. They ensure authorized people have access to the data they need. And since data is sensitive and valuable, they control who has access to it to keep it safe from misuse or theft.

Knowledge and trust

As a result, database administrators know more about their company’s data than anyone else in their organization. They certainly know more than the data scientists who work for the technology vendors that develop the data platforms upon which modern enterprises rely.

At the same time, database administrators are trusted advisors within their enterprise. They’re the go-to source for help when a business user needs to derive insights – whether that’s a salesperson looking to improve lead generation, a service manager trying to spot potential customer satisfaction issues, or an executive seeking market predictions for the coming year.

It, therefore, makes sense to ensure database administrators can leverage the insights and capabilities of AI-augmented data platforms.

The Lake House

The majority of data-platform vendors have been working towards the concept of a Lake House – a convergence of databases, data warehouses, and data lakes – that makes the platform usable and accessible to everyone and everywhere. With data scientists increasingly focused on creating these new platforms, vendors have fewer resources to dedicate to building, managing, and maintaining the – often highly customized – tools required by business users. That’s why it’s important that data platform vendors augment their solutions with AI. It’s also why these AI augmentations must be easy to use in the DBA’s day-to-day role: They should not have to invest huge amounts of time learning data science to take advantage of these tools. Enterprises are increasingly demanding this simplicity of their suppliers – whether they are vendors of databases, data platforms, analytics, or cloud-based solutions.

At Google, we’ve developed a number of solutions that help bridge the gap and create data warehouses infused with AI/ML that work for all users – not just data scientists.

  • Vertex AI brings together Google Cloud services for building machine learning in a unified user interface and API. With Vertex AI, a database administrator can easily train and compare models using AutoML or custom code training. All models are stored in one central repository and can be deployed in ways that allow DBAs and other non-data scientists to start using AI/ML in their day-today work, with very little training.
  • Dataplex is an intelligent data fabric that breaks apart silos. It provides a single pane of glass that allows database administrators to centrally manage, monitor, and govern an organization’s data – including ingestion, storage, analytics, AI/ML, and reporting. It does this across any type of platform – including data lakes, data warehouses, and data marts – with consistent controls that provide access to trusted data and power analytics at scale.
  • BigQuery is a serverless, cost-effective, multi-cloud data warehouse designed for business agility. BigQuery democratizes insights with a secure and scalable platform to perform functions such as anomaly detection, customer segmentation, product recommendation, and predictive forecasting. It features built-in machine learning to derive business insights using a flexible, multi-cloud analytics solution and adapts to data at any scale from bytes to petabytes with zero operational overhead. Most importantly, database administrators can learn BigQuery and easily incorporate it into their tasks

The smart data-warehouse platform

Looking ahead, I envision a future in which most successful organizations deploy a smart data-warehouse platform that provides a number of important benefits. These include:

  • Easy access to the organization’s data, public data, and other business data – without worrying about what kind it is or where it’s stored
  • Serverless tools to access data in real-time, to mine and infuse AI/ML capabilities. These would be scalable on-demand, set a strong foundation for building AI models, and be cost-effective.
  • Reporting tools that showcase analytics in real-time – in a safe, secure, and scalable way
  • Modern data warehouse capabilities equip all users with the tools and resources they need to do their jobs efficiently and effectively, and that provide CXOs with the tools they need to keep their staff motivated.

As enterprises work to achieve this goal, leveraging AI to empower database administrators in their day-to-day work is something they can do now, and do cost-effectively. They just need the right tools from their vendors.

Giving DBAs easy-to-learn AI-powered tools will enhance the value they already provide to the enterprise. It can also help keep these knowledgeable team members – the organization’s trusted advisors on all matters IT-related – relevant as the enterprise embraces a new, more powerful, and innovative data-powered future.



Database administrators know the company’s data and are trusted by its people. They have important roles to play in an organization’s transformation into a data-powered enterprise.


Database administrators bridge the gap between the data scientists who are creating the next generation of AI-powered analytics tools and the business users who will benefit from the insights such tools provide.


Data-platform vendors must incorporate easy-to-learn AI tools into their products so database administrators can take full advantage of these state-of-the-art solutions.

Interesting read?

Data-powered Innovation Review | Wave 3 features 15 such articles crafted by leading Capgemini and partner experts in data, sharing their life-long experience and vision in innovation. In addition, several articles are in collaboration with key technology partners such as Google, Snowflake, Informatica, Altair, A21 Labs, and Zelros to reimagine what’s possible.