Cloudera Study Reveals Unified Data Fuels AI Growth

90% of IT leaders believe that unifying the data lifecycle on a single platform is critical for AI and analytics development, according to a Cloudera study

While organisations may be investing in artificial intelligence (AI), there are still challenges to be overcome in the business environment. 

With generative AI (Gen AI) in particular continuing to grow worldwide, having trustworthy data is essential. In fact, a recent study conducted by software company Cloudera has found that the rise of AI is impacting enterprise data strategies, revealing 90% of IT leaders believe that unifying the data lifecycle on a single platform is critical for analytics and AI.

The survey was conducted with IT decision makers and found the main obstacles faced in enterprise AI journeys include quality and availability of data (36%), scalability and deployment challenges (36%) and integration with existing systems (35%).

Cloudera suggests that the key to successful AI is in modern data architecture, unified data management and versatile data platforms

‘AI insights are only as powerful as the data feeding them’

With Gen AI continuing to explode in popularity, trustworthy data has never been more vital.

Within the global business landscape, the vast majority of organisations are keen to develop and deploy Gen AI to disrupt their operations. However, research suggests that many currently underestimate the requirements of building and maintaining a clear AI strategy long-term.

Notably, only a small number of businesses currently believe they have the right level of technology, funding and skill sets to support the rapid adoption of AI.

In order to better protect company data, the Cloudera study found three foundational requirements for organisations looking to achieve effective AI

A modern data architecture grounded in business strategy

Having a single data platform that works seamlessly across public cloud and on-premises. Cloudera highlights that, when it comes to the benefits of modern data architectures, the most popular responses from IT leaders were simplifying data and analytics processes (40%) and gaining flexibility in handling all types of data (38%).

Unified data management

Cloudera suggests that organisations need flexible and scalable cloud management technologies. These help to provide the relevant tools to turn information into insights. According to Cloudera’s research, 62% of survey respondents said it’s the volume and complexity of data (62%), data security (56%) and governance and compliance (52%) that are holding back end-to-end data management that’s needed for AI model development.

Versatile and secure data platforms

From a long-term perspective, Cloudera states that embracing a hybrid data management approach including both on-premises and public cloud deployments is the preferred data and analytics strategy.

In fact, 93% of those surveyed agree that “multi-cloud/hybrid capabilities for data and analytics are key for an organisation to adapt to change.”

With companies around the world looking to accelerate their AI strategies amidst a turbulent and competitive market, ensuring a clear and clean strategy to protect essential data is paramount.

“As more enterprises look to transform their businesses to build digital and AI ready solutions for their customers, they are choosing a hybrid and multi-cloud strategy, which in turn creates ‘data sprawl and architectural overruns’ across LOBs, functional units, business applications and practitioner teams,” says Abhas Ricky, Chief Strategy Officer at Cloudera. 

“In order for them to effectively leverage AI capabilities, organisations need to design and embed standardised, use case-centric data architectures and platforms that will allow disparate teams to tap into all of their data – no matter where it resides - whether on-premises or in the cloud.”


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