DATA & ANALYTICS
“ It is wonderful to see AI becoming far more mainstream ” CHRIS ROYLES EMEA FIELD CTO | CLOUDERA
Effectively applying AI & ML to analyse large volumes of data : Derive actionable businesses insights At Cloudera , they have always believed data is a foundational resource to derive actionable insights . Services such as ChatGPT have raised awareness and fuelled conversations about AI and its potential business benefits . “ For organisations to truly benefit from the innovations in generative AI and Large Language Models ( LLMs ), they should look to use existing Open Source foundational models to augment how they converse with their trusted and private Enterprise data ,” says Royles . “ We refer to this as Enterprise AI , and how an Open Data Lakehouse can support Enterprise AI that organisations and their customers can trust .”
To achieve AI at scale and drive digital business transformation , Royles advises that organisations must be able to secure and govern all of their data , irrespective of where it resides under management . “ By building a corpus of trusted information , organisations can use it to underpin engaging user interactions . To build trust the services also have to be current , aware of the latest information and able to respond to changes in real-time .”
Key challenges in implementing AI-driven data analytics projects - and strategies to address these challenges Implementing AI-driven data analytics projects poses several challenges that organisations must address strategically .
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