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Cloud is now the new normal, and data and AI are the new big things in IT. Yet, for many organisations, AI is a solution in search of a problem. The team at Cloudera says a strategy-first approach will bring you far greater gains.
With data being the new gold in today’s business environment, organisations across Australia and globally are turning to data intelligence and AI capabilities to excel in a rapidly evolving landscape.
Yet, when a company says it wants “an AI strategy” or “a data strategy” it’s implicitly letting the tail wag the dog. You need to start with company strategy and let that dictate the people, processes, and technology says Cloudera chief data and analytics officer Shayde Christian (pictured) and Cloudera ANZ solutions engineering team leader Vini Cardoso.
Christian guides data-driven cultural change for Cloudera to generate maximum value from data. He enables Cloudera customers to get the absolute best from their Cloudera products such that they can generate high-value use cases for competitive advantage. Previously a principal consultant, he formulated data strategy for Fortune 500 clients and designed, constructed, or turned around failing enterprise information management organisations.
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Christian and Cardoso recently partnered to deliver a presentation on building a data strategy at a recent Gartner conference. Their presentation was powerful in its simplicity, with four slides, and based on the thesis that while many people believe an enterprise data strategy is about tech, processes, and people, Christian and Cardoso say these are only a means to an end.
In fact, in their four-slide presentation, only one – the final slide – was about the means – the people, processes, and tech – with three about the path that leads you there.
“Align everything you do to corporate strategy,” Christian says. Then ultimately bring in KPIs and metrics to tell you how successful you are. “To think like the C-suite and get the executive engagement you must tie everything into that corporate plan.”
When it comes to their own product, Cloudera, the pair say you should implement Cloudera because your business strategy naturally leads you to identify you need data governance. However, you don’t start with that first, they say. You don’t start off a strategy around technology. You don’t decide you will cement your company goals around Cloudera and work out where to go from there.
The talk clearly resonated with the audience, with many in the audience taking photographs of the deck. It’s the Cloudera approach, Christian says. “We don’t spew this is what you need to do, how to do it, but give a framework.”
Of course, this does not mean the tech is irrelevant, and far from it. It’s vital to select the right tech stack to implement and achieve your corporate strategy.
“We have a long history of guiding customers through this,” Cardoso says. “The world’s going crazy over large language models like ChatGPT but it’s not a panacea. It doesn’t apply to all problems.”
“A lot of companies are putting a lot of time and energy into ‘ML’, by which they mean LLMs,” he says. “Five years ago companies were looking to Blockchain for everything. Be careful to think about the use cases. Next year I think the world will go back to focusing on machine learning.”
Christian adds, “When talking to a customer or talking internally we want to do three things: increase revenue, increase customer experience, increase operating margin. If you are using AI and have cases that warrant it, then you take AI into your walled garden where your environment is secure.”
When it comes to the issue of bias, Christian suggests the concerns may not be as significant as others would have you believe. “Most customers are not training on Internet data, but on their own financial data or product data. These are not controversial, and they’re not making the data public. There should be very little that is controversial in the data of most companies.”
Keeping that data secure is essential and here the Cloudera data platform has provided common data governance and security since the product’s inception. “This is what secures you on all clouds, on-premises, multi-cloud, hybrid …” Christian says. “Other competitors have a narrow sliver of the end-to-end data lifecycle, but you’ve been able to do that in our product for years. With our app, you can keep your data secure wherever it resides. Only those who need to access the data can.”
Cloudera is working with major banks and telcos in Australia, and with its focus on achieving business outcomes sees its work manifested as increased customer satisfaction, improved network performance, addressing Government requirements around analysis and compliance, banks addressing regulatory requirements with confidence, enhanced credit and risk models, has aided the bank sector to find things that have not worked well in the past, and many more results.
“Some of our insurance customers are utilising external images from space to look at the condition of events such as the California wildfires,” Cardoso says. “AI has been trained to detect homes that are partially or fully devastated. One of our customers used this, then wrote payments to affected customers the next day without site visits needed.” It’s a magnificent example of the power of AI to do good, and drastically improve customer service and deliver outcomes to people at one of the most difficult times in their life.
“We have customers spotting diseases with high accuracy, and using our platform to make the diagnosis exponentially more accurate.”
You don’t need to fear AI; by all means, be cautious, but Christian says, “recognise, and let the world benefit from, the great things that our customers have and will continue to be doing.”
And it starts with identifying your business goals. Let that guide your data strategy, your AI strategy, and your technology choices.
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