Advanced Analytics and AI Strategy with Bob Rogers

Data is changing how we do business. The ability to use this data, to compete and to innovate, will determine the winners. Research shows that companies using advanced analytics and AI tools are five times more likely to make decisions more quickly than their competitors. Bob Rogers, chief data scientist for IT Transformation, Data Center Group at Intel, gives examples of companies using advanced ...analytics and AI to shape their futures, as well as describing two key imperatives to help achieve success.

Transcript

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We are in the throes of a digital transformation. And if you haven't realized it yet, you are a data company. Data is all around us, and it's changing how we do business. And the ability to use this data to compete and innovate will set the winners apart from the losers. In fact, research shows that with analytics and AI tools, you are five times more likely to make faster decisions than your competitors.

Companies around the world in all industries are using data to adapt and compete at an unprecedented pace. Sharp Healthcare is using AI to sift through years of clinical records to predict which patients are at risk of sudden decline. Fero Labs is using advanced analytics and AI to help manufacturers boost industrial output, prevent costly machine breakdowns, and reduce waste. And the Bank of New Zealand is using AI to create a more personalized customer experience.

But operationalizing analytics and AI does not come without challenges. I want to address two key imperatives that will help lead to success in your AI and analytics efforts. You need to tame your data and accelerate your journey with a Xeon-based infrastructure.

Let's start with data. There's no analytics without data. Over the last decade, we've seen a 10x explosion of data. But the reality is that most enterprises access less than 1% of their data for analysis. Data isn't useful if you can't apply it to your business. So getting your data layer right is a critical first step.

To do this, you need to unlock the data silos across your organization and know what data you have and what data you'll need. You need to ensure data can be used at scale through data modeling, cleansing, normalization, and transformation. It's also important to have stringent, well-defined data governance, lineage, and security policies. This upfront data work is difficult, and often missed in an effort to adopt analytics. But it's really critical to success.

A second imperative is to accelerate your deployment of advanced analytics and AI initiatives with a modernized infrastructure. Intel delivers breakthrough innovations and optimization for advanced analytics and AI workloads. Whether it's predictive analytics, cognitive computing, machine learning, or deep learning, we optimize all layers of the technology stack, from hardware to software to the application layer. We can help accelerate your success today by starting with your Xeon-based infrastructure and scaling out as you prove ROI.

A great example of this strategy is JD.com, the Chinese e-commerce giant. They leverage their investment in an analytics cluster based on Intel Xeon scalable processors to add new, deep-learning capabilities such as image recognition. This gave them the scale and performance necessary to improve their service.

Intel-based infrastructures are designed to deliver scalability, agility, and performance. And through our deep ecosystem partnerships, we optimize Intel-based solutions that can address data cleanup and transformation, as well as power your most demanding analytics and AI workloads.

Advanced analytics and AI are rapidly changing the competitive dynamics of every industry. To compete, you need a holistic strategy that uses a modernized infrastructure to deliver results. Intel can help you get started today.

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