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A Complete Guide To Driving Digital Transformation In Marketing

datapine

Digital transformation is a broad term that is difficult to define precisely. Think of digital transformation as a way to future-proof a business. But, you can consider it a change in the business activities to prioritize your business’s digital presence. Steps To Driving A Successful Digital Transformation.

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Data Strategy: The Missing Link in Your Digital Transformation Plan

Smart Data Collective

On the surface, digital transformation is a simple process. This could be moving your spreadsheets to cloud software or even going so far as to move up from paper to digital. Specifically, we’re talking about how digital transformation efforts routinely fail to take advantage of the data they provide access to.

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From Cloud to Customer

CIO Business Intelligence

Marketing is becoming digitally transformed through the adoption of new cloud-based marketing applications. Different cloud platforms mean unproductive time spent cobbling together and homogenising data. Using this data collection method, the window of maximum campaign opportunity will close before a campaign is even started.

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12 most popular AI use cases in the enterprise today

CIO Business Intelligence

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

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The most valuable AI use cases for business

IBM Big Data Hub

Personalize customer experiences The use of AI is effective for creating personalized experiences at scale through chatbots, digital assistants and customer interfaces , delivering tailored experiences and targeted advertisements to customers and end-users.

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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

and constantly report this data to backend. At the backend, based on the data collected, data is stored in data lakes. Such data is collected from hundreds, thousands and millions of users. Then AI/ML algorithms are run on this collected data. IoT, Artificial Intelligence and Healthcare.

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