This week, big data or good data? How AI and ML are using previous projects to learn and enhance the accuracy of predictions and decision-making. And a new way of working during the pandemic packed 10 years of digital innovation in to 3 months.

Manufacturing AI Is about good data, not big data

By Kai Yang, contributing writer for Industryweek.com

Manufacturing is starting to adopt AI to boost efficiency, but current AI approaches won’t always work.

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Can AI, machine learning accelerate sales and marketing?

By Monica Sullivan, contributing writer for Martechseries.com

With supply chain challenges and the ongoing global pandemic regularly introducing new obstacles, sales and marketing professionals must continue to move at the speed of business regardless of where they currently work. According to McKinsey, our new way of working during the pandemic inspired ten years of digital innovation in three months. To ensure no opportunities are missed in this rapidly changing landscape, sales and marketing teams need data to unearth new, actionable insights that they can use to identify in-market prospects and customers at scale.

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Generating real-world evidence at scale using advanced analytics

By Representatives from McKinsey’s Life Sciences Practice, contributing writers for McKinsey.com

Advanced techniques for generating real-world evidence (RWE) help pharmaceutical companies deliver insights that transform outcomes for patients—and create significant value. McKinsey estimates that over the next three to five years, an average top-20 pharma company could unlock more than $300 million a year by adopting advanced RWE analytics across its value chain.

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Leveraging machine learning to add value to direct marketing

By Srikanth, contributing writer for Techieexpert.com

Machine learning (ML) utilizes Artificial Intelligence (AI) to enable a system to learn a particular thing autonomously. While AI seeks to mimic human intelligence, ML forms historical data and applies that information independently to the performance of specific tasks. Eventually, with the increasing amount of data, the machine can learn from previous projects and enhance the accuracy of predictions and decision-making. Note that businesses accumulate a massive amount of data from direct marketing.

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