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In the past decade, data science and machine learning have become indispensable tools to many types of businesses, from tiny startups to established multinational enterprises. Data processing, task automation, product recommendations, and financial analysis are just some of the areas that they’ve revolutionized.
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As organizations strive to make the most out of the data they collect, they turn to different techniques for generating insights from vast data sets. The market for data science and analytics is still on the rise – it is expected to reach USD 25.94 billion by 2027, according to a new report by Grand View Research, Inc.
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Are you looking to bring data science experts on board for your project? Expect to face a bit of a challenge. Data scientists who specialize in machine learning are in high demand today so finding and hiring talents will be a tough nut to crack.
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In recent years, the insurance industry has finally started to embrace digital technology, as insurtech startups have forced the traditional players to adapt if they want to survive. Wefox, a digital insurance marketplace, is at the forefront of the changes. Having successfully moved what has historically been a face-to-face business online, the company is looking into the future, a world where the Internet of Things, data science and artificial intelligence will play major roles in our lives, including how we insure what is valuable to us.
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So you’re ready to dive into the exciting world of AI. However, in such a rapidly-evolving field it may be difficult to decide how to go about it. What’s the best way to create a robust and effective AI product? Should you develop a custom solution or buy one off the shelf? We gathered practical pros and cons for both options to help you decide.
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