Big Data Intelligence with AI

  • November 3, 2017

    Artificial intelligence and big data are inextricably linked. One of the key practices in digital transformations is leveraging AI to process and learn from big data.

    We often hear “big” data in the business lexicon. So what makes big data big to begin with? Asaf Yigal in his article, The Intersection of AI and Big Data describes it as a diverse, high volume set of information that must be processed at high speeds. By analyzing big data, businesses can make informed, strategic decisions and learn more about their customer base. Public health organizations can use electronic health data to predict early disease detection. Political campaigns can use it to effectively recruit volunteers and donors. The uses for big data are infinite.

    Big Data Sometimes Gets Too big  

    Big data comes with its challenges. As IT operations flock to the cloud, the information living in the cloud becomes larger and more complex by the minute. Many organizations house their data in a variety of methods from serverless environments to public cloud servers. Big data becomes extremely difficult to manage and analyze. One of the solutions to mitigate this problem is artificial intelligence (AI).

    AI helps cut through the noise. By processing data quickly and making deductions through analysis, AI can make sense of big data when humans cannot.

    What is AI?

    Artificial intelligence is a broad term to describe machines executing tasks that we deem “smart”. Even more so when a user cannot decipher the difference between a computer- generated response and a human response. Machine learning applies AI in a way that computers can predict outcomes based on data. Over time, they actually learn and algorithms are augmented to predict outcomes more accurately. We may no longer need to teach computers as they can teach themselves.

    Big Data Powered by AI

    Some of today’s most revolutionary technologies depend on the intersection between AI and big data. Yigal provides the example of autonomous vehicles. The cars rely on machine learning from terabytes of data to determine how to maneuver in traffic situations and how to navigate routes. The same principles can apply to your DevOps program. Machine learning navigates the complexity of big data and can help make strategic, data driven solutions quickly that will take your business to the next level.

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