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The Future of Artificial Intelligence for Analytics
(Image source: https://www.pexels.com/photo/high-angle-photo-of-robot-2599244/)
If you’ve been working in analytics for a while, you know just how far the industry has come over the past decade and beyond. While data analysis has long been a priority for major companies around the world, artificial intelligence allows businesses to unlock their data more efficiently than ever.
With the analytics space changing dramatically seemingly every year, it can be tough to stay on top of the latest trends and developments. Let’s take a look at three of the most important AI-related changes facing data analytics in 2021.
Natural Language Processing
Natural language processing is a rapidly growing field in the analytics space. In fact, the natural language processing market is expected to reach over $2.5 billion by 2027, nearly four times higher than its 2021 size of $703 million.
Alongside other benefits, natural language processing makes it easier than ever for people to engage with data analytics—even if they don’t have as much experience or expertise working with data. Furthermore, natural language generation facilitates automated report preparation, making AI-powered insights even more accessible to a lay audience.
Unstructured Data
Conventional data analysis practices work fine for certain types of information, but they aren’t a great fit for “unstructured data”—things like images, audio, and text that aren’t as easy to interpret.
While there are still challenges involved in analyzing unstructured data, it’s clear that AI is making it easier than ever to work with this kind of information. This allows companies to use a wider range of data without compromising accuracy.
Machine Learning
For a long time, basic regressions were often the best tool companies had for decision making. Machine learning offers deeper insights and much greater efficiency compared to more conventional methods, so it’s no surprise that more and more businesses are adopting it every year.
Predicting short- and long-term outcomes, for example, is far more practical with a machine learning tool that can extract trends from historical data. These systems are also incredibly effective when it comes to identifying anomalous information—for example, transactions that could be the result of fraud.
Artificial intelligence is already being leveraged in nearly every industry, and it’s only going to become more important throughout the 2020s. These trends are rapidly changing the way businesses of all sizes use data to guide decision making. Don’t hesitate to investigate how an ai-powered bi tool can help you update your approach to data analytics.
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