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Five trends in machine learning-enhanced analytics to watch in 2021

Progress of AI-powered operations looks set to grow this year.. trends in machine learning

usage is growing rapidly. What does 2021 hold for the world of analytics, and how will drive it?

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningAs the world prepares to recover from the Covid-19 pandemic, businesses will need to increasingly rely on analytics to deal with new consumer behaviour.

According to Gartner analyst Rita Sallam, “In the face of unprecedented market shifts, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to accelerate innovation and forge new paths to a post-Covid-19 world.”

Machine learning and are finding increasingly significant use cases in data analytics for business. Here are five trends to watch out for in 2021.

1. Augmented analytics within embedded dashboards

Gartner predicts that by 2024, 75% of enterprises will shift towards putting and into operation. A big reason for this is the way the pandemic has changed consumer behaviour. Regression learning models that rely on historical data might not be valid anymore. In their place, reinforcement and distributed learning models will find more use, thanks to their adaptability.

A large share of businesses have already democratised their data through the use of embedded analytics dashboards. The use of to generate augmented analytics to drive business decisions will increase as businesses seek to react faster to shifting conditions. Powering data democratisation efforts with will help non-technical users make a greater number of business decisions, without having to rely on IT support to query data.

Companies such as Sisense already offer companies the ability to integrate powerful analytics into custom applications. As algorithms become smarter, it’s a given that they’ll help companies use low-latency alerts to help managers react to quantifiable anomalies that indicate changes in their business. Also, is expected to play a major role in delivering dynamic data stories and might reduce a user’s role in data exploration.

2. Greater commercialisation of and

A fact that’s often forgotten in conversations is that these technologies are still nascent. Many of the major developments have been driven by open source efforts, but 2021 will see an increasing number of companies commercialise through product releases. […] 

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