Enter the age of analytics

 

Data and data analytics is here to stay, and to make our lives much simpler. Today an increasingly greater number of business decisions, critical ones at times, are made using data of such complexity that the human mind struggles to comprehend them.

 

It is believed that by 2023, AI and deep-learning techniques will be the most common approaches for new applications of data science. And to keep up with the times, data and analytics (D&A) leaders must invest in intelligent and intuitive technology to support their organization’s users.

 

Here are two key trends that will shape analytics in the years to come.

Trend No. 1: The rise of AI and deep learning

Even though artificial intelligence (AI) and deep-learning techniques will be the most common approaches for new applications of data science, these new technologies come with their own set of challenges, the leading one being peoples’ suspicions of analysis they don’t understand.

 

Earlier, analytic techniques were always comprehensible, at least in conceptual terms. Even if users did not understand a specific model, they understood the logic behind it.

 

Deep learning, even though it delivers more-accurate results, lacks transparency. If users are unable to comprehend how the solution was achieved, they tend to distrust the technology.

 

Another concerning restriction on the corporate adoption of deep-learning techniques is the threat of lawsuits over difficult-to-explain algorithms that could make a mistake. D&A leaders should involve the legal department before deploying a new technique.

Trend No. 2: Intelligent and augmented insights

Relevancy is a key criterion for analytics. Users should not have to look for information; instead, the system should recognize that a piece of information is relevant to the user and deliver the insights preemptively.

 

Many analytical platforms already integrate augmented analytical techniques. They detect trends and correlations in the data, and suggest ways to interpret the results in natural language.

 

As users begin to increasingly expect intuitive interface mechanisms, organizations should invest in analytics technology that can deliver. AI techniques can be deployed to focus the user on issues that require their attention.

 

Today analytics technology has evolved to a point where it adapts to the needs of employees and customers, instead of users being forced to adopt traditional approaches.

 

To get a deeper understanding of where data and analytics is headed in the future, please join us at the Gartner Data & Analytics Summit 2019, 10 - 11 June, Mumbai.

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