Business Benefits of AI-Powered Analytics

by Julie Davis | Guest Contributor | BUSINESS, DIGITAL MARKETING

With datasets that can surpass trillions of bytes, data scientists need specialized tools if they are going to extract meaning from the data. With datasets this vast, just the work of processing it could take weeks for humans. This is one of the ways AI can improve business analytics.

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Modern businesses have access to a wealth of data. The volumes of data are so vast, that traditional analytics practices can’t keep up. This is causing a shift toward AI-powered analytics.
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Using an AI-powered BI tool can open up a lot of opportunities for businesses. An AI-powered platform can handle and analyze data faster than a human, and it can do the work with greater accuracy. These tools are also helping to make data analytics more accessible to more people.

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So what can AI do with business data? What benefits can businesses expect when they use AI-powered analytics tools?

The Benefits of AI-Powered Analytics
With datasets that can surpass trillions of bytes, data scientists need specialized tools if they are going to extract meaning from the data. With datasets this vast, just the work of processing it could take weeks for humans. 

This is one of the ways AI can improve business analytics. Using machine learning, AI-powered platforms can be trained to process the data. These platforms can connect with a variety of different sources to extract the data, process it and unify it into one dataset. On its own, this could save a business a considerable amount of time and money.

Another benefit is access to real-time insights. When you have data being processed in real-time by the platform, you can get insights that are more current. Instead of having to wait for all the time-consuming work to be done, the AI platform can have the data ready almost instantly. That means it can provide insights that are more relevant to the current state of the business.

Many of these platforms also work with Natural Language Processing (NLP). This allows the platform to understand human language. Instead of having to use code to create queries, you can ask a question in a way that is more like speaking to a human. Many of the platforms can even provide feedback in human language. This can make data analytics easy to understand for people who are not data scientists. 

Some AI-powered analytics tools can also work with unstructured and semi-structured data. That means they can analyze data from pictures, text documents, videos, invoices and more. This type of data could not be used by traditional analytics tools or it would take hours upon hours of human labor for it to be categorized and structured for use in the system.

Predictive Analytics 
Beyond real-time insights and analysis that looks at the past, AI-powered analytics tools can offer predictive analytics for a look at the future. Using data about the past and statistical modeling, these tools can look at current data to provide forecasting for the future.

As an example, an AI-analytics tool might be able to predict future sales based on models of past customer behavior. This could help an organization with inventory management or marketing. Some analytics platforms could also predict things like which leads are the most promising, the effectiveness of marketing strategies, needs for different materials, the impact of different organizational changes and more.

Many of these analytics tools can even help business leaders make better decisions by offering prescriptive analytics. With prescriptive analytics, the AI will build models to forecast the outcomes of different decisions that might be made. It will then run the decisions through the models to forecast the outcomes. Many of them can even work through an entire decision tree to forecast the results of a series of decisions that might be made.
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Artificial intelligence can help businesses unlock the full power of the data they have. It can automate data processing tasks and take much of the work out of analytics. This can help businesses make data-driven decisions while also saving time and money. Along with that, it makes it possible to put the power of analytics in the hands of more people.

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