Digital Marketing

How AI is Used for Analytics

It seems like artificial intelligence is everywhere. The average consumer uses all sorts of products and services that employ some type of AI and businesses are turning to AI to meet a number of challenges.

Business analytics is one area where AI is having a massive impact. With an AI-powered BI tool, businesses can now get so much more from the data they have. It isn’t replacing human data analysts, but it is making them faster, more efficient and giving them the ability to work with vast datasets while also helping them to extract more information from the data. 

With AI transforming the world of analytics, businesses need to understand the ways they can benefit from this technology. 

AI and Analytics

As useful as they are, conventional methods for analytics could be time-consuming, tedious and inefficient. Human data scientists would have to spend hours or days processing and inputting data, developing hypotheses to test and then applying various analytics techniques to test those hypotheses.

With AI projects for analytics, you can use machine learning to enhance this process and make it more effective. The AI can be used to automate the processing and entry of data to save time. It can also be trained for pattern recognition and anomaly detection. It can find the trends or events that matter without being explicitly told to look for them. A machine learning program can even test hypotheses faster than human data scientists.

What also helps AI perform better is that it does not come with the biases of a human. A human might only know to look for the trends or events informed by their experience or training. An AI algorithm is going to find all of the meaningful relationships in the data. That means that it might even find insights that a human wouldn’t think to look for. 

Along with that, an AI system can get more granular. As an example, a human might see a drop in sales and look at that as the issue to solve. An AI analytics platform might see a more specific issue like a drop in sales among a specific demographic or in relation to a specific event. 

Examples of AI in Action

As you can see, artificial intelligence has the potential to make analytics teams more effective. They can work with larger datasets, get insights that are more specific and test more hypotheses when they try to find answers to questions. 

What does it all mean when it is applied to business data? The answer to that question all depends on the ways a business intends to use AI for analytics. 

One example is diagnostic analytics. This is a type of analytics that uses data to determine the cause of an event or trend. It can be used to monitor things like revenue, expenses, customer satisfaction, quality control and more. When the system identifies events or trends in the data, it can then perform analysis to answer why the trend or event happened.

Businesses can also use AI-powered analytics for predictive maintenance. With predictive maintenance, the AI is fed data from different sensors in a machine or piece of equipment. It continually analyzes the data to determine when the machine will need different types of maintenance tasks performed. This can save a business money by preventing costly repairs and the breakdown of expensive equipment.

Artificial intelligence can also be used to forecast the need for different materials or products. By analyzing data concerning the inventory and use of different products or materials, the AI can build predictive models. It can then apply those models to current conditions to determine the amounts that will be needed in the future. This can help a business prevent shortfalls in inventory or the high costs that come with ordering too much of a product or material.

AI won’t replace human analysts, but it can make them better at their jobs. As the technology continues to develop, these platforms will only become more powerful, and in some cases, they will be able to run with little to no human intervention.

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