Advanced robots, self-driving cars, automated delivery bots, Internet of Things, and all the other cool and sexy tech we have today all run on some kind of an AI-powered platform. But those platforms only exist because of data. Data analytics is at the heart of AI, business, and the world as a whole today. So, if you want to get ahead, you must wield its immense power for making business decisions. However, the human brain cannot compute such enormous blocks of information. So, you’ll need to use a SaaS analytics platform to do it for you.

How to Use an AI-Powered Platform to Improve Your Decision Making

The best thing about Big Data is that it holds the answers to all your questions. Actually, it can even predict the future if used right. And that means ‘if it’s processed by an AI-powered platform geared toward predictive analysis.’

No business today can survive without data analytics. It’s because you literally can’t make decisions without the insights derived from data. You might only rely on your monthly business reports or go for a broader scope including global economic reports. But the point is that you have to make decisions based on something more concrete than your intuition. It means understanding what types of data analytics exist. And more importantly, how to use them at different stages of decision making.

Types of Data Analytics Performed by an AI-Powered Platform

Descriptive

Descriptive data analytics provides you with answers to the question “What happened?” In essence, you can use this data to understand how your business is doing. Then, depending on how deeply you analyze various processes, you can decide which areas to focus on.

There is no doubt that these insights from a basic AI-powered platform are extremely beneficial. They are especially handy when you need to identify areas where you can cut costs.

That said, descriptive analytics insights are somewhat limited. They only give you information about your past business performance and don’t consider any outside factors affecting it.

Diagnostic

Diagnostic data analytics is used to understand why something happened. Performing this analysis is the logical next step after collecting descriptive data insights. At this point, the AI-powered platform can delve deeper and understand why some of your business decisions failed or succeeded.

Bear in mind that diagnostic analytics will require a wider scope of data than your internal business reports. Also, it will be, at least somewhat, based on conjecture. It’s hardly possible to account for all potential factors that affect any business outcome. Therefore, you’ll have to accept that while highly valuable, these insights are also not absolute.

Predictive

Predictive analytics is far more advanced and requires the implementation of an AI-powered platform. Machine learning, in particular, is the basis of any successful predictive analytics. Insights derived from it allow you to see what is likely to happen shortly. Therefore, you can use them to make decisions that might propel your business forward.

This kind of prediction for future trends is most valuable for businesses that want to grow. However, any forecasts cannot be 100% accurate. There are just too many factors that are beyond your control that affect the outcome. Many of these factors are macroeconomic and volatile.

Bearing that in mind, you should use predictive analytics to develop a proactive approach to business. It can help you plan, especially for the situations that might affect you in the future. Thereby they help your business prepare for potential challenges.

Prescriptive

Prescriptive data analytics is the most advanced type, and it can provide the most valuable insights. At this state, an AI-powered platform will aim to give you guidance on what actions you can take. To get the most value from these insights, you need to have specific questions in mind. Then, analyzing your goals and data will enable the AI to determine the actions necessary to achieve your desired results. These insights are primarily based on the data obtained from predictive, descriptive, and diagnostic analyses.

However, prescriptive analytics will also use technology like simulation analysis to discover solutions to potential or current problems. Of course, these solutions are subject to the same limitations as any predictive analysis. But they are highly valuable as they enable you to reduce risks that are inherent to any business.

Implementing Insights Delivered by an AI-Powered Platform

Studying a real-life example is the best way to understand how an AI-powered platform can benefit your business. Marquètte is a piece of SaaS data analytics software developed by Devtorium and powered by proprietary AI tech. It uses a combination of data analytics methods and technology to conduct a SWOT and PESTEL analysis of any field.

On the user side, this looks like you are conducting a simple internet search. However, in reality, AI goes through huge blocks of data in order to find concrete answers to your questions. So, when it’s done its job, you get a summary that answers your question in detail and includes actionable insights. Then, as a business owner, you can put those into action right away. Thus, you ensure your company derives maximum benefit from the information.

Businesses can use the insights provided by Marquètte to:

• Revamp your brand design for increased impact
• Find new areas for your business to expand in
• Predict challenges your company needs to prepare for
• Adjust your marketing strategy for maximum efficiency
• Answer any industry and niche-specific questions you have
• Forecast business development when planning for the future

As you can see, an AI-powered platform is an invaluable ally for any business. So, the only question is whether you want to use an existing solution, like Marquètte, or to have custom SaaS data analytics software developed for you.