How Artificial Intelligence Allows a “Data-First” Approach to Business Analytics
Artificial intelligence has been on the forefront of the business world over the past few years. For a long time, people have tried to imagine a world where humans interact with intelligent computers. Now it appears this hypothetical future will soon be a reality. Major advances in computing power and algorithmic processes have changed the AI landscape. The results are going to radically alter the world forever.
In the businesses world, AI’s presence will likely be first felt in data collection and analysis. The ubiquity of data today makes it a necessary part of operating a competitive company. This is why it’s estimated 90 percent of large organizations will employ a CDO (Chief Data Officer) by 2019. Here’s how AI will allow a “data-first” approach to business analytics.
Process More Data
Time is the key limiting factor to most things done by human beings. Even if you’re an expert at something, you can only complete a set number of tasks over a given time frame. We as people can’t compress our actions into milliseconds. But this is completely achievable by artificial intelligence. The limiting factors on AI are simply how well it’s designed by its human creators. This is, of course, until AI can actively work to improving its own infrastructure. Network structuring and hardware determine how efficiently AI can gain insights from raw data.
There’s another reason why AI can process more data than its human counterparts. You might go in to work for eight or nine hours every day. That can really wear you down if you’re doing mentally demanding work. On the other hand, AI can work all day and night without breaking a sweat. This allows businesses to scale up their data processing to unprecedented levels. Additionally, as AI improves, it can better analyze more forms of data—such as written documents, photos and audio files. These additional sources of information build a stronger data pool.
Spend Less Time Waiting
Turnaround time is one of the biggest issues with traditional business intelligence. There are a few reasons why it can take a while to get results from traditional BI. First, data usually needs to be collected, which can take a significant amount of time. An analyst will need to locate specific datasets, which are sometimes misplaced or mislabeled.
Additionally, some organizations will have convoluted data storage with many silos and permission gateways. This can add days or weeks to the turnaround on data analysis. Of course, the actual analysis of data can be time consuming depending on the situation. And after all this, there also needs to be extensive work checking to ensure accuracy. Artificial intelligence applications can solve these issues.
Using an AI analytics engine, business users can now click to get AI data intelligence in seconds. This alleviates the need for data scientists to dig deep to uncover insights—like trends and irregularities—manually. The algorithms do the heavy lifting, while humans weigh in with feedback to refine the system for future success.
Get More Accurate Information
Your data analysis isn’t worth much if it’s not correct. Human error can come into play at any step of the process. There might be an issue with the initial data collection. The premise of the analysis could be potentially flawed. Or, someone could make a critical mistake in the compilation process. Much of this can be alleviated by introducing AI into the picture. As long as the AI protocol is correctly designed to handle your specific needs, it shouldn’t run into any accuracy issues. This sort of technology isn’t just for large companies. Soon, data-driven AI tools will be an essential part of businesses of all sizes.
Many people have strong opinions about the future of artificial intelligence. One thing that’s certain is that AI is going to completely change the world of data analysis.
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