The data analytics field has been completely transformed over the last two decades, and artificial intelligence is taking on a larger role in analytics every year. With the technology becoming more accessible and affordable, more and more organizations are implementing AI to optimize their approaches to analytics.
In this article, we’ll take a look at three of the most impactful ways in which artificial intelligence is used for data analytics. Don’t forget to look into incredibly useful services such as this ai-powered bi tool that can help you take your analytics strategies to the next level.
Natural Language Interaction
The data science talent gap continues to bottleneck the growth of data analytics, but new approaches to natural language interaction reduce the need for data scientists in certain use cases. These tools allow smaller companies and organizations to leverage AI without breaking the bank.
Natural language interaction, or conversational AI, enables analysts to speak directly to the system in full sentences. While there will always be a demand for data scientists, natural language interaction is moving AI forward by making the technology available to more users.
While basic rules-based AI systems have been around for decades, contemporary automation streamlines the analysis process like never before. Furthermore, automated reports can be created in natural language through natural language generation, making them digestible for experts and non-experts alike.
Automation is another critical element of the movement away from teams of data scientists. With more tasks getting automated than ever, companies don’t need to dedicate the same resources to human analysts.
Unstructured data can be a significant obstacle when Excel and other traditional data analytics tools. While these systems could easily process certain types of information, they struggled with images, audio, text, and other forms of content.
Along with natural language processing for text and speech, modern AI systems also support computer vision for unprecedented video and image analysis. Additionally, data extraction platforms built with deep learning systems can extract the relevant information from a wide range of “semi-structured” inputs like receipts, invoices, and order forms.
With more and more startups pushing AI forward, it’s clear that we’re in the early stages of a large-scale movement toward artificial intelligence. While we’re still only scratching the surface of AI’s potential, these applications are already transforming how analysts interact with all kinds of data.