David Ohnstad of Minnesota works in project management. In the realm of data analytics, a seismic shift is underway, and in the following article, David Ohnstad discusses how the transformative power of Artificial Intelligence (AI) is reshaping how businesses harness and leverage their data.
Data analytics is the cornerstone of business decision-making. Without it, informed choices would be a mere wish. However, the unprecedented growth of data over the past few years has made it near-impossible for humans to continue this colossal task unaided.
Enter artificial intelligence, the technology taking the world by storm. The intricate algorithms behind AI are providing the tools necessary to analyze a vast dataset of information quickly and accurately, giving businesses across the planet sensical information.
The transformative technological advancement is changing the way data is collected, analyses, managed, maintained, and stored, altering the entire field as a result. And it’s happening at a faster-than-imagined pace, with Gartner suggesting the end of 2024 will see 75% of enterprises operationalizing artificial intelligence and exhibiting a five-times increase in analytics infrastructures and information streaming.
David Ohnstad Explains the Revolutionary Impacts
The days of manual data analysis are well and truly over. With AI kicking up a fuss in the data analytics sector for all the right reasons, it’s bringing a wealth of benefits to businesses, entrepreneurs, and industry professionals.
Complex Task Automation
Perhaps one of artificial intelligence’s most prominent advantages in the field is its profound ability to automate complicated tasks. The very nature of the industry involves processing massive amounts of both unstructured and structured data — a time-consuming, tedious task to manually complete.
David Ohnstad of Minnesota explains that AI allows businesses to automate data collection, sorting, and analysis, allowing human analysts to focus on the more strategic factions of the job.
Chatbots, for instance, collect and consider customer feedback, identifying major trends and improvement areas. Not only does this save organizations and professionals time, but also increases the accuracy of analysis by negating the human error element.
Faster, More Accurate Analysis with Predictive Analytics
Speaking of accuracy, predictive analytics (a technique used in the modern data analytics field) uses machine learning algorithms to look at and analyze historical data, detecting patterns that can help predict future outcomes. David Ohnstad notes that as AI continues evolving, it’s enhancing predictive analytics’ capabilities by accelerating the process, even when huge data volumes are present.
With the newfound speed provided by advanced AI-powered data analytics algorithms, large and complex datasets can be analyzed in a matter of moments — an impossibility for human analysts.
David Ohnstad says that the larger scope gives businesses plenty of room to grow; AI will grow right along with them.
Providing Personalized Experiences with Machine Learning
Machine learning, an AI subset allowing machines to learn from data without specific programming, automatically identifies patterns in datasets and makes predictions based on its findings. It’s transforming the field, making it possible to process unfathomable amounts of information without human intervention.
This has proved particularly helpful in the manufacturing industry, where machine learning is used to predict failures before they happen. As such, David Ohnstad of Minnesota reports that manufacturers are now able to schedule maintenance prior to a breakdown, saving time and improving productivity.
Data Analytics AI: A Role Augmenter, Not Replacer
Despite widespread belief, experts are emphasizing the notion that artificial intelligence is a role augmenter, rather than a replacer. Analysts don’t need to worry about the security of their job; AI isn’t meant to eradicate people from the field. It’s there to take over time-consuming, tedious duties, freeing professionals’ time for strategic work.
According to those at the International Institute of Business Analysis, human expertise is remains vital for understanding business context, making crucial decisions, communicating data insights, and ensuring ethical data protocols are followed.
Data Analytics Isn’t the Only Area Undergoing an AI Transformation; Data Quality Management Is Too
David Ohnstad explains that as industry participants can attest, data quality management is a crucial cousin of data analytics. Without it, businesses wouldn’t be able to collect high-quality data. And, like many areas in the space, artificial intelligence is changing things for the better, helping companies improve data quality and guarantee their sets are fit for purpose.
AI-based quality management solutions find and rectify errors (e.g., missing or duplicate information) to minimize the likelihood of entities making decisions based on inaccurate data. Ultimately, this enhances business outcomes across the board.
Artificial Intelligence is Catapulting Data Analytics into the Ever-Digital Future.
David Ohnstad of Minnesota reports that data volumes will continue growing, and it’s AI that will ensure companies can keep up with the non-stop flow.