Can generative AI solve the problem of data overload?

Data is arguably the most valuable asset for businesses today. This means that it is essential that people within the organization are able to work with data and extract insights that (hopefully) lead to better, more informed decisions across the entire organization. ‘organization.

But all this is easier said than done. Because, rather than being empowered by data, many people feel intimidated (or even paralyzed) by it.

How serious is the data overload problem?

In a world full of data – where everything we do generates data – the volume of data available to the average business can become overwhelming. This phenomenon is described by Oracle software leaders as “Decision dilemma“You might also call it “decision paralysis” or “data anxiety.” Whatever you call it, the bottom line is that more data causes anxiety and a lack of action instead. to make better decisions.

For its Decision Dilemma report, Oracle surveyed more than 14,000 employees and business leaders across 17 countries, and the results were revealing:

· 83 percent agree that access to data is essential to help businesses make decisions, BUT…

· 86% said data made them less confident and

· 72 percent said data prevented them from making a decision.

At the same time, three-quarters of business leaders say the daily volume of decisions they have to make has decreased. tenfold over the last three years. More decisions to make, but less confidence in making them despite the masses of data at our disposal? This is a potential crisis for business leaders.

Could generative AI help solve this crisis? Judging by generative AI’s ability to make sense of data and extract useful insights from it – and the fact that generative AI’s capabilities are already built into analytics tools – the answer seems to be yes .

What can generative AI do?

How exactly can generative AI be used to interpret data? Use cases include:

· Promote faster and more effective decision-making through better information: By monitoring data in real time, decision-makers can better understand what is happening in the business and have actionable insights. And this can be achieved through natural language prompts, such as “What are our top three customer behavior trends this month?”

· Act as decision-making co-pilot: Thanks to the conversational capabilities of generative AI, these tools can function as virtual advisors – a sounding board to help discuss and generate ideas.

· Generate data summaries: Generative AI can sift through large amounts of data and create summaries that extract key points, as well as best practice recommendations.

· Data visualization: Generative AI can generate analytics reports in an easy-to-digest format, presenting insights from data not only in textual stories, but also in a visual format (graphs, charts, etc.).

· Automating data analysis: Generative AI can potentially automate the data analysis process and provide automatic notifications for whatever you want. Sales spikes, website activity trends, decreased factory machine performance, increased sick leave, and more.

· Exploit predictive capabilities: In addition to understanding what is happening in the company right awayGenerative AI can help decision-makers anticipate what might happen.

· Use synthetic data to test ideas and scenarios: By creating large amounts of synthetic data that mimic real-world data, leaders can model scenarios that may be difficult to model with real-world data (for example, because an event is a rare but impactful event, or because collecting such a large amount of data would be difficult and expensive).

· Data preparation: Generative AI can also be used to support data preparation tasks such as tagging, classification, segmentation, and anonymization.

· Help clean data for better analysis results: Because generative AI is very good at detecting patterns, it can be used to detect anomalies and inconsistencies in your data that can skew results.

Another benefit is that generative AI can, in theory, work with all kinds of messy and unstructured data, including photo and video data, customer reviews, and social media posts. Which means it is not limited to well-structured data in databases. .

Better yet, these incredible capabilities make data much more actionable for decision-makers across the organization: regardless of their data expertise. So you don’t need to be a data expert to leverage data in your daily work. Decision paralysis, over!

Beware of AI-powered generative tools

Analytics software and platform providers are starting to integrate generative AI features into their tools to enable smarter data analysis. For example, tools such as Microsoft Power BI, Teradata VantageCloud, Tableau AI, and Qlik Cloud now include generative AI capabilities. This typically allows for natural language data querying, simple summaries, custom reports, and more.

We are therefore witnessing a democratization of AI and generative data. This will help level the playing field between large and small businesses, as you will no longer need an army of data scientists to gain a competitive advantage.

We urgently need people to become more confident and competent in using data. I believe generative AI will help realize this vision and solve the problem of data overload, giving everyone the ability to analyze large amounts of data more intuitively. In other words, you just need to ask the right questions!

Learn more about generative AI and its impact in my new book, Generative AI in Practice, 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society.