What news from AWS re:Invent last week will have the most impact on you?
Amazon Q, an AI chatbot for explaining how AWS works.
Super-fast S3 Express storage.
New Graviton 4 processor instances.
Emily Freeman leaving AWS.
I don't use AWS, so none of this will affect me.

How to Cut through the Noise with Decision Intelligence

Decision intelligence tests millions (or billions) of features and columns in cloud-scale data to deliver statistically significant, relevant information.
Sep 15th, 2022 9:19am by
Featued image for: How to Cut through the Noise with Decision Intelligence
Image via Pixabay.

We have a data distraction problem. Companies have access to more data than ever before, yet it’s nearly impossible to focus through the noise and use the data to its full potential. While the data industry’s transformation over the past decade is indisputable, the way organizations make decisions with data has barely improved.

According to Seagate, 68% of enterprise data goes unused, and I’ve personally heard larger enterprises claim figures closer to 90%. Even organizations that have invested heavily in a modern data stack are still performing manual analysis on their cloud-scale data — often getting lost digging through a giant haystack while also incurring mistakes and missing insights.

This state of affairs is a disservice to analysts, executives, customers, and of course, companies’ bottom lines. With the ever-growing volume and richness of data, business reviews and workflows should be backed by data. Yet this gap continues to grow because what worked before doesn’t work today and won’t work tomorrow.

So how do we cut through distraction to put data to business use?

Today, accurately and comprehensively analyzing all relevant data is a machine-scale task. There’s simply too much data for humans to effectively analyze and focus on what truly matters.

This doesn’t mean there isn’t a place for humans in the decision-making process. On the contrary, decisions are better with humans in the loop. Individuals are intuitive, creative and bring historical business context to the table. However, advanced technologies such as machine learning are scalable, literal and unbiased. Machine learning can rapidly analyze billions of data points to deliver what’s most relevant to help people focus. And together, machines and people can successfully uncover fast, comprehensive and actionable insights without burning out data teams searching for signals or leaving decision makers to rely on gut instinct alone.

Enter, decision intelligence. While decision intelligence is a new and emerging discipline, it brings together advanced technology and analytical techniques (like artificial intelligence and machine learning) along with decision-making processes to help people make the best decisions. In short, decision intelligence is the sum of technology, process and people.

Decision intelligence transcends business intelligence and augments decision-making processes by recognizing both humans and technology as equally critical elements in the equation. By elevating existing tools and processes, decision intelligence comprehensively tests millions (or billions) of features and columns in cloud-scale datasets to deliver statistically significant, relevant information at machine speed and, in turn, mitigate data distraction.

In the next five to 10 years, the standards of business management will evolve, and it’s critical that the modern data stack follows. Integrating decision intelligence into your tech stack supercharges your analysts, improves your results and puts your data to work.

Group Created with Sketch.
TNS owner Insight Partners is an investor in: Pragma.
THE NEW STACK UPDATE A newsletter digest of the week’s most important stories & analyses.