What is Data-Driven?

Data-driven decisions are based on the data collected. Data is so valuable that organizations want to leverage it as much as they can. For example, financial institutions look at data such as credit scores and make lending decisions based on this information. Data-Driven decisions are concerned with analyzing the data and making predictions about what will happen next.

What is Data-Informed?

Data-informed decisions are made with a combination of data and intuition. Data-informed decisions rely on a mix of quantitative and qualitative analysis.

For example, let’s say you’re deciding whether or not to purchase a new piece of machinery for your factory. You could conduct an ROI analysis that would quantify the costs related to the machine and its potential benefits to your company. The qualitative aspect would be whether or not people in the company like the machine, what it will do for their productivity, and how it could help them complete their tasks better. Combining these two aspects will give you more information about what decision to make than just relying on one side of the coin.

What is Data-Augmented?

Data augmentation is the process of using data to fill in gaps when you don’t have sufficient information. Data augmentation can be done manually or with automated software. It’s important to note that while data augmentation helps provide more complete sets of data, it cannot make up for a lack of original data.

Conclusion

Data Manager, Data Product Managers, and Leadership team play a key role in setting the direction for the organization. It’s about leveraging the data you have to make strategic business decisions and focusing on reducing the Data Risk.

The post Data-Driven Vs Data-Informed Vs Data Augmented: What’s the Difference? appeared first on Sagar Nikam.