The Relationship Between Artificial Intelligence and Data Quality

Artificial Intelligence (AI for short) is a groundbreaking, fast-evolving technology that’s already changing industries. However, it’s still only accomplishing a small fraction of what we imagine we can do with it. The use of AI in business is increasing, and organizations are finding new ways to implement this technology to improve their bottom line. But what’s the critical component of this rising AI trend?

Unsurprisingly, it’s data. Data is the one aspect businesses rely on most nowadays, and it will have a significant role in the implementation of new technologies. When it comes to defining the relationship between Artificial Intelligence and data quality, there are a few important things to note. Let’s have a look at how data quality affects AI:

The Relationship Between Artificial Intelligence and Data Quality
The use of AI in business is increasing & organizations are finding new ways to implement this technology to improve their bottom line. AI needs CLEAN_Data

Data Is the Main Element in Powering AI

Artificial Intelligence systems are impressive, reminding people that the future is fast approaching. Be it as it may, our elaborate and sophisticated AI wouldn’t have anything to work with without data. It’s the central element in powering AI, allowing it to perform the necessary operations (like data analysis) that make it useful to us. When we want to add intelligence to a system, one of the first things to do is gather data that it could use — but it has to be the right data, in sufficient quantities.


Dirty Data Can Be a Problem

What happens in an AI system when using improper data? It’s simple, and in some ways, much like it is with humans: without the proper information, we can’t reach the right conclusions. An AI system working with so-called dirty data is not likely to be efficient. Dirty data is a problem because organizations that haven’t been gathering and analyzing correctly have their data kept in different formats, scattered across all of their systems. Unnecessary time and resources would have to be used for a team of trained human data scientists to make sense of the data being kept like that.


Solutions that Collect and Keep Data Clean

To make proper use of AI, organizations need to find a solution that will help them gather clean and accurate data. These solutions would ideally be integrated into their existing data gathering systems so that all of the required information is present in the same place.

One such solution is Runner EDQ’s CLEAN_Data, which is a software integration into your existing enterprise systems that automatically collect and cleanses data. The range of data quality services and solutions Runner offers can help an organization get their databases in order, giving them a clean slate to start implementing AI that would work with this data.

Artificial Intelligence is poised to take over the business world, and organizations should be ready to embrace it and use it to its full potential. That’s impossible to do without quality data, so ensuring that you’re using a quality solution to keep your data accurate and clean is going to help your business’ bottom line.