5 Ways AI Improves Data Quality

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AI provides ease in the world of big data where bad data infiltrates. Learn 5 ways to use AI and machine learning to ensure your data remains high quality.

Modern businesses run on data, but many business functions and teams continue to struggle with ensuring data quality. Inaccurate or unreliable data can lead to wasted time and money, so high-quality information is essential for business success. According to research from Gartner, poor data quality is still one of the top reasons that marketing analytics aren’t reliable for business decisions.

AI techniques help improve the quality of your data. In this article, we’ll cover:

  • Characteristics of data quality
  • How AI improves quality
  • Anomaly detection
  • Identifying duplicate data
  • Streamlining data entry
  • Data standardization
  • Continuously improving data quality standards

What makes data high quality?

You may think a fact is a fact, that any piece of data you’re able to gather is useful. But there’s a lot of bad data out there. This data may be out of date, inaccurate, or incomplete, and won’t do much to help you reach people or make better business decisions.

There are six key characteristics of data quality:

  • Accuracy: Data quality requires that information be error-free.
  • Availability: To be useful, information must be accessible.
  • Completeness: Incomplete data is not accurate data.
  • Relevance: You must use data that’s applicable to the task at hand.
  • Reliability: Is your data contradictory? It must be consistent.
  • Timeliness: Outdated data is one of the most common causes of poor data quality.

When data meets each of these requirements, you can depend on its quality and use it effectively for your campaigns. Your decision making, productivity, and customer reach all depend on accurate and timely information.

So how does AI help you ensure quality?

1. Anomaly detection

One major way that AI improves processes of all kinds is by detecting errors. Machine learning techniques can be used to detect anomalies or defects in a system, knowing how to detect concerning patterns and red flags that indicate data could be bad.

2. Identifying duplicate data

One big problem for organizations is duplicate or redundant data, which can compromise quality and create confusion and ambiguity about the source of truth. AI instantly detects duplicates and filters data based on timestamps and other characteristics. 

3. Streamlining data entry

Businesses no longer have to depend on manual data entry. AI techniques automatically capture and enter data, saving energy on this time-consuming task while ensuring that data is accurate. When data entry is done with automation, there’s much less opportunity for human error, which significantly improves data quality.

4. Data standardization

Another way machine learning impacts data quality is by defining standards and conforming data to that standard. For example, AI can ensure that all stored data does not date back beyond a certain date. Standards and metrics can be applied across an entire data set, so they are implemented consistently.

5. AI continues to improve

One important thing about AI: It’s always improving and changing. For example, the introduction and ubiquity of cloud computing have led to many new AI innovations that better support data analytics. As these technologies continue to improve, their techniques will become commonplace, so data is more accurately gathered, used, and shared. 

According to Gartner, by the end of 2024, 75% of enterprises will move from piloting to operationalizing AI. This will drive a five-times increase in streaming data and analytics infrastructures. It also predicts that 90% of data and analytics innovation will involve public cloud services by 2022.

How BDEX delivers high-quality data

At BDEX, we’re committed to delivering high-quality data in all of our products. The BDEX Identity Graph gives you access to consumer information so you can track them across channels, and our BDEX ID Check is a response to all the bad data we’ve seen over the years. ID Check allows us to detect and filter out bad data, so it never enters our platform. We’re glad to offer the highest-quality data graph on the market.

All of our data solutions have one goal: To foster human connectivity. We know how important it is for you to use quality data to make meaningful impacts on your audiences. We have over 6 billion unique IDs, more than 5,500 data categories, and over a trillion data signals to give you the information you need, right when you need it.

Contact our team of data experts at BDEX to get started with our data marketplace.