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The Problem with Poor Data Quality

45% of data analysis teams are measured on the quality of the metrics they provide.

Yet, since 2016 more than 80% of CEOs are concerned about the data’s quality they make their decisions on.

1. Immediately identify where the missing data is to quicken the investigation process and solve the issue.

2. Know exactly where to go to find the data and save time and company resources.

3. Seamlessly integrate with over dozens of cloud and on-premise data sets within minutes to determine where missing data could be.

Enter Outlier.What if you could easily and automatically:

Overall, poor data quality is bad for business and has a significant cost as it relates to time and effort.

What Data Problems Are Organizations Facing?

Did you know that poor data quality costs businesses at least 30% of revenues?

Organizations who have made data and analytics a top investment priority, still have little confidence in their company’s data, including it’s

Benefits of Quality Data:

Accuracy Integrity Consistency

- More confidence in your decsion making with full data: Only 16% of companies characterize the data they are using as “very good.”

- More productivity: Employees waste up to 50% of their time dealing with mundane data quality tasks.

- Better program optimization: Every year, 25-30% of data becomes inaccurate leading to less effective programs.

91% of businesses suffer

from data errors

Sadly, humans are to blame for the most amount of

data errors

$ $$$ $ $ $ $ $ $

The financial impact of poor data quality is $15 million per year.