If your organization depends on data to make decisions, provide services, or tackle problems, it's important to ensure the data will be the highest quality possible. How do you do that, though, when there may be millions or even billions of data points? Data quality monitoring software can automate the process, making it much easier to produce top-notch results.
What sort of issues will data monitoring tools identify and help you address, though? You're likely to find these 5 problems.
People and machines produce duplicate records frequently. Even if you have duplicates because a few customers were impatient while clicking a submit button on a website, it's an issue. Fortunately, data monitoring software can check for both exact matches and close ones. Using statistical methods, the software can compare many fields to determine how likely it is that they represent the same records.
Especially if you have to produce analysis, incompatible data types can be frustrating. A single mistyped entry in millions of rows of data can crash an entire process. Data monitoring tools, however, can scan fields and compare them to others in the set to confirm they'll be compatible. You can then quickly clean the dataset and get on with analyzing the information.
Entry and Scanning Errors
Sometimes the wrong thing ends up in an odd place. Maybe nothing ends up in the entry. People make entry errors, and even automated systems like OCR scanners may mistake one letter for another. It's a common problem that can be hard to hunt down manually, particularly if it happens repeatedly due to smudges or misinterpretations. Data quality monitoring methods, though, can spot out-of-place letters and numbers to avoid including them in finished sets.
Misalignment of Fields
Another common problem is data landing one column off in a table. It's not always easy to correct, especially if only some of the columns are misaligned. You might run into this because a system importing CSV files didn't catch a comma, for example. If you leave the data misaligned, it can mess up output or crash programs.
Sometimes the transformation process creates issues. A company might do daily downloading of JSON files from a government website. If the agency changes how it formats the files, the transformation of the data into the company's preferred format could end up mangled. Data quality monitoring software can use existing data from previous downloads to flag inconsistencies early and avoid issues.
To learn more about data quality monitoring software, contact a supplier near you.