Despite the continued hype surrounding AI adoption, many overlook one of the biggest factors for AI success: data quality.

Data cleansing starts at the point of entry. Inaccurately entered data affects quality and will result in the expense of cleansing later on. So ensure your data is entered correctly at the beginning.

Merge lists even with typos and inconsistent names. Tune the similarity threshold, use a transform table, and audit results ...

There is growing recognition of the importance to pension schemes of having good membership data. Poor quality data can frustrate a scheme’s business plans. It can also increase costs. Anecdotally, ...

There are always two aspects to data quality improvement. Data cleansing is the one-off process of tackling the errors within the database, ensuring retrospective anomalies are automatically located ...

Here's how clean data and an independent finance function can secure a higher exit valuation.

PHILADELPHIA, April 9, 2024 /PRNewswire/ -- Perspecta, the leading provider of provider directories and provider data management for workers' compensation, government, and healthcare, today announced ...

Tools that clean or correct data by getting rid of typos, formatting errors, and unnecessary and expendable data are known as data quality tools. These tools help organizations implement rules, ...

Data cleansing is a process by which a computer program detects, records, and corrects inconsistencies and errors within a collection of data. Image: freshidea/Adobe Stock Data is at the foundation of ...

The message was clear — the data is out there. The competitive advantage will belong to those willing to clean it, interpret ...