Poor data quality causes many problems for organizations. Thus an entire field of Data Quality Management (DQM) is now an essential branch of Computer Sciences and specializations such as Data Quality Analysts, Data Owners, Data Custodians, and many more.If nobody knows that,it could have disastrouse consequences for the company. Data Quality refers to the methodical approach,
Testing software and data is one of the most crucial steps in any lifecycle of data oriented projects as well as of application development projects. We often hear words such as black-box testing, white-box testing, beta testing, and many others but at the heart of testing, this is not the main concern. In 2020, the
Version 2.7.0 of BiG EVAL focusses on efficiency. We built several features that boost the efficiency within data quality management processes and also in the data test automation.
What do data and teeth have in common? Nothing? Teeth can bite, but data can’t. Teeth sometimes become discolored. But… data? At first glance, the two don‘t have much in common. But, at second glance? At second glance, they are not that different, especially if you consider dental health and data quality.Teeth need maintenance. So
Are your databases piling up with incorrect customer addresses, duplicates, and contradictory values? These are signs of poor data quality. Don’t ignore the signs! Studies show that incorrect data often leads to unpleasant consequences. Software like BIG EVAL can help by finding data errors, monitoring data systems, and keeping data quality high.Data quality can have
AI’s are computer programs that approach human intelligence. Their intelligence is based on large amounts of data and their analysis (algorithms). They learn from experience, respond to new information, and perform tasks.Does the Theory Actually Work in Practice?AI machines are intelligent, but unfortunately, they are not smart enough to recognize whether the information given them
How can we resolve the problem? Easy: use these 5 steps to achieve lasting high data quality.Step 1: Become Aware of the ProblemRecognize how important high data quality is, which problems can result from poor data quality, and how these problems affect us all. Inform and train those who work with you about this issue.Step
Did you know how easy it is to continuously and automatically test your data and maintain a high level of quality? More and more enterprises are concerned with the issue of data quality, but they are finding the control process difficult. This is primarily due to the complexity of the issue, but also a result of
