
Building a Framework for Data Quality Management
Data quality management has emerged as an increasingly important factor in determining the success of big data analytics and AI/machine learning initiatives. Even at a purely operational level, the...
Data quality management has emerged as an increasingly important factor in determining the success of big data analytics and AI/machine learning initiatives. Even at a purely operational level, the...
To measure data quality – and track the effectiveness of data quality improvement efforts – you need, well, data. Keep reading for a look at the types of data and metrics that organizations can...
Data quality is crucial – it assesses whether information can serve its purpose in a particular context (such as data analysis, for example). So, how do you determine the quality of a given set of...
By now, you’ve heard how valuable data can be, how it can drive your company forward, how you can use it to make better decisions. There’s a caveat there, of course. Information is only valuable...
Artificial intelligence and advanced analytics will be significant drivers of competitive advantage in the coming decade. The volume of available data has skyrocketed in recent years, made possible...
Data can be your organization’s most valuable asset, but only if it’s data you can trust. When companies work with data that is untrustworthy for any reason, it can result in incorrect...
Data quality is important to business. That you know. But do you understand what it takes to provide data quality We’ll review how data quality problems can arise. Briefly defined, data...
We are all familiar with the old saying “garbage in, garbage out” (or “GIGO” for short). That phrase has been around since the early days of computing, but in this era of high-volume data,...
As more and more enterprises recognize the value of data analytics and data-driven decisions, the challenges associated with poor data quality have been brought to the forefront. As business leaders...