Developing a data quality framework is reminiscent of herding cats. You have to bring together disparate groups to establish a set of standards to maintain data quality, when these groups don’t...
Data quality is crucial, though there are few industries in which it’s a life-or-death issue. The healthcare field is a notable one – a missing value, an additional value, or the wrong value...
Your data is only valuable if its quality is high. The best way to achieve high data quality is through data profiling. Yet, what is the most effective (as well as cost-effective) way to carry out...
Change data capture is a necessity. In order to ensure that the changes you’ve made over time in one data set are automatically transferred to a second data set, you must ensure that change data...
Streaming data pipelines enable companies to process large amounts of information from a wide variety of sources across the enterprise. However, these pipelines are still a recent innovation for many...
In the past decade, big data has made headlines for its ability to provide answers to crucial questions. However, what these stories tend not to focus on is that big data is only useful when you have...
Snowflake has garnered attention for its architecture which allows for the separation of storage and compute which allows each piece to scale individually. In turn, it helps people share data in real...
Gartner reports that integration work accounts for half of the time and cost of building a functioning digital platform. Why does data integration take up so much time and money? There are several...
Raise your hand if this situation sounds familiar: you need to make a decision right away based on the most accurate, up-to-date information. However, the information resides in a number of different...
