The Data Roundtable
A community of data management experts
When you spend long enough writing and working in any industry, you inevitably see trends emerge and reach varying levels of maturity. Data governance is one such trend, as you can see from the following Google Trends chart:
.@philsimon lists the gravest data-quality errors.
I've been doing some investigation into Apache Spark, and I'm particularly intrigued by the concept of the resilient distributed dataset, or RDD. According to the Apache Spark website, an RDD is “a fault-tolerant collection of elements that can be operated on in parallel.” Two aspects of the RDD are particularly
Data quality has always been relative and variable, meaning data quality is relative to a particular business use and can vary by user. Data of sufficient quality for one business use may be insufficient for other business uses, and data considered good by one user may be considered bad by others.
I recently presented a webinar (via the IAIDQ) on the topic of 7 Habits of Effective Data Quality Leaders. To prepare, I looked back at the many interviews of leading data quality practitioners I had undertaken over the years. A common trait among all these interviews stood out – they
.@philsimon chimes in on this pivotal question.