The Data Roundtable
A community of data management experts
No one knows for sure who coined the term Big Data. Despite etymological studies, we are still no closer to attributing provenance to any one person, or indeed any one period. Some say the term was coined in the '80s, others believe the '90s – and many are convinced the term originated
Jim Harris discusses perspectives on the question of how much quality big data really needs.
Data quality issues don’t go away just because you have more data. Big data is sometimes considered exempt from the requirement to be integrated, cleansed and standardized. Unfortunately, chances are that the more data you have, the worse its quality will become.
There are many ways to do data integration. Those include: Extract, transform and load (ETL) – which moves and transforms data (with some redundancy) from a source to a target. While ETL can be implemented (somewhat) in real time, it is usually executed at intervals (15 minutes, 30 minutes, 1
Jim Harris addresses some of the most common questions and challenges big data poses for data quality.
.@philsimon on bridging the IT-business divide once and for all.