In the public sector, we’ve worked with a lot of jurisdictions with their open data efforts using CKAN, and we’ve seen how data wrangling is a pervasive problem. We see qsv as an integral part of our data pipelines moving forward that will dramatically lower the barrier to publishing high-quality data.

From screening for PII; to slicing data to manageable, logical partitions; to geocoding; to prepping/normalizing time-series data from various IoT vendors; to automatically creating validation schemas and data dictionaries using descriptive statistics – qsv will allow users to compose robust data pipelines with other best-of-breed tools.

In our private sector projects, we also see qsv becoming a useful tool in enterprises standing up Data Management Systems, as CSV is the lingua franca of Data Exchange.