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Basic operations to support minimal data quality assessment, make life more live-able, and increase the ease and effectiveness for data-science swat-team deployments, all in the large-tabular-data context
path normalization for interop between environments (classify path format by OS and translate to native format)
data type detect: nominal, numeric, date, geo
date detect and format validation
data dictionary vs file matching
data dict normalization plus recovery from multiline cells
metadata: fields search, description search, w support for fuzzy matching
semantic matching
autodetect and application of human-readable lookups present in other tables
flatfile parsing -- all sets
dataset identification and integration
redundant records detection -- large data
lossless data compression
windowing for multitemporal analysis
low memory (large data) sorting, incl. but not limited to: by date!
not require specific install location
allow people to select versions for data
parse and filter largest files bypassing RAM memory limitation restrictions
The text was updated successfully, but these errors were encountered:
Basic operations to support minimal data quality assessment, make life more live-able, and increase the ease and effectiveness for data-science swat-team deployments, all in the large-tabular-data context
The text was updated successfully, but these errors were encountered: