What do you call poor data hygiene? Bad BI? Machine learning is being used to clean up data management protocols. This interesting topic came to us from ZD Net in their article, “The great data science hope: Machine learning can cure your terrible data hygiene.”
Maintaining good data hygiene is tough, especially when you are trying to clean up the past. Enterprises have been creating data dictionaries, metadata and information for years – most of it being clean. This is something humans have a hard time achieving. Without clean data, a data scientist can’t create algorithms or a model for analytics.
Data cleansing removes corruption from records, tables, or databases. In the end there should be consistency with the rest of the data. This quality of data is optimum for decision making and planning.
We have come a long way from data on index cards manually written and filed, but there are still challenges to keeping the data squeaky clean.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
