While data is a valuable asset, it needs to be tuned to the context of the business to be used effectively. Data preparation is a self-service activity that converts disparate, raw, messy data into a clean and consistent view. The process includes searching, cleaning, transforming, organizing and collecting data.
Data preparation accounts for about 80% of the work done by data consumers today, which leaves less time to mine and model curated datasets for business-critical analytics. Many businesses have identified data preparation as a core challenge to deriving value from data, and they are seeking solutions to help speed up the process.
IBM has compiled a holistic portfolio of offerings that use automation to improve and speed data preparation, from the individual stakeholder level to enterprise scale. Continue exploring to find the right scale for you.