Data lifecycle management (DLM) is becoming increasingly important since the explosion of #bigdata and the ongoing development of the Internet of Things (IoT). Enormous volumes of data are being generated by an ever-increasing number of devices all over the world. Proper oversight of data throughout its life cycle is essential to optimize its usefulness and minimize the potential for errors. This also helps in minimizing the risk of data breaches and prevents critical information from being misused. A recent survey from McKinsey showed that 56% of respondents reported AI data lifecycle as a best-practice approach to preparing data for the AI lifecycle.
