The emergence of big data has created tremendous opportunities for businesses to gain real-time insights and make more informed decisions by leveraging data from the exploding number of digital systems they have in use. However, as often is the case with disruptive technologies, the innovations behind big data have created a critical problem – one that we call data drift. Data drift creates serious challenges for businesses looking to fully harness the insights available from big data.
Data drift is defined as:
The unpredictable, unannounced and unending mutation of data characteristics caused by the operation, maintenance and modernization of the systems that produce the data.
Data drift erodes data fidelity, operational reliability and ultimately the productivity of your data scientists and engineers. It increases your costs, delays your time to analysis, decreases the productivity and agility of your data engineers and leads to poor decision-making by data scientists and the line of business.
Or more details on the causes of data drift as well as potential solutions, read our white paper on data drift.