More data means more opportunities to discover powerful, actionable insights around customers, internal processes, and the broad market. Unfortunately, legacy IT architectures and approaches can block progressive analytics efforts.
That leaves a lot of room for improvement, and the learning and investment curve for starting in analytics can be steep. However, tending to three core steps will prove immensely helpful on this journey:
• Establishing an organizational foundation
• Mapping the data pipeline
• Transitioning analytics proofs of concept into production