Multiple data systems are common in an enterprise due to organic growth, M&A or divestiture activities, system upgrades and other key business changes. This dynamic can present significant business information issues as systems often do not communicate or communicate poorly with each other, thereby producing a risk of rampant errors as well misinformation due to improper use of data in systems that do communicate with each other.
This scenario increases an enterprise’s overall data and business risk, as interoperability of data is critical for mitigating costly data quality issues, meeting business agility needs across an organization, and ensuring a true enterprise information delivery model.
Many companies seek to achieve “one source of the truth” for their data—regardless of how many systems are at play—but this concept can be a broken model in large organizations. It is very difficult to apply “single source of the data” in reality because not all data can be, nor should be, syndicated uniformly across all systems . . .
Read the full article here: Do Your Data Systems Speak The Same Language?