Data is distributed across various source systems in companies. If this data is relevant for systems or users outside the respective source system, but not accessible, this is referred to as data silos. This typically prevents further use of the data outside the source system. Cross-system analysis, overviews oriented to processes rather than systems, operational tasks that require data from different sources - use cases like these are blocked by data silos or require tedious, manual activities and evaluations. Learn more about data silos in our article: "DATASILOS - an underestimated risk for your company?"
This is where Sherlock's data integration comes into play. Using Sherlock's integration hub, source systems are easily connected, converted from the source format into a neutral format, and linked with data stored in other systems using linking rules. This way, data is not only made usable outside of the source system, but is enriched into valuable information by linking it in an information network. Use this approach to make existing data available to new target groups and use cases.
Easily map the process of data management with Sherlock, from data architecture and data modeling, to data integration and data storage, to testing and ensuring data quality and data governance.
Data integration and data management are key to success. Learn how the Sherlock information platform simplifies your data management.
RAB - Related topics (references):
- Intelligent Information
- Information management and digitalization