EI-SUITE is our suite of software tools that enables an enterprise to become EI compliant. The toolset is developed to bridge existing gaps preventing proper sharing of spatial and temporal Geo- and Environmental data in between staff in large companies, private-to-private companies as well as public-to-private companies.
The toolset is thought to contain ALL relevant information between the business and IT where both parties have their own points of entry to the same information. The toolset is NOT intended to replace existing tools for data gathering and data presentation.
EI-CORE is the foundation for the entire Environmental Intelligence Solution. It is a “Master Data Integrator” containing all relevant information about data flows and requests from the business to IT. Before this information was scattered around multiple software applications, in word documents, Excels, e-mails or not documented at all. This also made the solution difficult to scale and even more difficult to move to another platform.
EI-CORE is optimized to support the user groups normally present in large companies working with spatial and temporal Geo and Environmental data.
Examples of information that can be managed, tracked and documented within EI-CORE include:
- Origin of source data
- Data capture method
- Data update frequency
- Domain Expert groups
- Standards Library
- Analysis ready data structures for any relevant subject areas (Dimensional Models)
- Transformations from source data to high valuable information stored in analysis ready Dimensional Models
- Mappings from Data Warehouse to output Data Marts consisting of high quality information in any form the end user requires.
The EI-EXPLORER displays data from the Enterprise Data Warehouse where data is stored as Dimensional Models. It relies on core concepts from BI (Business Intelligence) and focuses on technical data and the requirements of users in complex organizations such as an engineering company.
Examples of information that can be extracted with EI-EXPLORER include:
- exploration of high quality data
- confirmation of data structures (Dimensional Models)
- insight by non-specialists as to what data is available
- ability to determine what data is missing
- supports the construction of data marts
- historical intelligence
- join and access disparate data from multiple sources