Covering the essentials of business intelligence, explore the features & functions for an overview.
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Orbit’s data modeling functionality achieves highly-tuned queries by identifying the objects needed from multidimensional data relationships. You can build reports as per your business requirements to get the information that you need – when you need it.
Orbit doesn’t restrict your data sources, so your reports and analytics can span a variety of data architectures.
You can view information from flat files, as well as any database that complies with Java Database Connectivity (JDBC) standards.
Orbit can also mash data from multiple sources – including on-premise, cloud, and proprietary applications. When Orbit aggregates data, its intelligent query generator will include only the tables that users need for analysis.
Orbit’s innovative UI defines semantic layers that use data from your business functions. This advanced data modeling capability, combined with robust IT governance controls, ensures the availability, integrity, and security of your business intelligence applications.
Orbit’s data modeling capabilities find the most efficient path through massive volumes of data. This speeds decision-making while reducing strain on your network.
Orbit’s three-layer architecture to designing data models includes:
Orbit enables users to search, capture, store, reuse, and publish key metadata objects. Through Orbit’s centralized management system, users can easily customize:
Orbit allows you to store your metadata separately from your application databases, making your management easier and more efficient.
Orbit’s OLAP engine manages your complex business requirements. It handles Star Schema and Snowflake queries for the aggregation of dimensional data.
Orbit’s OLAP engine also handles drill down within the cube and into third-party data sources, along with customizable drill down options.
The R Statistics and Python libraries are embedded within Orbit’s BI server. This gives you the ability to create analytical models within the metadata layer, as well as build reports with advanced analytical visualizations.
The City of St. Petersburg wanted a scalable reporting and analytics solution to support the mayor’s Data Transparency initiative. The city’s existing tool was limited in its functionality. They also needed a solution that would integrate with Oracle EBS and their other in-house applications.
The City of St. Petersburg selected Orbit due to its flexible user interface and data visualization options. The city is currently deploying reports and dashboards that will be shared with residents of City of St. Petersburg through its website.