Data aggregation or consolidation for accurate reporting and analytics is essential, and businesses have adapted many specialized business applications to stay competitive. These applications can be homegrown, on-premise, or cloud applications.

Orbit data management functions allow business users and data engineers to use the drag-and-drop visual data modeler that’s incredibly easy to use and helps create ad-hoc data mashing models to complex data models. The data models can be further configured for data security and shared across the enterprise to promote self-service data-driven decision-making.

What Sets Orbit Data Management Apart?

Users log in with a single sign-on for data governance at an organization’s macro level, and individual business apps manage their permissions. With Orbit’s access controls, all permissions are managed from one point and users get permission to menu functions based on specific application roles.

Data security is the next layer of access controls, i.e. data security rules can be defined and applied for user roles restricting the user from accessing certain data. Orbit allows users access to data in your ERP and other corporate applications while enforcing data security rules defined in respective business applications.
Datasets is a data catalog feature promoting data stewardship of creating and maintaining trusted, reliable and consistent data. Ad-hoc data mashing auto modeler is a self-service ability for business users to create agile data by mashing corporate data with external datasets that might be in flat files like excel,csv,json,xml or directly accessible as a web service urls.
In reporting and analytics, data models promote data stewardship and give the most lineage in empowering business users and enforcing data security, in the process. Additionally, data models help reduce maintenance efforts while increasing data lineage, and ensure data consistency by the abstraction of complex formulas across domains. All this together empowers the business user to build the reports they need. Orbit’s sophisticated metadata layering design allows organizations to enforce governance centrally. From an IT point of view, it is a lot easier to maintain a common Semantic Layer than thousands of individual reports.
In modern businesses, data is often spread across various databases, both inside and outside the organization. Being able to run SQL queries across different types of data sources (relational and non-relational) and combine the results is crucial. For example, when we need information from both an Oracle database and an MSSQL server, combining them into one result set is called data federation.
Data virtualization is a Data Management technique of hiding the data complexity under the hood. Business users do not need to know all the technical details about data sources, such as where and how data is stored. What they need is a single trusted view presented for consumption. For example, complex calculations like commissions can be abstracted to avoid mistakes.
You need to collect data (extract the data, transform the data, and load the data) from multiple sources so that you can make well-informed business decisions. DataJump is Orbit’s solution for ETL (extract, transform, and load) and ELT (extract, load, and transform) requirements. DataJump gives you the ability to blend data from multiple sources into one single source. DataJump allows you to synthesize data from multiple sources so that you can build a database such as a data hub, data warehouse, or data lake.

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