Covering the essentials of business intelligence, explore the features & functions for an overview.
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Data aggregation or consolidation for more accurate reporting and analytics is essential as businesses have adapted a multitude of specialized business applications to stay competitive, and these applications can be home grown, 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.
Data governance at an organization’s macro level, involves users authentication by single sign on and user authorizations are provisioned by individual business applications. Orbit access controls allow user permissions to application 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 on user roles restricting the user from accessing certain data. Orbit empowers 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 automodeler is a self-service ability for business users to create agile data by mash 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 the context of reporting and analytics, data models promote data stewardship and give the most lineage in terms of empowering business users, also enforcing data security in the process. Additionally, data models help in reducing maintenance efforts, increasing data lineage, and ensures data consistency by the abstraction of complex formulas across domains. All of this put together empowers the business user to build the reports they need. Orbit’s sophisticated metadata layering design allows organizations to centrally enforce governance and from an IT point of view, it is a lot easier to maintain a common Semantic Layer than to maintain thousands of individual reports.
In today’s enterprise landscape, it is rare to find all the data in one database. With disparate data sources, internal and external to organization the need to execute SQL queries across relational and non-relational data sources and produce a mashing resultset is a capability has been proven important. For example, a query federates when we have two different data sources, an oracle database table and mssql server database table as part of a desired resultset.
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 it is data stored, they care about a single trusted view presented for consumption. For example complex calculations like commissions can be abstracted to avoid mistakes.
You need to collect data from multiple sources so that you can make well-informed business decisions. You have all of the sources in front of you but no way to connect them. You need a way to extract the data, transform the data, and load the data. Without doing that, you won’t be able to access critical data and make the best decisions for your business.
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.
