Good analytics rely on good data. EBX helps companies ensure that their business analytics are accurate. Now you can manage the enterprise dimensions and hierarchies used in BI and big data.
Our customers use EBX’s unique hierarchy management capabilities coupled with workflow, versioning and audit trail features to maintain a single, trusted source of analytical master data shared with their data warehouses, big data stores and business intelligence tools.
The goal of business intelligence and big data programs is to provide more timely analysis to help organizations improve their sensemaking, planning and performance evaluation processes.
Support for any type of hierarchy, including balanced, unbalanced, ragged
Derived hierarchies based on relationships in the data model
Explicit hierarchies configured by end users on any existing dimension
Version control to work on past, present and future dimensions and hierarchies
Workflow for change requests and approvals on hierarchies
Interfaces to import and export hierarchies to EDW and big data stores
When looking at the architecture that supports these programs, teams generally understand what most of the parts are for. They recognize that enterprise data warehouses (EDW) or big data platforms, such as Hadoop or Spark, will hold all the data. Business and operational intelligence tools will process that information and deliver the analysis in the form of visualizations, real-time dashboards, reports and drilldowns to business users. Lastly, data integration technologies, such as ETL, will move data from your organization’s systems of record into a data warehouse or big data platform.
However, when it comes to explaining the rationale behind managing enterprise dimensions, attributes and hierarchies, many people are at a loss. The problem is that neglecting the management of enterprise dimensions, attributes and hierarchies will result in erroneous analysis.
With EBX, companies can transform their master and reference data into actionable, conformed dimensions and hierarchies and improve the accuracy and performance of their BI and big data programs.