Multi-User Support (named login)
Named model access means that users have access based on name and password.
Cat avg: 9.4
Top Performing Features
Single Sign-On (SSO)
Allows users to use one set of login credentials to access multiple applications
Cat avg: 9.4
Data Warehouse Management
The effectiveness of the product’s tools for loading, transforming, sharing, and exploring data, schemas, and dependencies.
Cat avg: 9.2
Data model creation
Ability to create and maintain data models using a graphical tool to define relationships between data
Cat avg: 8.3
Worst Performing Features
Visualization
The product’s support and tooling for analysis and visualization of data.
Cat avg: 5.1
Self-Optimization
The product’s capability to monitor and adjust internal metrics and systems to keep performance as high as possible.
Cat avg: 6.6
Location-Based Data Governance
Refers to how well the software enables users to comply with data privacy standards regarding the use of precise location data for customers.
Cat avg: 6.8
SAP BW Features from Reviews
Access Control and Security
Access control means being able to determine who has access to which data.
8.5-4%
Multi-User Support (named login)
Named model access means that users have access based on name and password.
Category average: 9.4
Multiple Access Permission Levels (Create, Read, Delete)
Multiple access permission levels means that different levels of users have different rights.
Category average: 8.9
Single Sign-On (SSO)
Allows users to use one set of login credentials to access multiple applications
Category average: 9.4
Location-Based Data Governance
Refers to how well the software enables users to comply with data privacy standards regarding the use of precise location data for customers.
Category average: 6.8
Data Modeling
A data model is a diagram or flowchart that illustrates the relationships between data
8.7+5%
Data model creation
Ability to create and maintain data models using a graphical tool to define relationships between data
Category average: 8.3
Data Warehouse
A data warehouse is usually a relational database, designed specifically for data analysis instead of standard transactional processing
7.5-5%
High-Volume Data Processing
The product's ability to efficiently process large amounts of data.
Category average: 8.6
Data Warehouse Management
The effectiveness of the product’s tools for loading, transforming, sharing, and exploring data, schemas, and dependencies.
Category average: 9.2
Administrative Automation
The product’s capacity to automate administrative tasks such as patching, scaling, and creating backups.
Category average: 6.9
Self-Optimization
The product’s capability to monitor and adjust internal metrics and systems to keep performance as high as possible.
Category average: 6.6
Data Exploration
Ability to explore data and develop insights
5.4+6%
Visualization
The product’s support and tooling for analysis and visualization of data.
Category average: 5.1