SAP Business Data Cloud Features
Model Development (5)
Language Support
Supports programming languages such as Java, C, or Python. Supports front-end languages such as HTML, CSS, and JavaScript
Drag and Drop
Offers the ability for developers to drag and drop pieces of code or algorithms when building models
Pre-Built Algorithms
Provides users with pre-built algorithms for simpler model development
Model Training
Supplies large data sets for training individual models
Feature Engineering
Transforms raw data into features that better represent the underlying problem to the predictive models
Machine/Deep Learning Services (6)
Computer Vision
Offers image recognition services
Natural Language Processing
Offers natural language processing services
Natural Language Generation
Offers natural language generation services
Artificial Neural Networks
Offers artificial neural networks for users
Natural Language Understanding
Offers natural language understanding services
Deep Learning
Provides deep learning capabilities
Deployment (15)
Managed Service
Manages the intelligent application for the user, reducing the need of infrastructure
Application
Allows users to insert machine learning into operating applications
Scalability
Provides easily scaled machine learning applications and infrastructure
Language Flexibility
Allows users to input models built in a variety of languages.
Framework Flexibility
Allows users to choose the framework or workbench of their preference.
Versioning
Records versioning as models are iterated upon.
Ease of Deployment
Provides a way to quickly and efficiently deploy machine learning models.
Scalability
Offers a way to scale the use of machine learning models across an enterprise.
On-Premise
Provides On-Premise deployment options.
Cloud
Provides Cloud deployment options (private or public cloud, hybrid cloud).
Language Flexibility
Allows users to input models built in a variety of languages.
Framework Flexibility
Allows users to choose the framework or workbench of their preference.
Versioning
Records versioning as models are iterated upon.
Ease of Deployment
Provides a way to quickly and efficiently deploy machine learning models.
Scalability
Offers a way to scale the use of machine learning models across an enterprise.
Administration (4)
Data Modelling
Tools to (re)structure data in a manner that allows extracting insights quickly and accurately
Recommendations
Analyzes data to find and recommend the highest value customer segmentations.
Workflow Management
Tools to create and adjust workflows to ensure consistency.
Dashboards and Visualizations
Presents information and analytics in a digestible, intuitive, and visually appealing way.
Compliance (4)
Sensitive Data Compliance
Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards.
Training and Guidelines
Provides guidelines or training related to sensitive data compliance requirements,
Policy Enforcement
Allows administrators to set policies for security and data governance
Compliance Monitoring
Monitors data quality and send alerts based on violations or misuse
Data Quality (3)
Data Preparation
Curates collected data for big data analytics solutions to analyze, manipulate, and model
Data Distribution
Facilitates the disseminating of collected big data throughout parallel computing clusters
Data Unification
Compile data from across all systems so that users can view relevant information easily.
Management (16)
Cataloging
Records and organizes all machine learning models that have been deployed across the business.
Monitoring
Tracks the performance and accuracy of machine learning models.
Governing
Provisions users based on authorization to both deploy and iterate upon machine learning models.
Model Registry
Allows users to manage model artifacts and tracks which models are deployed in production.
Cloud Cost Analytics
As reported in 29 SAP Business Data Cloud reviews.
Provide cost management insights and analytics regarding cloud usage.
Cloud Security
29 reviewers of SAP Business Data Cloud have provided feedback on this feature.
Manage vulnerability, access, and protection for multiple clouds.
Cloud Resource Management
Based on 29 SAP Business Data Cloud reviews.
Manually or automatically manage cloud resource usage and scaling.
Cloud Backup and Recovery
29 reviewers of SAP Business Data Cloud have provided feedback on this feature.
Back up cloud resources, and offer recovery capabilities for outages and crashes.
Business Glossary
Lets users build a glossary of business terms, vocabulary and definitions across multiple tools.
Data Discovery
Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources.
Data Profililng
Monitors and cleanses data with the help of business rules and analytical algorithms.
Reporting and Visualization
Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console.
Data Lineage
Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination.
Cataloging
Records and organizes all machine learning models that have been deployed across the business.
Monitoring
Tracks the performance and accuracy of machine learning models.
Governing
Provisions users based on authorization to both deploy and iterate upon machine learning models.
Functionality (3)
Cloud Consolidation
30 reviewers of SAP Business Data Cloud have provided feedback on this feature.
Consolidate viewing and management of multiple clouds in one solution.
Cloud Orchestration
Based on 30 SAP Business Data Cloud reviews.
Provide cloud orchestration for setup, configuration, and management.
Cloud Optimization
This feature was mentioned in 31 SAP Business Data Cloud reviews.
Optimize cloud performance and integration with disparate systems.
System (1)
Data Ingestion & Wrangling
Gives user ability to import a variety of data sources for immediate use
Data Management (6)
Data Integration
Consolidates, Cleanses and Normalizes data from multiple disparate sources.
Data Compression
Helps save storage capacity and improves query performance.
Data Quality
Eliminates data inconsistency and duplications ensuring data integrity.
Built-In Data Analytics
SQL based analytics functions like Time series, pattern matching, geospatial analytics etc.
In-Database Machine Learning
Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc.
Data Lake Analytics
Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS
Integration (3)
AI/ ML Integration
Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities.
BI Tool Integration
Integrates with BI Tools to transform data into Actionable Insights.
Data lake Integration
Provides speed in data processing and capturing unstructured, semi-structured and streaming data.
Performance (1)
Scalability
Manages huge volumes of data, upscale or downscale as per demand.
Security (5)
Data Governance
Policies, procedures and standards to manage and access data.
Data Security
Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion
Access Control
Authenticates and authorizes individuals to access the data they are allowed to see and use.
Roles Management
Helps identify and manage the roles of owners and stewards of data.
Compliance Management
Helps adhere to data privacy regulations and norms.
Maintainence (2)
Data Quality Management
Defines, validates, and monitors business rules to safeguard master data readiness.
Policy Management
Allows users to create and review data policies to make them consistent across the organization.
Operations (3)
Metrics
Control model usage and performance in production
Infrastructure management
Deploy mission-critical ML applications where and when you need them
Collaboration
Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance.
Generative AI (9)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text-to-Image
Provides the ability to generate images from a text prompt.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - Data Science and Machine Learning Platforms (7)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Proactive Assistance
Anticipates needs and offers suggestions without prompting
Decision Making
Makes informed choices based on available data and objectives


