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SAP BusinessObjects Business Intelligence from SAP
Scalable analytics platform for insurers enabling big data integration, ad-hoc reporting, interactive dashboards, and predictive analytics for core insurance business processes.
Product analysis by function
Big Data Processing Frameworks for Business Intelligence and Analytics
Distributed computing environments that handle massive volumes of insurance data, including telematics, IoT sensor data, and external information sources.
More Big Data Processing Frameworks
More Business Intelligence and Analytics ...
Data Ingestion and Integration
(6 Yes /7 Known /12 Possible features)
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Multi-source Data Support Ability to ingest and handle data from various sources (telematics, IoT devices, legacy systems, third-party providers). |
SAP BusinessObjects BI supports ingestion from various sources including legacy databases, cloud apps, flat files, and APIs. | |
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Streaming Data Ingestion Support for real-time/near real-time data input, e.g., from IoT sensors or telematics. |
Not as far as we are aware.* Documentation focuses on batch and scheduled data ingestion; limited/no evidence for native streaming data ingestion in core product. | |
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Batch Data Processing Support for scheduled or on-demand batch data loads. |
Batch data loads are a foundation of SAP BusinessObjects scheduled reporting. | |
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Schema Evolution Handling Framework's ability to accommodate changes in data structure over time. |
No information available | |
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Data Deduplication Automated removal of duplicate records during ingestion. |
No information available | |
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Data Validation Checks for data quality and conformity to business rules upon ingestion. |
SAP BusinessObjects supports data validation through ETL integrations and universe modeling. | |
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Connectors and APIs Availability of pre-built connectors and APIs for popular insurance systems and data sources. |
Pre-built connectors for SAP/non-SAP sources and robust API support. | |
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Data Format Compatibility Support for a range of data formats (CSV, JSON, Parquet, Avro, XML, etc). |
Documentation confirms compatibility with major data formats (CSV, Excel, XML, JSON, etc). | |
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Automated Metadata Extraction System can automatically recognize and record metadata for ingested datasets. |
No information available | |
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Change Data Capture (CDC) Identifies and processes only changed data since last run. |
No information available | |
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Data Lineage Tracking Tracks the flow and transformation of data from source to destination. |
No information available | |
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Data Enrichment Ability to augment raw data with external or contextual information during or after ingestion. |
Integrates data enrichment via SAP Data Services and other ETL tools. |
Distributed Processing Architecture
(5 Yes /5 Known /10 Possible features)
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Horizontal Scalability System can increase computing power seamlessly by adding nodes. |
Supports scaling across added server nodes and load balancing. | |
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Elastic Resource Allocation Automatic provisioning or deprovisioning of resources based on workload. |
No information available | |
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Fault Tolerance Built-in mechanisms to continue processing in case of node or task failure. |
Redundant architecture, clustering and built-in failover provided. | |
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Cluster Management Tools Availability of native or integrated solutions for managing compute clusters. |
Cluster management via Central Management Console (CMC). | |
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Distributed Storage Support Integrates with distributed storage systems such as HDFS, S3, Google Cloud Storage, etc. |
Can use distributed storage via integration (e.g. with Hadoop or cloud storage backends). | |
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Geographically Distributed Clusters Capability to manage and process data across data centers/regions. |
No information available | |
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Resource Management Granularity Ability to allocate compute and memory at node, job, or task level. |
No information available | |
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High Availability (HA) Redundant components ensuring uptime in case of failures. |
High availability via redundant nodes, cluster failover, and session persistence. | |
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Throughput Maximum data processing rate. |
No information available | |
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Latency Time taken from job submission to results in distributed environment. |
No information available |
Performance and Scalability
(5 Yes /5 Known /10 Possible features)
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Parallel Processing Support for simultaneous data processing using multiple threads/cores. |
Parallel queries and processing supported through clustered architecture. | |
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In-memory Computation Data and intermediate results can be stored in memory for faster processing. |
No information available | |
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Load Balancing Even distribution of work across all nodes in the cluster. |
Load balancing is a mainstay of SAP BI cluster deployments. | |
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Auto-scaling Automated increase/decrease of resources based on workload fluctuations. |
Auto-scaling possible in cloud deployments or with third-party scaling/provisioning. | |
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Performance Monitoring Real-time tracking of cluster and job-level metrics. |
Performance monitoring provided through CMC and audit dashboards. | |
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Resource Utilization System's ability to maximize CPU, memory, and storage use while processing. |
No information available | |
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Job Throughput Number of jobs or queries processed per time period. |
No information available | |
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Maximum Data Volume The largest dataset size the framework can efficiently manage. |
No information available | |
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Concurrent User Support Number of users or processes that can submit jobs concurrently. |
undefined Concurrent user and job processing is a characteristic of the platform. |
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Query Response Time Average time taken to return results for typical queries. |
No information available |
Data Storage and Management
(6 Yes /6 Known /10 Possible features)
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Support for Hybrid Storage Ability to leverage both local disk and cloud/object storage systems. |
Supports both local and cloud storage as data source and export targets. | |
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Data Partitioning Efficiently splits data into manageable and parallelizable chunks. |
No information available | |
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Compression Support for compressing data to save space and speed up processing. |
Compression supported for exporting data and in some data sources. | |
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Data Retention Policies Configurable rules for automatically archiving or deleting old data. |
Data retention managed via storage integrations and lifecycle tools. | |
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Tiered Storage Management Automatic movement of data across storage types based on usage or age. |
No information available | |
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Metadata Catalog Centralized repository for storing and retrieving data schemas and attributes. |
Metadata centrally stored in universe/catalog, accessible via admin UIs. | |
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Transactional Consistency Support for ACID or eventual consistency as required. |
No information available | |
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Backup and Restore Capabilities for regular data backups and disaster recovery. |
Backup and restore of CMS database, content, and configurations supported and documented. | |
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Role-based Access Control Granular permissions for data access and management. |
Role-based access control administered in CMC. | |
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Immutable Data Storage Ability to store data in a non-modifiable state for compliance. |
No information available |
Security and Compliance
(9 Yes /9 Known /10 Possible features)
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Data Encryption At Rest Encrypts stored data to prevent unauthorized access. |
Encryption at rest supported for underlying database and file stores. | |
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Data Encryption In Transit Protects data using secure transmission protocols (e.g. TLS). |
Data in transit is protected by secure protocols (TLS/SSL) for web interfaces and backend connectivity. | |
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User Authentication and Single Sign-On Supports centralized user authentication and SSO mechanisms. |
Integrates with enterprise SSO solutions and supports SAML, LDAP, and Active Directory. | |
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Granular Access Control Detailed permissions for datasets, jobs, and clusters. |
Granular security configuration for users, objects, and folders documented. | |
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Audit Logging Comprehensive logs of user, job, and data access activity. |
Comprehensive audit logging of access, queries, and job execution available. | |
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GDPR & Other Regulatory Compliance Assists in meeting regulations like HIPAA, GDPR, PCI DSS—especially important in insurance. |
Compliance tools and documentation support GDPR and broader regulatory requirements. | |
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Tokenization and Masking Protects sensitive data fields such as PII. |
SAP BusinessObjects provides options for data masking and redaction through integration with SAP Data Services. | |
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Multi-factor Authentication Extra security step for sensitive operations. |
No information available | |
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Data Access Auditing Detailed tracking of who accessed or queried what data and when. |
Detailed user and data access auditing supported; configurable in admin tools. | |
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Secure API Gateways Controls and monitors API access for data and system operations. |
API management controls available and integration secure via SAP API Management. |
Analytics and Machine Learning Support
(4 Yes /4 Known /10 Possible features)
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Built-in Analytics Libraries Out-of-the-box support for descriptive, diagnostic, and predictive analytics. |
Features descriptive, diagnostic, and predictive analytics through out-of-the-box analytics functions. | |
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Distributed Machine Learning Training Ability to process ML workloads over big, distributed datasets. |
No information available | |
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Model Versioning Track and manage multiple versions and iterations of analytic models. |
No information available | |
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Pipeline Orchestration Automate and schedule end-to-end data science workflows. |
Workflow and data pipeline orchestration available using SAP Data Services integration. | |
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AutoML Capabilities Support for automatic machine learning to optimize model selection and parameters. |
No information available | |
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GPU Acceleration Leverage GPU resources for faster analytics/modeling. |
No information available | |
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Support for R/Python/Scala APIs Code analytic and ML logic using popular data science languages. |
APIs and SDKs for R, Python and more are supported via SAP Predictive Analytics integrations. | |
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Model Deployment at Scale Automated deployment and inference of trained models across production environments. |
No information available | |
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Integration with External ML Platforms Connectors or APIs for TensorFlow, PyTorch, H2O.ai, etc. |
Integration APIs and connectors to external ML platforms are available. | |
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Model Monitoring Continuously tracks model performance and drift in production. |
No information available |
Data Governance and Quality
(1 Yes /1 Known /10 Possible features)
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Data Cataloging Central source to register, discover, and search all datasets. |
No information available | |
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Data Lineage Visualization Visual tracking of data's journey, including transformations and usage. |
No information available | |
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Data Quality Monitoring Automatic scanning for inconsistencies, errors, and anomalies. |
No information available | |
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Policy-based Data Governance Rules that automate governance actions based on policies. |
No information available | |
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Data Stewardship Tools Interfaces and workflows for designated users to resolve or annotate data issues. |
No information available | |
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Data Profiling Automated generation of dataset statistics and summaries. |
No information available | |
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Custom Quality Rules Ability to define and enforce custom data validation checks. |
No information available | |
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Master Data Management Integration Ensures accurate, consistent 'golden records' for all entities. |
No information available | |
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Data Masking and Redaction Built-in capabilities for masking sensitive data. |
Data masking and redaction available via SAP Data Services integrations. | |
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Data Audit Trails Comprehensive records showing when and how datasets were modified. |
No information available |
Interoperability and Extensibility
(10 Yes /10 Known /10 Possible features)
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Open Source Ecosystem Support Ability to use and extend popular open source big data frameworks like Hadoop, Spark, Flink, etc. |
SAP BusinessObjects can leverage and integrate with Hadoop, Spark, and other open source sources. | |
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RESTful API Availability Exposes standardized APIs for integration with other business services or systems. |
Comprehensive RESTful APIs available for integration. | |
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Data Export Easily extract processed/analytic data to other systems or BI tools. |
Supports data and analytics export to other systems and BI tools. | |
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Plugin/Extension Architecture Framework allows custom modules, processors, or logic to be added. |
Custom extension and plugin support available via SDK. | |
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Workflow Integration Connects with ETL/ELT and workflow orchestration tools (e.g., Airflow, NiFi). |
Integrates with ETL/ELT and workflow tools, especially via SAP platforms. | |
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BI & Visualization Integration Connect data output to BI tools like Tableau, Power BI, or Qlik. |
Native integration with popular BI tools and visualization platforms. | |
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Custom Scripting Support Ability to create user-defined functions or scripts for processing tasks. |
Custom scripting possible with user-defined functions for reporting and processing. | |
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Cross-platform Compatibility Runs across different operating systems and hardware. |
Runs on a variety of OS, including Windows and major server UNIX/Linux. | |
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Multiple Language APIs Support for multiple programming languages (Java, Python, Scala, R). |
Multiple programming language APIs supported, such as Java, REST, and scripting. | |
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SDKs and Developer Tools Resources and libraries for developers to build custom solutions. |
Developer SDKs and tools provided for extensibility. |
Deployment and Operations
(8 Yes /8 Known /10 Possible features)
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Cloud-native Deployment Optimized for AWS, Azure, GCP, and/or hybrid/multi-cloud operation. |
Cloud deployments supported on AWS, Azure, Google Cloud, and hybrid. | |
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On-premises Deployment Can be installed and run within an enterprise data center. |
Can be deployed on-premises for enterprise customers. | |
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Containerization Support for Docker/Kubernetes for portability and orchestration. |
Docker/Kubernetes supported as part of SAP's overall cloud strategy. | |
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Rolling Upgrades Ability to update or patch the system without downtime. |
No information available | |
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Automated Provisioning Self-service or automated cluster setup and resource allocation. |
Automated provisioning via installer and/or management APIs for clusters. | |
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Monitoring & Alerting Centralized dashboards; notifications for infrastructure and job health. |
Monitoring and alerting for infrastructure and data jobs via CMC and plugins. | |
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Self-healing Capabilities Automatic detection and remediation of node or service failures. |
No information available | |
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Disaster Recovery Automated failover, backup, and restoration processes. |
Disaster recovery covered in product documentation; includes backup/restore and failover. | |
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Multi-tenancy Support Logical separation and resource isolation for different departments or teams. |
Supports multiple user groups and logical separation for business units/teams. | |
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License/Subscription Management Built-in tools for managing product usage, licensing, and billing. |
Subscription and user license management present in admin interface. |
Usability and User Experience
(8 Yes /8 Known /10 Possible features)
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Visual Workflow Design Drag-and-drop or graphical tools for building data pipelines and transformations. |
Visual pipeline building via tools like SAP Lumira or integration with workflow designers. | |
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Job Scheduling UI Easy interface for scheduling and managing batch/stream analytics jobs. |
No information available | |
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Integrated Documentation Comprehensive, context-sensitive help inside the product. |
Integrated help and documentation available contextually in the application. | |
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Interactive Data Exploration Exploratory analysis tools for ad hoc queries and visualization. |
Interactive ad-hoc querying and dashboard exploration supported. | |
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Template Workflows A library of pre-built workflows and pipelines for common insurance analytics use cases. |
Pre-built templates and accelerators for analytics processes in insurance provided. | |
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Customizable Dashboards Personalized dashboards for monitoring jobs, clusters, and data assets. |
Users can customize dashboards for their activities in SAP BI. | |
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Multi-language Support Localization and internationalization features for global teams. |
Globalization and localization support for multi-language use. | |
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Notebook Integration Support for Jupyter and other data science notebooks for collaborative analytics. |
Notebook-like features not native but integration with Jupyter through SAP Data Intelligence possible. | |
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Role-based User Interfaces Tailored views and permissions based on user type (data engineer, analyst, admin, etc). |
Role-based UIs for admins, analysts, and business users well established. | |
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Mobile Accessibility Access dashboards and reports from smartphones/tablets. |
No information available |
Cost Management and Optimization
(2 Yes /2 Known /10 Possible features)
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Cost Tracking and Reporting Detailed breakdowns of resource usage and costs by user, job, or department. |
No information available | |
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Auto-termination of Idle Resources Releases unused or underutilized resources automatically to save costs. |
Idle resources can be auto-terminated via infrastructure integration (cloud, VM, etc). | |
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Spot/Preemptible Instances Support Leverage lower-cost compute instances for non-critical workloads. |
No information available | |
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Budget Alerts Notifications when budgets approach or exceed defined limits. |
No information available | |
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Usage Quotas Policies to limit maximum resource usage per job/user/project. |
No information available | |
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Resource Usage Forecasting Predicts future costs and resource needs based on job history. |
No information available | |
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Data Storage Tier Optimization Automatically moves rarely accessed data to lower-cost storage. |
SAP and partner solutions enable storage tier optimization for cloud/hybrid deployments. | |
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Chargeback/Showback Reporting Generates reports to allocate technology costs to business units. |
No information available | |
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Automated Scaling Policies User-defined policies to control scaling and associated costs. |
No information available | |
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Cost-aware Scheduling Optimizes job scheduling based on spot/discounted resource pricing. |
No information available |
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