Minimized hardware costs with persistent memory |
5
10
15
16
22
27
34
37
38
42
46
48
50
53
55%Improved employee productivity |
10
14
19
24
27
31
33
36
38
39
42
43
47
49
50%Improved capacity for innovation |
10
14
19
22
23
25
28
29
32
36
38
40
42
44
45%Reduced technology infrastructure costs |
10
14
19
22
23
25
28
29
32
36
38
42
44
46
47%Improved analytic efficiency |
Process transactions and analytics simultaneously within the same applications (see figure on this page) | |
Combine advanced analytics techniques to extract contextual insights | |
Deliver a unified view through a single logical data model, helping you access all data |
Open interfaces and tools | |
Develop once, deploy everywhere | |
Free for application development |
Data security and advanced privacy protection with real-time anonymization | |
Ubiquitous data access and governance |
Trusted expertise and best practices | |
Tools for developers and business users |
Modern architecture to embrace new technology innovations |
Technology partner ecosystem
Support for persistent memory
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Early technology adoption
Blockchain integration |
App server | Multilanguage and bring your own license |
Application lifecycle management | |||
Predictive and business libraries |
UI5 and SAP Fiori user experience |
Graphic modeler |
On premise, hybrid, and multi-cloud |
Real-time insight to action with embedded analytics enabled by high-performance, in-memory processing | |
Faster, more intelligent business processes augmented with automation and intelligence | |
Increased situational awareness by enriching business data with IoT, spatial, and other forms of data and analyzing it in context | |
Improved business productivity with simpler applications | |
Reduced IT system landscape complexity by supporting both operational and analytical workloads on a single system | |
Significantly decreased data storage needs, lowering total cost of ownership |
Increased business agilityto respond to market forces and pivot business processes |
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Improved customer experiencesthrough personalized interactions and self-service tools |
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Higher business performanceusing intelligent technologies and data assets to meet business goals faster and with less risk |
Real-time insight and predictions on live transactions and historical data | |
Simplified IT landscape – with one platform and less data duplication | |
Faster time to value, thanks to a simplified application architecture | |
Lower total cost of ownership | |
Increased flexibility, supporting deployment on premise or fully managed on any cloud | |
Newly unleashed power of data without breaching trust |
Enhanced abilityto address stadium issues in real time while seizing opportunities to improve the game-day experience |
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Reduced waiting timesfor fans to enter the stadium, using analysis of ticket data and fan movement to direct fans to the appropriate gates |
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Identification of more than 40% of resolved issuesbefore the game, minimizing negative impacts on the fan experience |
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10% increasein fan satisfaction in the first full season after Executive Huddle was deployed |
Increased innovation of new solutions at the speed of business | |
Greater agility, with simpler application and data architectures | |
Faster, simpler enhancement of business processes | |
Enhanced ability to provide the right data to the right person in real time | |
IT resources that can now focus on new solutions, with a single database platform that combines database, advanced analytics, data integration, and application services |
Enhanced abilityto manage customer and sales order data, thanks to a single, powerful, in-memory data platform that handles large data volumes in real time |
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Instant evaluationof each order and whether it can be delivered as promised, with real-time alerts to CSOs |
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Increased ability for CSOsto follow the order-to-cash flow and make more-informed, proactive decisions using a customer service cockpit |
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More time for CSOsto focus on critical tasks and customer communication, enhancing customer service |
Real-time reports with the depth and breadth of information tailored for customers and management | |
Better understanding of purchasing patterns, improving policies and procedures | |
Enhanced insight into sales, demand planning, and supplier-network planning performance | |
Higher productivity, efficiency, and performance of sales reps with full visibility of customer data in real time – even from mobile devices |
Ability to generate reports instantlywith deep, broad information tailored for customers and management |
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Fine-tuned policies and proceduresresulting from a greater understanding of purchasing patterns |
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Increased insightinto trends such as sales, demand planning, and supplier-network planning performance |
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Full visibility of customer datain real time – even from mobile devices – improving employee productivity, efficiency, and performance |
Enhanced ability to plan and predict with confidence | |
Connection of real-time events with business processes, allowing users to take action in the moment | |
Faster identification of emerging threats and opportunities as they happen | |
Increased detection of anomalies, with ability to act in real time | |
Integration of a large volume of historical data with fresh data for advanced analysis |
Increased insightinto animal locations using sensor data analyzed by SAP HANA |
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Ability to track herds,identify when they are near danger, and move them to safer areas |
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130 elephantsrescued through collaring and relocation |
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30 rhinosprotected from dehorning |
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100% reductionin poaching incidents in drone-protected areas |
Automated, improved business decisions made proactively, with confidence, and at scale | |
Enriched customer and employee experiences with automated, optimized business processes | |
Data-driven innovation, supported by machine learning embedded in applications and analytics, whether on premise or in the cloud | |
Simplified IT landscape with one solution and less data duplication for data science needs | |
Accelerated data science lifecycles for faster time to results | |
New insights discovered through applications and analytic solutions |
Created a new type of insuranceto meet the needs of farmers and others affected by climate change and adverse weather conditions |
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Enabled cost-effective pricingand underwriting of index-based weather insurance targeted to clients’ unique weather risks, anywhere in the world |
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Reduced riskto leading weather-sensitive businesses, such as Axereal, one of France’s largest grain cooperatives |
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Realized 12x faster data uploadfor climate change–sensitive insurance |
More data processed, in real time at a lower total cost of ownership | |
Real-time decisions and the ability to take action in the moment | |
Increased cloud-vendor choice, with a multi-cloud and hybrid database platform | |
Accelerated innovation through a simplified IT landscape | |
Reduced redundancy and simplified data management | |
Single entry point for all data |
Migration to the cloudcompleted in less than 24 hours |
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3x to 240ximprovement in query performance |
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Instant provisioning of Amazon Web Services instanceswith scaling on demand |
Faster, more predictable system performance by spreading workloads across on-premise and cloud systems | |
Reduced TCO and increased flexibility by paying for peak performance only when needed | |
Enhanced innovation by exploring new possibilities in the cloud instead of expanding on-premise systems | |
Synchronized data balanced across deployments of SAP HANA in hybrid environments | |
Increased system responsiveness, enhancing the user experience |
Ability to generate reports instantlywith real-time data access from analytics applications |
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Minimized data sprawlby connecting to data sources instead of collecting the data into soon-to-be-stale data marts |
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Simplified landscapeby extending SAP HANA on-premise artifacts into SAP HANA Cloud |
Optimized manufacturing processes and supply chains using intelligent data | |
Ensured availability of supplies, exactly when customers need them | |
Reduced manual effort for ordering and tracking supplies | |
Improved process transparency and reduced operational costs through data orchestration | |
Increased sales revenue using a new, data-driven inventory management solution |
Shortened prediction cyclefrom monthly to weekly, and replaced full-day manual work with just a few clicks |
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Improved forecasting accuracy,optimized the forecasting cycle, and gained the ability to generate five weeks of predictions |
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Shifted toward a strategic approachbased on granular insight |
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Provided more employees and user groupswith access to information on market share |
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Leveraged an architecture blueprintthat can be applied to other analytics use cases |
Reduced production costs from defective goods and wasted materials | |
Increased business continuity with fewer unexpected outages | |
Improved production forecast based on reliable operation of equipment | |
Identification of weak spots in production lines, which allows optimization of equipment sourcing |
Real-timeequipment health and performance monitoring as well as the ability to predict future behavior |
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Sensor-level time-series forecastingthat helps predict a sensor’s behavior over the next 24 hours |
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Strong predictabilityfor abnormal events across groups of equipment |
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Holistic view of equipmentthat provides a better understanding of what triggers events as well as overall decomposition |
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Deep-dive equipment analysisthat reveals hidden patterns and provides insight about how various elements and events affect each other |
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System that learnsfrom its own data so that predictions become more accurate and effective over time |
Holistic view of the supply chain and its dependencies | |
Ability to identify bottlenecks and prepare for alternatives | |
Proactive action taken for outages in single parts before they hit the overall process | |
Business continuity and reliable production by reducing risks to supply chains |
Ability to visualize locations and service areas | |
Capacity to locate materials and capital projects | |
Critical customer identification | |
Faster response, recovery planning, and execution processes | |
Ability to route, navigate, and track |
Quickly process and analyzegeospatial data essential to the customer’s view of performance across miles of pipelines in real time |
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Streamlined operationsthat keep OGE fit to serve its consumers optimally |
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Cloud computingthat slashes the local system maintenance and software update load |
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Clear GIS-enabled analytics,giving stakeholders immediate transparency into pipeline operations with little or no IT intervention |
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Field workersthat have solid guidance in locating pipelines and identifying maintenance and repair needs |
Increased confidence in decision-making at a higher speed | |
Simplified identification of business opportunities and new leads | |
Connected data that allows for in-depth analysis of business networks | |
Improved quality of master data on business partners |
Increased sales revenueby discovering unused sales and up- and cross-selling potential in complex structures |
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Reduced costsby eliminating expensive and time-consuming inquiries, leading to a savings of up to 50% of research costs |
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Gained abilityto avoid high-risk business contracts and penalties due to regulatory violations |
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Boosted strategic decision qualitywith high-quality, trustworthy data combined with graph intelligence and smart algorithms |
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Improved data qualityby validating company structure and the ability to avoid duplicates and cleanse incorrect data |
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Derived new insightsand delivered deep analysis with unique and comprehensive algorithms within SAP HANA |
Maximized business value of sensitive or personal data while protecting the privacy of individuals | |
Enabled new data-centric use cases | |
Unlocked increased value of data by analyzing information that was previously available but not accessible | |
Enabled new business models for data syndication | |
Showed responsibility to customers and users by protecting sensitive and confidential data | |
Enabled machine learning scenarios for analyzing sensitive data | |
Acted as a competitive differentiator for organizations |
Targeted medication and treatmentsto each individual patient |
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Developed a deeper understandingof the relationship between preconditions and reactions to treatment while adhering to data protection laws |
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Created a shareable “database”to fight COVID-19 |
Cost control with lower-cost pricing on lower-volatility data | |
Access to cloud-data-lake data for smart multi-model processing such as machine learning, spatial, graph, and more | |
Enterprise security for data stored in the data lake | |
Centralized data access for governed single instances of valuable data |
Processed position coordinatesfrom the NHL’s puck-tracking system every 30 milliseconds |
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Gave events and insightsreplicated to the Web site and benches every two seconds |
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Enabled instant analysisof archived data, considering 30 GB per game |
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Stored personal informationof 20 million fans protected by a variety of data privacy regulations (for example, GDPR, Personal Information Protection and Electronic Documents Act, and California Consumer Privacy Act) |
Connect your data sources, whether they’re on premise, in the cloud, SAP, or third party | |
Reduced TCO and increased agility through fully managed and scalable services | |
Flexible deployment options so you can extend on-premise investments or move completely to the cloud | |
Reduced complexity thanks to migration tools that remove the need for manual, time-consuming work |
Gained insightsinstantly by analyzing live transactional data |
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Lowered TCOthanks to flexible data tiering options |
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Higher availabilityby migrating to SAP HANA Cloud |
Anonymizes data in real time to protect business data without duplicating it | |
Incorporates SAP application security |
Spatial and graph | Time series | Document store | |||
Text and search | Machine learning | Streaming |