How is AI changing enterprise computing?
More Data Sources than Ever
Ingest rates are increasing by
100x
Higher Performance Demands
GPUs increase data rates by
100x
Sharing Data Across all Stages
Need for secure sharing with
Zero Silos
What are your AI plans?
83%
Of businesses believe AI is a strategic priority
~ Forbes
61%
Of business leaders believe ML and AI are their most important data-driven initiatives.
~ O’Reilly Media
86%
Of firms say AI is becoming a mainstream technology for them
~ PWC
54%
Of CEOs say AI solutions have already improved productivity
~ PWC
PLANS VS REALITY
ONLY
40%
Of AI adopters report suboptimal data practices.
LESS THAN
50%
Make it from pilot to production.
What does successful AI data management require?
Smart
Scaling
Annual data growth is 50%.
~ 90% of AI data is unstructured.
You need scale to handle volume…
and technology to reduce volume
Doing More
with Less
70% of firms want to modernize IT. But budgets are growing by only 10%. The IT skills gap is growing much faster.
You need to process AI data faster…and automate processing itself
Faster Innovation and Results
89% of IT leaders say data silos slow down innovation
You need to integrate all stages of AI data lifecycle… and consolidate mixed data and protocols for faster results
Businesses need solutions that can optimize all stages of the AI data journey
We’re used to seeing these stages for AI data, where parallel file systems are critical and data is largely unstructured.
AI ingest
Capture data from multiple sources. Many-to-one reads.
AI labeling
Identify, classify, and add meaning across interactive data.
AI learning
Provide high-throughput, fast reads across millions of files.
AI inference
Correlate learnings to arrive at optimal decisions.
Home Directories
Interactive file workloads
Containerized Apps
Virtualized file and block workloads
Databases
Low-latency block workloads
Backup / Archive
Fast, scalable NAS
But broad AI adoption adds workloads that rely on non-parallel file systems
Beyond parallel file services, the expansion of AI into Life Sciences, Financial Services and other commercial markets has increased demand for additional workloads.
Demand for advanced enterprise data services – such as integrated data protection and data reduction.
These workloads are using both structured and unstructured data.
But broad AI adoption adds workloads that rely on non-parallel file systems
Beyond parallel file services, the expansion of AI into Life Sciences, Financial Services and other commercial markets has increased demand for additional workloads.
Demand for advanced enterprise data services – such as integrated data protection and data reduction.
These workloads are using both structured and unstructured data.
Home Directories
Interactive file workloads
Containerized Apps
Virtualized file and block workloads
Databases
Low-latency block workloads
Backup / Archive
Fast, scalable NAS
How can WE help you manage AI data?
Collect and access data faster than ever
On-premises and in the cloud.
DDN drives
70%
of the world’s largest supercomputers.
How can WE help you manage AI data?
REMOVE AI DATA MANAGEMENT RISK
Expertise, simplicity, stability at any scale.
"
DDN IS THE DE-fACTO NAME FOR AI STORAGE IN HIGH-PERFORMANCE ENVIRONMENTS
~ Marc Hamilton | Head of Enterprise Computing | NVIDIA
"
How can enterprise DATA services help you manage AI data?
Simplify cross-protocol integration.
NFS and SMB
One DDN system
for NAS and SAN, virtualized and native apps, NVMe and HDD media
Deploy enterprise-grade data services.
Data availability, protection, security
One DDN license
for ALL features – the latest enterprise data services today and in the future
Consolidate more data.
Reduce TCO by up to 80%
One DDN appliance
to run multiprotocol workloads concurrently – without any compromises
How the commercialization
of AI changes data
lifecycle needs
The AI data lifecycle now spans Core to Edge.
All need be optimized and work together simultaneously on shared data services.
- Across multiple stages.
- Each with different workloads.
- And different data types.
- Requiring different protocols.
Protocol
File and block
DATA STATE
Static and Dynamic
Data Collaboration
Batch and Interactive
APP TYPE
Native and Virtualized
IO LOAD
Read and Write Intensive
DDN Solution for Life Sciences Data
Best of High-Performance and Enterprise Data Services
Parallel File System
Enterprise Data Services (file and block)
Power & Scale
CSI Drivers for File and Block
High Capacity NAS
Low-latency Block
Native SMB Support
GPU-Intensive Workloads
Container Storage
Reference Databases
Genomics Data Archive
High Data Rate Instruments
Fast, flexible data movement
THE Complete, Integrated Research and Life Sciences Data Platform
Supports entire data lifecycle.
Each stage and data type
Fast discovery, time-to-market.
Performance at any scale
Higher Productivity.
Faster AI apps, DL workflows
Simplified AI data management
With a single-rack solution that delivers consistent power at multi-petabyte scale and meets critical multiprotocol workload requirements.
- Support for all stages of AI data.
- Linear performance for accelerated computing.
- Integrated backup, archive and DR.
What workloads benefit
from a complete AI data solution?
You can accelerate time-to-market, reduce complexity and enhance data value across multiple workloads.
Keep AI data management simple, smart and strong
ONE
Technology to move AI data between any lifecycle stage.
ONE
Partner for all your AI data requirements.
ONE
Rack to manage your entire data lifecycle.
ONE
Platform architecture for all AI data.
ONE
License for all enterprise features and upgrades.
NONE
Resource impact from data reduction or data security.
NONE
Cost for data protection.
NONE
Cost for integrated 24/7 support.
UNLEASH THE POWER
OF YOUR AI DATA
Speak to a Member of Our Team Today!
