What Customers Are Saying About AI

Mike McNamara
Mike McNamara

The artificial intelligence (AI) survey data discussed in the blog post is based on answers from more than 100 customers at recent AI conferences to gather primary research on AI data management challenges, AI infrastracture and tools, and reasons for choosing different types of data storage.

The majority of survey respondents were software developers (24%), data scientists (18%), researchers (15%), line-of-business owners (7%), data analysts (6%), or general IT (6%). Company size of respondents ranged widely: more than 10,000 employees (45%), fewer than 1,000 employees (28%), 1,000 to 5,000 employees (18%), and 5,000 to 10,000 employees (9%). The top use cases for AI were healthcare and computer-assisted diagnosis, automotive and autonomous vehicles, manufacturing and robotics, and financial services and fraud detection.

The top three storage and data management challenges with AI were scaling storage, cloud integration, and backing up data.

What Customers Are Saying About AI - Inline Image 1The top three requirements when choosing an AI infrastructure vendor were cost, easy to deploy and manage, and services and support offerings.What Customers Are Saying About AI - Inline Image 2The three most common tools used with AI were NoSQL databases, Apache Hadoop, and Splunk. The majority of respondents either use a Hadoop cluster (data lake) with AI or plan to in the near future.

The most common file systems used with AI are HDFS and NFS. Less than 10% of the respondents used ZFS and GPFS.

Cloud storage is the most popular storage used for AI, followed by direct-attached storage (DAS) and then external storage.What Customers Are Saying About AI - Inline Image 3The top reasons for using servers with internal storage or servers with JBOD are performance, cost, and management decision. As shown in the following graph, the top reasons for using external data storage are performance, reliability, and data protection.What Customers Are Saying About AI - Inline Image 4NFS is the protocol of choice for AI with external storage, followed by Fibre Channel and then NFS. Ease of use, easy to scale, cost, and already use cloud for compute are the main reasons for using cloud storage. The most popular services used in the public cloud are Amazon Web Services, Microsoft Azure HDInsight, and Google Cloud Dataproc.What Customers Are Saying About AI - Inline Image 5To learn more about AI and how it’s transforming how business processes are carried out in the digital era, read the “Infrastructure Considerations for AI Data Pipelines” report from IDC. To learn about NetApp® AI solutions, visit www.netapp.com/ai.

Mike McNamara

Mike McNamara

Mike McNamara는 NetApp의 제품 및 솔루션 마케팅 분야의 고위 경영진이며 25년이 넘는 데이터 관리 및 클라우드 스토리지 마케팅 경험을 보유하고 있습니다. 10년 전 NetApp에 입사하기에 앞서, McNamara는 Adaptec, Dell EMC, HPE에서 근무했습니다. McNamara는 자사 클라우드 스토리지 오퍼링 및 업계 최초의 클라우드 연결형 AI/ML 솔루션(NetApp), 유니파이드 스케일아웃 및 하이브리드 클라우드 스토리지 시스템 및 소프트웨어(NetApp), iSCSI 및 SAS 스토리지 시스템 및 소프트웨어(Adaptec), 파이버 채널 스토리지 시스템(EMC CLARiiON)의 출시를 이끈 핵심 팀 리더입니다.McNamara는 Fibre Channel Industry Association에서 마케팅 의장을 역임한 경력 외에도 Ethernet Technology Summit Conference Advisory Board와 Ethernet Alliance에서 회원으로 활동하고 있으며, 업계 저널의 고정 기고자로 활동하며 여러 행사에서 연설을 맡기도 했습니다. McNamara는 또한 FriesenPress에서 'Scale-Out Storage - The Next Frontier in Enterprise Data Management'라는 책을 출간했으며, Kapos가 선정한 눈 여겨 볼 상위 50대 B2B 제품 마케터에 이름을 올렸습니다.Mike McNamara의 모든 게시물 보기

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What Customers Are Saying About AI | NetApp Blog