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 McNamara 是 NetApp 產品和解決方案行銷的資深主管，在資料管理和雲端儲存行銷領域擁有超過 25 年的豐富經驗。在十年前加入 NetApp 之前，Mike 曾任職於 Adaptec、Dell EMC 和 HPE 等公司。Mike 是推出第一方雲端儲存產品和業界第一款雲端連線 AI/ML 解決方案 (NetApp)、統一化橫向擴充和混合雲儲存系統與軟體 (NetApp)、iSCSI 和 SAS 儲存系統與軟體 (Adaptec)，以及光纖通道儲存系統 (EMC CLARiiON) 的重要團隊領導者。此外他曾經擔任「光纖通道產業協會 (Fibre Channel Industry Association，FCIA)」的行銷主席，也是乙太網路技術高峰會議顧問委員會、乙太網路聯盟的成員，現在仍定期為業界期刊撰稿，並經常擔任活動講師。Mike 還透過 FriesenPress 出版了一本名為《橫向擴充儲存設備 - 企業資料管理的未來樣貌》的書籍，並被 Kapos 列為值得關注的 50 名 B2B 產品行銷人員。查看 Mike McNamara 的所有文章

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