SQream, the New York-based data analytics startup, is releasing this week its State of Big Data Analytics Report, shining a light on the increased costs being incurred by enterprises, and a need to improve the cost-performance ratio of AI projects to generate more value for companies.
The report, in which SQream surveyed 300 senior data management professionals from US companies with at least $5 million in annual spend on cloud and infrastructure, also shows a move towards Graphics Processing Units (GPUs) as a solution to address the surge in data from GenAI, and to get spending under control.
Said Deborah Leff, Chief Revenue Officer of SQream, “This survey underscores the widespread nature of these data management challenges for large enterprises.”
“Leaders are increasingly recognizing the transformative power of GPU acceleration. The immense value of an order-of-magnitude performance leap is simply too valuable to be ignored in the race to become AI-driven,” added the executive.
Below are some of the highlights from the report.
This year 3 in 4 executives are looking to add more GPUs
75% of executives surveyed said that adding GPU instances to their analytics stack will have the most impact on their data analytics and AI/ML goals in 2024. GPUs continue to garner more attention, not only because of the rise of AI and the huge data processing that it requires, and GPUs significantly enhancing speed and efficiency, but because of the vast, and expanding, amount of data that the world produces daily.
Many companies experience analytics “bill shock”
While billing cycles vary from company to company, when asked how often they experience bill shock, 71% of respondents said they are surprised by the high costs of their cloud analytics bill fairly frequently.
41% of companies report high costs as the leading challenge
In the report 41% of companies consider the high costs involved in ML experimentation to be the primary challenge associated with ML and data analytics today.
98% of companies experienced ML project failures in 2023
The top contributing factor to project failures in 2023 was insufficient budget.
Close to half of the respondents admitted they compromise on the complexity of queries
48% of the respondents admitted to having compromised on the complexity of queries in an effort to manage and control analytics costs. 92% of companies are actively working to “rightsize” cloud spend on analytics.
To read the 2024 State of Big Data Analytics: Constant Compromising Is Leading to Suboptimal Results, visit here.
