With rise of AI, new report uncovers
widespread data problems for US enterprises due to exorbitant
running costs and frequent compromises that see 98% of companies
experience project failure
NEW
YORK, Aug. 5, 2024 /PRNewswire/ -- In its
2024 State of Big Data Analytics Report, SQream sheds light on the
growing disconnect for enterprises between the cost of analytic
projects and the operational value being realized, highlighting the
pressing need to change how companies handle huge volumes of data
to reduce 'bill shock' and avoid the risk of project failures.
The advent of cloud computing combined with recent advances in
generative AI has placed data analytics and powerful business
insights in reach for large enterprise organizations. Yet these two
tech trends are also responsible for producing massive and
ever-increasing volumes of data, causing IT costs to exponentially
increase at an unsustainable and unprecedented rate.
To get to the crux of why data analytics are draining enterprise
budgets and how to change this, SQream surveyed 300 senior data
management professionals from US companies with at least $5M+
annual spend on cloud and infrastructure. Despite the already
substantial budgets at play, 98% of these companies still
experienced ML project failures in 2023.
Adding more compute power has in the past been the go-to way to
yield better AI results. However, SQream's survey highlights that
doing so indefinitely is an untenable approach for modern,
data-driven enterprises, with the complexity of queries and volume
of projects being compromised due to skyrocketing bills and IT
costs.
"This survey underscores the widespread nature of these data
management challenges for large enterprises," said Deborah Leff, Chief Revenue Officer of SQream.
"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."
The State of Big Data Analytics Report includes a range of
detailed insights and findings for team leaders, innovation
executives and data-oriented professionals, including:
- Most organizations experience analytics "bill shock":
Although billing cycles vary from company to company, when asked
how often they experience bill shock, 71% of respondents (more than
2 out of 3 companies) reported they are surprised by the high costs
of their cloud analytics bill fairly frequently, with 5%
experiencing bill shock monthly, 25% bimonthly and 41%
quarterly.
- 41% of companies report high costs as the leading
challenge: As with data analytics, the cost-performance of ML
projects is key to successful business predictions. However, given
that in ML the more experimentation a company conducts, the better
the final result – it is no surprise that 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 (29%), which is consistent with findings
throughout the report. In addition to cost concerns, the other top
contributing factors to project failures were poor data preparation
(19%) and poor data cleansing (19%).
- 3 out of 4 executives are looking to add more GPUs in
2024: 75% of those 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.
- 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 – especially in relation to
cloud resources and compute loads. 92% of companies are actively
working to "rightsize" cloud spend on analytics.
"To get ahead in the competitive future of AI, enterprises need
to ensure that more big data projects reach the finish line.
Constant compromising, including on the size of data sets and
complexity of queries, is a huge risk factor that corporate leaders
need to address in order to effectively deliver on strategic
goals," said Matan Libis, VP Product
at SQream.
The State of Big Data Analytics Report is available for download
here.
About SQream
SQream specializes in data processing and
analytics acceleration, revolutionizing the way organizations
approach big data analytics and AI/ML workloads with its unique
GPU-patented SQL engine. SQream's solutions are designed to meet
the needs of enterprises grappling with massive or complex
datasets, offering unparalleled performance, scalability, and
cost-efficiency. Tailored for industries ranging from finance to
telecommunications, SQream empowers businesses to unlock actionable
insights from their data with unprecedented speed and
efficiency.
Contact
Global Media Contact:
Name: Conrad Egusa
Phone: +1 203-293-8941
Email Address: conrad@publicize.co
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SOURCE SQream