Study Shows Denodo Boosts Data Lakehouse With Higher ROI
KUALA LUMPUR, Sept 25 (Bernama) -- Organisations risked leaving millions of dollars on the table and months-long delays in artificial intelligence (AI) and analytics initiatives by not augmenting their lakehouse investments with a logical data management platform.
Conducted by independent analyst firm Veqtor8, the new study compared the return of investment (ROI) of using the Denodo Platform alongside data lakehouses, such as those provided by Snowflake and Databricks, versus relying on lakehouses alone.
The study found that organisations integrating Denodo with a modern data lakehouse achieved 345 per cent ROI over three years, based on structured stakeholder interviews and industry benchmarks, with cost savings amounting to several million dollars.
In addition, participating organisations received payback in just six and a half months, while also gaining three to four times faster time-to-insight from virtualised data access and a semantic abstraction layer.
In contrast, enterprises attempting to achieve the same outcomes without Denodo were forced into costly custom pipelines, point-to-point integrations, and redundant data governance tools, driving higher engineering effort, longer timelines, and wasted investment.
Denodo senior vice president and chief marketing officer, Ravi Shankar in a statement said the study’s findings are clear that relying on lakehouses alone wastes money and time, jeopardising competitiveness.
“The results show that using Denodo alongside a data lakehouse provides tangible financial benefits that have been realised by Denodo customers,” he said.
To arrive at these findings, Veqtor8 conducted both structured research and in-depth interviews with large companies that use leading data lakehouse platforms both with and without Denodo, quantifying the technical, operational, and financial impact of leveraging Denodo in this configuration.
The report highlights that Denodo enables enterprises to unify governance, simplify data engineering, and deliver AI-ready and business-ready data across silos, without the costly replication and infrastructure delays associated with traditional approaches.
-- BERNAMA