Nearly one third of business intelligence (BI) professionals spend 50% to 90% of their time cleaning raw data for analytics, according to a survey by Xplenty, which provides a big data integration platform.
The study focused on several areas of the Extract, Transform and Load (ETL) process, including preferences for on-premise or cloud-based services, perceived challenges and the amount of time spent on ETL.
A huge majority (97%) of the 200 BI professionals from the U.S. surveyed in May 2015 said ETL was critical for their business intelligence efforts. About half (51%) said they use on-premise ETL solutions, versus 49% cloud-based. But of those who said they use on-premise ETL tools, 51% said they were “strongly considering” moving all ETL processes to the cloud.
“While many organizations still rely heavily on existing on-premise IT for ETL, the desire to shift to a more cloud-based model has never been stronger,” Yaniv Mor, CEO and co-founder of Xplenty, said in a statement. “Cloud ETL offers a host of benefits over on-premise, from increased agility in resource deployment to reduced costs. As such, the cloud is an increasingly attractive option from both a performance and operational perspective.”
When asked what the biggest challenges were in making data “analytics-ready,” 55% of the respondents said integrating data from different platforms; followed by transforming, cleansing and formatting incoming data (39%); integrating relational and non-relational data (32%); and the sheer volume of data that needs to be managed at any given time (21%).
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