- Seven in 10 data and analytics leaders say end users rely on old or error-prone data to make decisions in the enterprise, according to a report from Fivetran, conducted by Wakefield Research. The survey consulted 300 IT data and analytics leaders.
- C-suite leaders are also unaware that their organization is using faulty data, according to two-thirds of respondents. Eighty-five percent of data leaders say their companies lost money due to decisions made with bad data.
- The decision-making process is also slow for the majority of companies, according to the survey. Just 13% of companies can derive value from newly-collected data in minutes or hours, while three-quarters said it can take days or up to a week.
The success of data-driven decisions for the enterprise hinges on data quality and timeliness.
But enterprises contend with vast amounts of data coming from different parts of the organizations. Many large organizations also rely on self-service models, which allow for employees to directly access, compile and gather insights from data.
Organizations struggle to seamlessly connect with data workers, and the mismatch goes all the way up to the C-suite. Nearly half of enterprise chief data officers (CDOs) say expectations on their role are too high and misinformed, Exasol data shows.
Given enterprise growth aspirations for the post-pandemic era, data is an essential component of business strategy. Companies using data management tools are 58% more likely than non-data-driven companies to beat their revenue goals, Forrester found.
Aside from difficulties in leadership and communication, the enterprise is also grappling with data overflow.
More than 90% of data professionals expect the number of data pipelines in their company to increase by the end of the year, according to Ascend.io. Over half say the number of data pipelines in their companies will grow by over 50%.