External data integration is a special kind of hard.
New Forrester research reveals that data teams spend just 30% of their time on actual data analysis as the outcry for a solution grows louder.
The business world runs on data, yet organizations spend most of their time cleaning and preparing data rather than using it to make decisions. External data can inform everything from go-to-market strategies to technology investment strategies, and decision-makers are always looking for more.
However, it proves difficult for many in-house data teams to keep up with demand because every external data set is shaped differently and requires significant effort to re-index and integrate with other data sources.
Significant work goes into ingesting, integrating, and preparing new external data sets for analysis and insights extraction. The reality is that organizations spend significantly more time preparing data than analyzing and applying it.
Organizations that want to enable faster time to value with external data sets need to understand the challenges and opportunities facing their data teams. This enables them to make the changes needed to better integrate and prepare new external data sets at scale going forward.