5 2022 IT Leaders in the Data Fusion/Analytics Domain Survey Report 1 2 3 Key Findings The growing volume of data is a huge industry challenge On average, organizations that investigate using data fusion rely on 6 different data sources, but even when we spoke to those with between 2 and 4 data sources, 54% struggle with managing unstructured text records, a problem that ranks as companies’ fourth greatest challenge overall. Top of the list of organizational challenges is sheer data volume, and 62% of CIOs consider this their main data fusion challenge for investigation purposes. Machine Learning is in action or on the roadmap for 88% of organizations There is a widespread understanding of the power of machine learning analytics to generate investigative insights from data investigation, perhaps linked to handling the data volume challenge, which is getting increasingly difficult to address manually. 66% of respondents say they already use Machine Learning, and an additional 22% report that it’s in their plans. This leaves just 12% who have no plans to implement Machine Learning in their data investigation processes. Organizations demand flexibility, with 77% of organizations reporting making regular changes to data analytics platforms One of the most important features of a data fusion and analytics platform is the ability to make changes on the fly. The industry is fast-moving, and each case has its own specific needs. Less than a quarter (23%) of respondents say they almost never make changes to their analytics capabilities, with the rest relying on an agile and flexible platform in order to work more efficiently and close cases faster. A move towards agility and customization may also explain why 60% of respondents have either migrated, or have upcoming plans to migrate, to a secure government cloud service.