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2022 IT Leaders in the Data Fusion/Analytics Domain Survey Report
Introduction & Methodology
Investigators today are working with a greater amount of data than ever before, as well as a growing number
of formats, data sources, and versioning requirements, and yet they rely on achieving a unified picture in
order to make it actionable.
As global leaders in investigative analytics, we understand that the right data allows investigators to answer
time-sensitive questions, and critically – to fill the gaps and get the answer to the biggest question of all,
“What am I missing?” Without the ability to tag, sift, filter and analyze a growing wealth of data at speed,
and to connect the dots from one source to another – organizations will drown in the sheer volume of data
and manual work involved.
To get greater insight into the challenges for today’s CIOs and Head of Investigation stakeholders, and to
learn from their perspective what their wants and needs are in the market – we went straight to the source.
By speaking to 200 CIOs, CTOs, IT Directors, Directors of Technology and Heads of Artificial Intelligence, this
report takes the pulse of the industry in vital areas from investment priorities to cloud adoption, painting a
clear picture of the state of data fusion for investigation purposes today.
Methodology
We commissioned a survey of 200 senior employees across 14 countries, split between Western Europe
(45%), North America (30%), APAC (15%) and the rest of Europe (11%). The survey was completed by Global
Surveyz, an independent survey company, and took place during March 2022.
The survey responses are gleaned from Director to C-level roles who work at companies including Federal
and State Organizations (focusing on Law enforcement agencies at Federal and state level), Financial crime
units, Customs, IRS, and national security organizations. Respondents were recruited through a global B2B
research panel, invited via email to complete the survey. The average amount of time spent on the survey
was 6 minutes and 20 seconds. The answers to the majority of the non-numerical questions were
randomized, in order to prevent order bias in the answers.