  Managing data related to a software product and its development poses
significant challenges for software projects and agile development teams.
Challenges include integrating data from diverse sources and ensuring data
quality in light of continuous change and adaptation. To this end, we aimed to
systematically explore data management challenges and potential solutions in
agile projects. We employed a mixed-methods approach, utilizing a systematic
literature review (SLR) to understand the state-of-research followed by a
survey with practitioners to reflect on the state-of-practice. In the SLR, we
reviewed 45 studies in which we identified and categorized data management
aspects and the associated challenges and solutions. In the practitioner
survey, we captured practical experiences and solutions from 32 industry
experts to complement the findings from the SLR. Our findings reveal major data
management challenges reported in both the SLR and practitioner survey, such as
managing data integration processes, capturing diverse data, automating data
collection, and meeting real-time analysis requirements. Based on our findings,
we present implications for practitioners and researchers, which include the
necessity of developing clear data management policies, training on data
management tools, and adopting new data management strategies that enhance
agility, improve product quality, and facilitate better project outcomes.
