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Different types of talents can contribute to Data & AI projects and business achievements in various ways. Data & AI communities support ideation, accelerate projects execution,
prepare adoption and raise data literacy in the long term.
Data communities regroup and engage many profiles and roles around shared interests and expertise. They span across departments or other organizational boundaries.
These groups help organizations make Data & AI ubiquitous. Strengthen collaboration, support ideation, accelerate executions, encourage adoption, raise data literacy, and develop a strong data culture, data communities help the organization to be ready for future challenges.
Engage the right talents in the right initiatives and at the right moment: to design initiatives, get expertise support, identify data sources, prepare adoption, etc.
Orchestrate validation processes, tasks and synchronization across Data & AI products to ensure alignment and accelerate.
Achieve a shared and holistic view of data initiatives and assets, through multi-faceted communications and contributions.
Achieve the 3Us (Useful, Usable, Used) for your Data & AI initiatives by engaging users and stakeholders. And accelerate delivery by relying on the right expertise.
"Culture and data literacy are the top two roadblocks for data and analytics leaders" (Gartner, 2021).
Communities enable to scale literacy efforts and developing a data culture supports data-driven ambitions of the enterprise and encourages data monetization efforts.
Review day-to-day struggles and technology capabilities with creative mindsets. Accelerate the development of innovative ideas and use the investment in data & innovation to shape the future of the organization.
At least 30% of US companies reporting creating a data-driven culture is their main challenge (Gartner, 2020).
Tackling culture challenges can be tough to data leaders. In order to guide managers along the journey, we collected best practices to explain why data communities are important and how you can enable them in your organization. People are the key to data-driven and insights-driven transformation.
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