As businesses work to become more data-driven, it's crucial to promote the sourcing and consumption of data outside the IT organization. Self-service data models are becoming more popular, bringing flexibility, speed and agility to decision makers. However, if deployed without the proper protocols and technologies in place, self-service models will fail. In order to be successful, data and analytics leaders must ensure they take inventory of D&A assets, promote collaboration across teams, improve data literacy, enhance and standardize technologies as well as implement adaptive governance for analytics.
In this interactive discussion, CDAOs will explore strategies to enable self-service data models.
Topic 1: Instituting the proper operating model, governance and processes for self-service
- What does self-service mean to you?
- Is your operating model currently set up to enable self-service models and analytics?
- How do you balance self-service with governance?
Topic 2: Building a data-literate workforce to interpret data sets
- How important are the cultural aspects of enabling self-service?
- How are you training teams across your organization to discern and incorporate data into decision making?
- How are you building context into data and monitoring quality to maintain trust?