In the past, only IT departments could deploy the expensive storage and computing power needed for effective analytics. Only IT understood the technical issues and—very importantly—only IT could secure the data and the resulting analysis to ensure the right people had access to the right insights.
However, relations between business users and IT have changed dramatically. Beginning with mobile devices and extending to apps, infrastructure, and even data, users now have easy access to better technology and faster upgrades than IT can provision. Business analysts have embraced self-service business intelligence “with or without IT’s permission,” as analysts have noted. What can IT do now, in the age of self-service, to manage this rapidly changing environment? What can business users do to work more effectively with IT?
In this course we will lay out a new model of governance and compliance specifically tailored to the needs of organizations enabling self-service analytics.
You Will Learn
- The factors that drive self-service adoption of new technologies, tools, and data
- Why a traditional data warehouse may not be right for managing self-service demands
- Whether a data lake or other big data architecture is suitable for managing self-service
- How IT can provision data and analytics services for business users
- What the responsibilities of business users are when working in a self-service mode, and how those responsibilities can be governed
- Why the “data supply chain” is a better model for self-service management than traditional life cycle models
- How users should choose tools for self-service business intelligence, and what the most important features of the user experience are that will benefit both ease-of-use and governance