The idea that data is critical to running our companies is nothing new. Our data investments have been focused on delivering tools and data to programmers that in turn deliver analytical tools to users. We never envisioned data evolving from the secret sauce that drives analytic tools to becoming an office supply for every worker. While data self-service is a top-of-mind discussion topic, our data infrastructure isn’t ready to deliver data that’s ready for use by the average staff member.
Our environments aren’t ready. The data is too complex: there are multiple storage locations (and copies), the data formats vary wildly, and the content is rarely documented. Our “solutions” have been built one application and platform at a time; they were never architected with the user in mind. Our technical teams are positioned to support platforms and analytics tool usage; we haven’t structured our teams to support data.
In this session, Evan Levy will discuss the challenges with supporting self-service data along with providing an architectural framework and the roles and responsibilities necessary to deliver self-service data.
You Will Learn
- An architectural framework for developing a custom self-service data architecture specific to your company’s strengths and needs.
- The methods and infrastructure changes required to support the growth in new data sources and alternative data content
- The tooling changes necessary to migrate from a BI/data warehouse environment to a data self-service environment
- Organizational roles and responsibilities that are necessary to support the shift to a self-service data environment
- CIOs and chief data officers, data architects, data developers, data governance staff, data management staff, business/data analysts, and data stakeholders