BI systems have encapsulated a very waterfall-like approach, where a large amount of design work must be done by technology professionals up front, before even simple business analysis can be done. While business users may have self-service tools for data discovery and visualization, how does that help with the process of sourcing and preparing the data to be analyzed?
An agile approach is needed, but not one that’s sloppy. Pushing flat files into Hadoop may be tempting, but doing so has many of the same risks as storing lots of data in spreadsheets. What’s needed is something that provides structure but then gets out of the way, to allow for creative analysis. Between the waterfall approach of traditional BI and the entropy of “spreadmarts” and Hadoop lies a balanced approach. That’s what’s next for BI, and analytics in general.
In this webinar, our panel will discuss these topics and more:
- Can self-service data discovery tools be used to source and model data?
- Business users need machine data analytics, but can they work with machine data analytics tools?
- What would a data warehouse look like if it were designed for business users?
- Rich Morrow, founder / head geek, quicloud LLC
- Lynn Langit, Founder & Consultant, Lynn Langit
- David Loshin, Principal Consultant, Corporate Analyst/Advisor, Knowledge Integrity, Inc.
- Elad Israeli, Founder, CPO, SiSense