I recently gave a presentation to the Tampa Bay IIBA, Data Skills for Business Analysts. As you’ll see, the presentation is mostly me talking about visuals from my new book, Not Just Data: How to Deliver Continuous Enterprise Data. The focus of the presentation is on data analysis techniques and data analysis ways of working (WoW).
The key takeaways of the presentation are:
- Data analysis is a critical aspect of many IT initiatives. The point is that it is worthwhile for business analysts to gain data analysis skills and knowledge and thereby increase the potential value that they have to offer teams.
- Data analysis requires technical skills, knowledge, and tooling. An important aspect of data analysis is profiling existing data sources to identify what they store and the quality of that data. This is work is technical in nature, requiring specialized (although common) tooling and data knowledge.
- It’s not just about data. This is good news for business analysts because they can leverage their existing non-data skills that data professionals often don’t have. The implication is that business analysts can bring knowledge and skills to data initiative and add value immediately, but only if they have a sufficient background in data skills to interact effectively with other team members.
The topics I discuss in the presentation include:
- Learning the data lingo
- Different data initiatives require different analysis skills
- A continuous enterprise data pipeline
- Agile model-driven development (AMDD)
- Initial modelling in an Obeya room
- The Vision canvas
- Personas
- Quality of service (QoS) requirements
- Question stories
- Question stories for AI
- Conceptual diagrams
- Report/UI sketches
- Domain models
- Acceptance criteria
- Physical data models
- The 7 Ws of Modelling
- Data profiling
- Different data consumers, different analysis WoW
- Enterprise metadata
- Analysis WoW during a sprint
- Look-ahead data analysis
- Continuous delivery/DataOps
- Data lineage
Recording: Data Skills for Business Analysts