Part 1. Business scenarios.
I have spent many hours planning and executing in-company self-service BI implementation. This enabled me to gain several insights. Now that the ideas became mature enough and field-proven, I believe they are worth sharing. No matter how far you are in toying with potential approaches (possibly you are already in the thick of it!), I hope my attempt of describing feasible scenarios would provide a decent foundation.
All scenarios presume that IT plays its main role by owning the infrastructure, managing scalability, data security, and governance.
Scenario 1. Tableau Desktop + departmental/cross-functional data schemas.
This scenario involves gaining insights by data analysts on a daily basis. They might be either independent individuals or a team. Business users’ interaction with published workbooks is applicable, but limited to simple filtering.
User categories: professional data analysts;
Technical skills: intermediate/advanced SQL, intermediate/advanced Tableau;
Tableau training: 2-3 days full time (preferably) or continuous self-learning from scratch;
Licenses: Tableau Desktop.
Pros:
- Pure self-service BI approach with no IT involved in data analysis;
- Vast range of data available for analysis with almost no limits;
- Fast response for complex ad-hoc business problems.
Cons:
- Requires highly skilled data analysts;
- Most likely involves Tableau training on query performance optimisation on a particular data source (e.g. Vertica).
Advice:
- Create a “sandbox” that allows data analysts to query and collaborate on their own and without supervision. Further promotion of workbooks to production is welcome.
Scenario 2. Tableau Desktop + custom data marts.
In this scenario, business users are fully in charge of data analysis. IT provides custom data marts.
User categories: business users, line-managers;
Technical skills: basic SQL, basic/intermediate Tableau;
Tableau training: two or three 2-3h sessions + ad-hoc support on daily basis;
Licenses: Tableau Desktop + Server Interactors.
Pros:
- Easy access to data for ad-hoc analysis;
- Self-answering critical business questions;
- Self-publishing for further ad-hoc access across multiple devices.
Cons:
- Adding any data involves IT support;
- Requires elaborated data dictionaries.
Advice:
- Make requirements gathering a collaborative and iterative process with regular communication. That would ensure well-timed data delivery and quality;
- Deliver training in 2-3 wisely structured sections with 2-3 week breaks for business users to have time for playing with software, along with generating needs for the new skills.
- Focus on reach visualisations, not tables.
Scenario 3. Tableau Server Web Edit + workbook templates
This scenario fully relies on data models published by data analysts and powerful Web Edit features of Tableau Server.
User categories: line-managers, top managers;
Technical skills: Tableau basics;
Tableau training: one 30 min demo session + ad-hoc support;
License: Server Interactor.
Pros:
- No special training;
- Fast Tableau adoption with basic, but powerful Self-service BI capabilities (Web Edit);
- Thin client access via any Desktop Web Browser;
- Could serve as a foundation for self-service BI adoption among C-Suite.
Cons:
- High level of accuracy for data preparation and template development;
- Any changes in the data model require development and republishing of a template.
Advice:
- Try to select the most proactive and “data hungry” line manager or executive, who could help to spread the word;
- Investigate analytical needs, ensure availability of a subject matter expert;
- Start with simple visualisations, but be ready to increase complexity;
- Provide as much ad-hoc assistance as you can.
In my next post, I would like to throw light on some technical aspects and limitations of each scenario.
I highly appreciate any comments and looking forward to know about your experience.
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