My learnings from data exploration and visualization projects

With this article, I am sharing my learnings from working with Tableau across various data exploration and visualization projects, with the delivery perspective.

1. It improves the winability with your end customers because of the agile nature of the developments and shorter delivery time.
2. Success of the projects improves with positioning the execution closer to the consumer say with the business analysts or the power users. Overall I have seen it triggering better communication with the various stakeholders, as the various possibilities emanate during the iterative process. This frequent communications helps in the realization of an effective analytic faster.
3. Focus shifts from developer to the Business Analyst mindset. It’s the quality of alignment with the business processes, data, ability to mine data and extract insights that matters more than the technical skills (though that does help to go the extra mile). Therefore capabilities and the capacity should be aligned accordingly.
4. Though the enablement time is low relatively, it might be good to have an experienced hand to guide, especially at the beginning of the endeavour. This is because the approach to create the value is different from the typical BI projects. You may either cross skill existing resources or on board a small team depending on your work load and budget profile.
5. You can significantly cut the lead time to delivery, assuming the underlying data is readily available. However if you have a complex landscape with varied sources/processes/ masters etc., it might be better to leverage ETL / warehouse to get the data prepared for visualization. You need to ensure that good quality and consistent data is made available as input to the tool. That’s where the governance plays an important role.
6. Could be used for building the prototype for the consumer and then basis the feedback / value, decision can be taken to invest into the ETL flows / data warehouse objects for the dashboard. It can help do faster prototyping for your regular BI projects as well.
7. You can gain good expertise with such tools in short amount of time, say 2-3 years. At least that’s my perception while working with the tool. This excludes churning out really advanced custom Visualizations that have been done by the various Tableau experts. Though I believe that most of the value can be extracted for the business using the existing standard visualizations. You need to keep the maintenance aspect also into consideration while going for highly custom viz.
8. Does involve managing the change. Not all stakeholders might be initially comfortable with the visualizations. You might need to therefore look at ways to balance between the value derived from the dashboard and the amenability of the target audience.
9. Just because so many visualization options are available, there might be a tendency to use most in the viz. Empathy is the key. Think like your target audience. Keeping the why, what, how questions into perspective, will help you make simple, better, intuitive and actionable dashboards.