Pitfalls and pro-tips for effective and transparent BI tools data science & applications

on YouTube ↗37m

" summary

Practical rules for self‑service BI: track data lineage with Confluence or a GitHub repo so analysts see source fields, favor a layered stack — a data reader (Tableau/MicroStrategy) over a prep layer (Alteryx/RapidMiner) and ETL (SSIS or Python on AWS/GCP/Azure) — and monitor with both the BI tool and external watchdogs. Embrace barely sufficient production answers, focus on one optimization goal at a time, accept recurring maintenance (the Golden Gate gets repainted every seven years) and prioritize keep the lights on reliability.

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" chapters (6)

1. 0:00Start
2. 1:12About Me
3. 3:44Agenda
4. 11:00Routine maintenance for flexible persistence
5. 15:06Yes but no and it depends (The Rule of 3)
6. 25:17Workflow automation lifecycle for self service BI

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