#QlikScripting

[mydatastuff]

From reddit:

How to get more analysts to think of PowerBI (and other BI tools) as a valuable skill worth investing in?

Curious what other data team managers experience has been on this topic.

I have some theories on why "BI" has gotten a bad reputation: 1) other "keyword" skills often pay more. If you just search for BI analyst on any job portal maybe you'll see a 70k average while say a "data engineer" who focuses on python may be $120k+ 2) some parts of the core BI skills, like DAX or QlikScript are not as portable to new jobs as say getting really good at something like Python. 3) 90% of BI usage is frontend dashboard creation, relatively few analysts get deep in the weeds of the more advanced functionality like maintaining semantic layers at scale, role based permissioning etc.. Thus maybe mostly only leads or managers handle these and most others don't touch it. Maybe most BI users are doing like local tableu dashboards from Excel imports and don't even host it in the cloud anywhere?

Bullet 1 is definitely true, similar to the title of "data scientist" within the realm of "BI" there is an insanely wide range of skillsets and it's hard for the market to tease out and properly reward

Bullet 2 is true in that specific BI syntax is not portable beyond 1 vendor. However the same could be said of SparkSQL vs BigQuerySQL or dplyr vs. data.tables or keras vs pytorch, yet the underlying skills are quite transferrable. In particular proper data modeling and being able to transform business metrics into reliable code are timeless skills and worth their weight in gold.

Bullet 3 could potentially be true but I imagine large orgs using say PowerBI at scale HAVE TO employ principal PowerBI engineers with many years of tech experience, or else their mission critical reporting tools would just break... All the time. So maybe these job titles doing the more advanced work are just hidden as software engineers or something else?

[rphpacheco]

Neste vídeo, vamos abordar uma prática muito comum no fluxo de desenvolvimento de Aplicações de Business Intelligence, onde temos uma pasta que recebe periodicamente arquivos e nossa tarefa é ler o conteúdo destes arquivos, para em seguida movê-los para uma pasta processados.