The roles in data

For those who are not familiar with the variations of roles in the field of data, this is what I’ve learned so far about those roles. You have data analysts, data architects, data engineers and data scientists.

A data analyst works on, no surprise, analysing data. Often these are people preparing reports (for instance on sales performance) for management. When working in Microsoft Azure, you would spend a lot of time using Power BI to create reports, using polished data sets to perform transformations and calculations. Your goal is to create visualizations that anyone else in your organisation can easily understand.

To create those polished data sets for analysts to work with, you need a data infrastructure. That’s where the data architect comes in. An architect thinks through what the data needs are on one end, knows the perks of the raw data coming in at the other end and then designs the infrastructure in between.

The data engineer then uses the input from the data architect to build the infrastructure.

Sometimes you want to dig deeper into your data and discover more complex patterns. That’s where the data scientist comes in. These math wizards apply statistical, machine learning and AI models to data and are able to tweak these models using there mathematical knowledge.

I was rather surprised to learn how working in data, a relatively new field to work in, already split up in so many roles. And then I’m not even talking about all the specialisations you could choose within these roles for hard core programmers. For instance my trainer worked for many years solely on optimising SQL statements for a living.

My education prepares me for two roles mainly: the analyst and the engineer. I’m most definitely happy with all the skills I learned about using Power BI. That will help me a lot when I start digging for stories using data sets. The data engineering part is absolutely not my cup of tea. It’s really theoretical and an in-depth crash course on database management and Azure cloud infrastructure. You can compare it to fitting electrical pipes in your home. It needs to be done, otherwise you can’t live in your home, but it’s not as exciting as decorating your home. At least I get more excited about decoration and design than fitting pipes. That said, I’m still very happy to get a solid understanding of the inner workings of databases and the cloud tools one needs to create usable data from raw data. It helps me to be able to instruct others to click the right buttons, write the proper SQL statements and build the pipelines for me, so that I can dig for the data story gold 😉

Door |2021-06-23T17:10:12+02:0023 juni 2021|datascience, flow|0 Reacties

Read: What’s women really holding back?

This article reveals how strong narratives about gender roles when it comes to take care of kids in combination with a professional career are.

Eli and Padavic conducted research within a big global consultancy firm to help them figure out why women were progressing less than men career wise within their company. They conducted interviews and revealed a strong narrative:

High-level jobs require extremely long hours, women’s devotion to family makes it impossible for them to put in those hours, and their careers suffer as a result. We call this explanation the work/family narrative.

However, the men they interviewed talked about their struggle to balance their work with family life as well. They started investigating deeper why men progressed in their career despite feeling as much pressure finding a balance between work and family as women.

Their main conclusion:

Women were held back because, unlike men, they were encouraged to take accommodations, such as going part-time and shifting to internally facing roles, which derailed their careers. The real culprit was a general culture of overwork that hurt both men and women and locked gender inequality in place.

Using company data they revealed some disconnects between the company’s narrative and actual behaviour. There was no higher turnover rates for men and women, career progression of childless women was just as low as mothers’ progression, accommodation was almost only taken by women while two-third of male interviewees struggled as much as women in work-family balance and many of the interviews questioned the 24/7 work schedule mentality to overdeliver to clients who don’t really need that.

This is what they told the leaders of the company after their research:

For the firm to address its gender problem, it would have to address its long-hours problem. And the way to start would be to stop overselling and overdelivering.

And of course the leaders….dismissed this solid piece of advise and held on to the existing narrative that women were struggling to keep a balance between work and family and therefore solutions have to target women specifically.

The rest of the article, the researchers dive deep into why these leaders rather hang on to the existing narrative rather than to accept that long working hours are counter productive and holding women back. Read it. It’s an excellent piece of work.

Door |2020-04-20T18:00:12+02:0020 april 2020|flow, vrouw|1 Reactie

Solving a jigsaw

I’m deep into editing a documentary (not meant for public viewing) and with the amount of interviews I’ve done (eight) it’s like solving a jigsaw puzzle, yet I have random pieces that I have to shape individually to make them fit together, all the while knowing I’ll never be able to replicate the image on the box.

Door |2019-08-13T21:22:20+02:0013 augustus 2019|deze dag, flow|0 Reacties

Work

I don’t often work during weekends, but today I had the pleasure of filming eight millennials about their year living abroad through the Rotary Exchange. Wonderful stories were shared.

My portable studio set up using coloured led bars for background variation.
Door |2019-06-22T20:26:15+02:0022 juni 2019|deze dag|0 Reacties
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