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

Another certificate in the pocket

The past two weeks I spent most of my time studying for the MS DA-100 exam, also known as ‘Analyzing Data with Microsoft Power BI’. This morning I took the exam and passed with a very decent score of 893/1000 (although I have to admit I was a bit annoyed not breaking the 900 barrier). After the training and passing the exam I am now skilled enough to start my own data analyzing projects. I’m looking for ideas where to apply my new skills.

Door |2021-05-20T12:08:33+02:0020 mei 2021|datascience, flow|0 Reacties

Transforming and visualising data using Power BI

The past two weeks I was introduced to the ins and outs of Power BI. Four full training days I’ve been practising doing transformations on columns, making calculated measures and dragging columns and measures into visualisations. For those who are not into data analyses, Power BI is a piece of software developed by Microsoft to handle data sets. When spreadsheets are no longer sufficient to handle your data, you can step up the game by using Power BI.

Before this training I practised with SQL and Python to create scatter plots and calculate summations, and I have to admit that after using Power BI I finally understand what kind of actions I was doing to data sets when using Python. Power BI is a visual tool, so you click on the transformations you need to do to prepare your data and the results are immediately visible. And you can easily undo a step with one click.

I wouldn’t say Power BI is data analysis for dummies, because you still need to know conceptually understand what you’re doing to the data, but I totally see why many people prefer using Power BI over messing about with Python. It is visual, quicker and can create interactive reports and dashboards. The reporting part is (for now) least interesting to me, as I don’t work in a big company with lots of (sales) data that needs to flow through the organisation. However, I do feel more confident after the past weeks that I’m capable to get meaningful information from data sets. And that was the whole point of investing in this course.

Door |2021-05-04T14:26:14+02:004 mei 2021|datascience, flow|0 Reacties

I passed an exam

If my memory is correct the last exam I took was in 2004, when handing in my master thesis (on blogging and Habermas, when blogging was still new and shiny). That was an oral exam, for two of my professors. I really can’t remember the last paper-based exam I took before being allowed to hand in my master thesis. It probably was not a memorable subject or one of those mandatory statistical analysis exams. Since 2004, I never needed to sit an exam for anything. Not even for an assessment for hiring purposes, as I’ve been self-employed since finishing university.

Today I broke that examless streak.

The program at Techionista is thoroughly sponsored by Microsoft and therefore I’m learning all about Microsoft Azure. And to be able to learn that you don’t just read documentation, you increase your knowledge by practicing for an exam. Today I took my first exam, on the Azure Fundamentals (AZ-900 for insiders) and passed it with a proper score of 820 (700 needed to pass).

To avoid installing proctoring software on my computer I reserved a slot at the nearest test center. That happens to be in my home town and I learned later that it’s run by an institute that teaches IT skills to (young) people who are either on the autistic spectrum or highly gifted (many of whom can’t manage to fit into the standard school system and drop out without a degree). I noticed that the person who took me through the sign-in procedure made sure every rule in the procedure was followed in a kind manner, he properly guarded the silence in the hall next to the exam room, and as a bonus earplugs were available for all examinees. I’ll schedule my next two exams here as well.

Door |2021-04-12T12:28:54+02:0012 april 2021|datascience, flow|0 Reacties

Becoming brainwashed by MS

A big part of my data & AI course is getting to know Microsoft Azure. This week I started learning the MS fundamentals course (part 1 – 6). It’s a crash course on server terminology, such as virtual machines, containers, VPN gateways and virtual networks. It’s a lot to take in and I’m not sure how much use I’ll have of the ins and outs of Azure, nonetheless it gives me a better understanding of it all so I can become a better translator between real server and data nerds and those who are not.

Door |2021-03-09T19:16:30+02:009 maart 2021|datascience, flow|0 Reacties
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