Day 2 at the Data School

Since yesterday was mainly tech setup and being introduced to other team members, today was our first day of training.

We covered modern data analytics, data architecture and the modern analytics pipeline.  Learning about how different software's and languages are split amongst different stages of the modern analytics pipeline made it easier to understand their functionality. Knowing how they function in data made it significantly easier when taking on the main task of today, choosing a company and outlining their modern analytics pipeline either in real life or theoretically.

I chose to look at Microsoft however, I zoomed in on their sales team in the Microsoft store. At first, it was quite straight forward as, by no surprise, Microsoft own everything they use. This included the stages for, ingestion, data prep, central storage etc. Of course, they use Power BI as their data visualisation software because, why wouldn't they?

After researching all the software's they could use for their pipeline I came across the Azure Data Factory Pipeline API that takes on raw data, ingestion, central storage and data preparation all in one. That saved quite a lot of time as 4 stages were being completed with their API.

To finish on a fun fact from today, Amazon make most of their profits from AWS (Amazon Web Services) rather than the Amazon delivery website itself. I guess online services win over same day delivery.

Author:
George Ledger
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