It turned out that what I wanted wasn’t to become a data scientist, it was to learn how use data in a way that actually helped organizations make better decisions. (View Highlight)
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Instead of focusing on the quasi-mystical arts of data science — they were figuring out how to apply battle tested software engineering best practices to data analysis. They believed that we could teach analysts to rethink their workflows and massively increase their impact by adopting some principles from developers. (View Highlight)
Analytics engineering solves the problems organizations actually have
There is almost no organization on the planet that could not benefit from having organized, well modeled data that unifies information from disparate sources and allows them to create well organized abstractions and data products. (View Highlight)
From the three person startups to the fortune 500 companies, from universities to NGOs, almost no one really feels like they have a full view into what is actually happening with the day to day data in their organizations. There are too many inputs coming from too many different places to get a clear picture of what is going on. (View Highlight)
Note: Glad we are not alone in this feeling
Analytics engineering allows you to massively scale yourself
One of the things that convinced me that analytics engineering was for me was when Tristan told me that a key part of the philosophy of dbt (and analytics engineering) is that it allows you to solve hard problems once, then gain benefits from that solution indefinitely. (View Highlight)
Historically many data or data adjacent jobs have involved a huge amount of repetitive, manual drudgery. Whether it’s hand crafting the same monthly spend report in Google Sheets or going into your marketing automation system and downloading five different csv files and Vlookuping them together, these tasks quickly begin to eat up your days and drain your soul. (View Highlight)
Note: Analytics manual work pain!
Spending your days working on manual tasks has two drawbacks. First — it is incredibly boring. Second, you pretty quickly hit a ceiling on the amount of reports and projects you can manage as these repeating tasks pile up and you simply don’t have time to do anything else. (View Highlight)
Note: List pulls eat bandwidth for higher impact work
