Have you ever wondered how to build a contemporary analytics stack that is useful, scalable, and easy to maintain? And have you looked into building such a stack, only to find yourself quickly drowning in a sea of jargon?
We know how that feels, because we’ve been there. The truth is that much knowledge of modern data analytics is locked up in the heads of busy practitioners. Very little of it is laid out in a self-contained format.
In this short book, we will give you a practical, high-level understanding of a modern analytics system. We will show you what the components of most modern data stacks are, and how best to put everything together.
This book is suitable for technical team members who are looking into setting up an analytics stack for their company for the very first time.
I’m shocked to be telling you this next sentence: I read a free ebook from a company and actually loved it.See full review here
I would say it’s a must read for any company that is starting to venture into the big data realm. It’s a light read but addresses many important concepts to approach analytics in a scalable way.
Head of Group Analytics, LinkAja
I love that you went into more detail in the later chapters around modeling, transformations, and providing real-world case studies like the Snowplow case which I'd love to hear more about!
Analytics Engineering Consultant
[...] the book is great and is exactly what someone in my position needs, especially the part about the EL tools, the data modeling layer, and the relationship between the CEO and the Data Analyst.
Head of BI & Data, Unissu
I thought ELT was just another cool kids’ jargon [...] Chapter 2 slapped me hard in the face telling me that I was concluding too soon and I know nothing about it.
Data Engineer, Vidio
What does a simple and modern analytics setup look like?
How can I deploy one quickly yet still scales with my company's growth?
Consolidating data from different source systems
Why and when to choose a data warehouse?
ELT vs ETL: what's the big deal?
Why ELT is better than ETL is the modern era
Data modeling concept, and why it is important
Kimball's Dimensional Data Modeling
How has data modeling evolved in modern cloud era?
Why the market of business intelligence tools is so confusing today?
What should I look at when evaluating business intelligence tools?
The arc of adoption: How your company's BI culture will evolve over time
We've been making data analytics tools for over four years, and helped more than a hundred companies build their business intelligence capabilities, sometimes from scratch.