Building Data Products Introduction to Data and Analytics Engineering for non-programmers Author: Brian McMillan Released: July 2021 Publisher: minimumviablearchitecture.com ISBN: 978-1-7375365 Suggested Price: $34.99 |
Book Description
To understand Data and Analytics Engineering, a diverse group of non-technical people needs a broad exposure to specific technical skills and tools. However, in order to be effective, everyone involved, including non-technical managers, needs to understand the larger philosophy of software development. This book covers both.
If you are a manager focused on the difficulties of running a business faced with constant change and competition, this book introduces a number of ways to identify, manage, communicate, and measure what is most valuable. If you are an analyst faced with the simple fact that there are never enough hours in the day to get everything done, this book balances the typical technical demonstrations with software development philosophy and business management strategies you can use to maintain focus on delivering the things with the highest business value in a sustainable way. For seasoned engineers and educators, this book is intended to serve as an introduction to teaching the hard and soft skills needed to effectively understand the entire product lifecycle and foundational philosophies of data and analytics engineering.
Professional skills:
Technical Skills:
To understand Data and Analytics Engineering, a diverse group of non-technical people needs a broad exposure to specific technical skills and tools. However, in order to be effective, everyone involved, including non-technical managers, needs to understand the larger philosophy of software development. This book covers both.
If you are a manager focused on the difficulties of running a business faced with constant change and competition, this book introduces a number of ways to identify, manage, communicate, and measure what is most valuable. If you are an analyst faced with the simple fact that there are never enough hours in the day to get everything done, this book balances the typical technical demonstrations with software development philosophy and business management strategies you can use to maintain focus on delivering the things with the highest business value in a sustainable way. For seasoned engineers and educators, this book is intended to serve as an introduction to teaching the hard and soft skills needed to effectively understand the entire product lifecycle and foundational philosophies of data and analytics engineering.
Professional skills:
- Learn how to assess the financial maturity of a company.
- Learn how to assess the life cycle phase of any product.
- Learn how to use both to identify the most valuable goal to pursue.
- Apply agile principles and strategies to improve the development speed, reliability, and usability of data.
Technical Skills:
- Develop a toolbox of open-source software tools to dramatically reduce the time needed to deliver data products to stakeholders.
- Learn how to apply modern DevOps practices to data management.
- Confidently manage, explore, and share any data set.
- Efficiently automate complex workflows.
- Build complex data visualizations with code instead of GUI applications.
- Build and deploy a micro-data warehouse and learn valuable SQL development patterns.
- Build and deploy data using web services.
Business Stack:
Theory of Constraints / Throughput Economics
3X product lifecycle model
Wardley Maps
Extreme Programming (XP)
Technology Stack:
Standard UNIX command line utilities
GNU Make
SQLite database
CSV, JSON, Excel files
CSVKit
CSV-Utilities
Datasette
VegaLite
Google CloudRun
Theory of Constraints / Throughput Economics
3X product lifecycle model
Wardley Maps
Extreme Programming (XP)
Technology Stack:
Standard UNIX command line utilities
GNU Make
SQLite database
CSV, JSON, Excel files
CSVKit
CSV-Utilities
Datasette
VegaLite
Google CloudRun