Architecting Data and Machine Learning Platforms

Chapter 1. Modernizing Your Data Platform: An Introductory Overview

Data is a valuable asset that can help your company make better decisions, identify new opportunities, and improve operations. Google in 2013 undertook a strategic project to increase employee retention by improving manager quality. Even something as loosey-goosey as manager skill could be studied in a data-driven manner. Google was able to improve management favorability from 83% to 88% by analyzing 10K performance reviews, identifying common behaviors of high-performing managers, and creating training programs. Another example of a strategic data project was carried out at Amazon. The ecommerce giant implemented a recommendation system based on customer behaviors that drove 35% of purchases in 2017. The Warriors, a San Francisco basketball team, is yet another example; they enacted an analytics program that helped catapult them to the top of their league. All these—employee retention, product recommendations, improving win rates—are examples of business goals that were achieved by modern data analytics.

To become a data-driven company, you need to build an ecosystem for data analytics, processing, and insights. This is because there are many different types of applications (websites, dashboards, mobile apps, ML models, distributed devices, etc.) that create and consume data. There are also many different departments within your company (finance, sales, marketing, operations, logistics, etc.) that need data-driven ...