0%

Book Description

The demand for data scientists is well-known, but when it comes time to build solutions based on data, your company also needs data engineers—people with strong data warehousing and programming backgrounds. In fact, whether you’re powering self-driving cars or creating music playlists, this field has emerged as one of the most important in modern business. In this report, Lewis Gavin explores key aspects of data engineering and presents a case study from Spotify that demonstrates the tremendous value of this role.

Table of Contents

  1. What Is Data Engineering?
    1. Data Engineering Today
    2. Data Life Cycle
      1. Extract: Getting Data
      2. Transform: Clean, Prep, and Turn Data Into Information
      3. Load: Store Data in its Target Location
    3. Real Time
      1. Data Streams and Queues
      2. Reliability, Throughput, and Flexibility
    4. The Backbone of AI and Machine Learning
    5. Optimization
    6. Case Study: Spotify Discover Weekly Playlist
      1. Extraction and Real Time
      2. Transformation
      3. Load
    7. Summary
18.226.104.153