Data Science Texts

Discover what you don't know, and attack your weaknesses!

Databases

Strongly Recommended Prerequisites

Recommended Prerequisites

Data scientists interact with databases a lot. Most of the time, it's just through querying and updating databases. However, if you want to understand the engineering behind the database you're using, the books listed are a good place to start.

Recommended Books

  1. Fundamentals of Database Systems

    Ramez Elmasri and Shamkant B. Navathe

    (Image takes you to Amazon.)

    Key Features

    • In-text exercises

    Key Topics

    • Big Data
    • Centralized and Client/Server Architectures
    • Concurrency Control
    • Data Models, Schemas, and Instances
    • Data Warehousing
    • Database Architecture
    • Database Design Theory
    • Database Recovery
    • Database Security
    • Disk Storage
    • Distributed Databases
    • Enhanced Entity-Relationship Model
    • Entity-Relationship Model
    • Extensible Markup Language (XML)
    • Hadoop
    • Indexing Structures
    • Information Retrieval and Web Search
    • Map Reduce
    • Niche Database Models
    • NoSQL
    • Normalization
    • Object and Object Relational Databases
    • Online Analytical Processing (OLAP)
    • PHP
    • Query Processing and Optimization
    • Relational Algebra
    • Relational Calculus
    • Relational Data Model
    • SQL
    • SQL Constraints
    • Storage Architectures
    • Transaction Processing
    • Transactions
    • Web Database Programming

    Description

    This is one of those 1000+ page monstrosities. As its heft implies, it covers a lot of ground. Our favorite parts are the sections on query processing and optimization and distributed databases. You don't have to read the whole book in order to learn about the kinds of databases you use; the book is neatly organized into a large number of sections that you can pick and choose from.