Book Image

Architecting Data-Intensive Applications

By : Anuj Kumar
Book Image

Architecting Data-Intensive Applications

By: Anuj Kumar

Overview of this book

<p>Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet ?uent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture.</p> <p>This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn’t fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand.</p>
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Chapter 5. Understanding Data Collection and Normalization Requirements and Techniques

So far, we have mostly discussed, at various levels of granularity, the architectural patterns that are important to keep in mind when designing a data-intensive system. As you will realize, knowledge of these Architectural Patterns will come in handy when we start to define the architecture of various functional components of a data-intensive system. This chapter starts diving deep in the first functional component that sits at the edge of any Data-Intensive System.

In this chapter, we will cover the following:

  • Understanding, with examples of use cases, how to approach pinning down the requirements for your data-collection system
  • Functional characteristics of a data collection System, such as keeping track of data lineage and preserving the quality of the data
  • Various types of data sources (this was also discussed in Chapter 4Discussing Data-Centric Architectures)
  • Various requirements (both functional and...