1 Getting started: establishing your data pipeline

 

This chapter covers

  • Understanding the what and why of data wrangling
  • Defining the difference between data wrangling and data analysis
  • Learning when it’s appropriate to use JavaScript for data analysis
  • Gathering the tools you need in your toolkit for JavaScript data wrangling
  • Walking through the data-wrangling process
  • Getting an overview of a real data pipeline

1.1 Why data wrangling?

Our modern world seems to revolve around data. You see it almost everywhere you look. If data can be collected, then it’s being collected, and sometimes you must try to make sense of it.

Analytics is an essential component of decision-making in business. How are users responding to your app or service? If you make a change to the way you do business, does it help or make things worse? These are the kinds of questions that businesses are asking of their data. Making better use of your data and getting useful answers can help put us ahead of the competition.

Data is also used by governments to make policies based on evidence, and with more and more open data becoming available, citizens also have a part to play in analyzing and understanding this data.

1.2 What’s data wrangling?

1.3 Why a book on JavaScript data wrangling?

1.4 What will you get out of this book?

1.5 Why use JavaScript for data wrangling?

1.6 Is JavaScript appropriate for data analysis?

1.7 Navigating the JavaScript ecosystem

1.8 Assembling your toolkit

1.9 Establishing your data pipeline

1.9.1 Setting the stage

1.9.2 The data-wrangling process

1.9.3 Planning

1.9.4 Acquisition, storage, and retrieval

1.9.5 Exploratory coding

1.9.6 Clean and prepare

1.9.7 Analysis

1.9.8 Visualization

1.9.9 Getting to production

Summary